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Functional-element constraint hydrocarbon distribution model and its application in the 3rd member of Dongying Formation, Nanpu Sag, Bohai Bay Basin, eastern China
Journal of Petroleum Science and Engineering 139 (2016) 71–84
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Functional-element constraint hydrocarbon distribution model and its application in the 3rd member of Dongying Formation, Nanpu Sag, Bohai Bay Basin, eastern China Jigang Guo a,n, Jing Xu b,c, Fengtao Guo d, Jianhua Li e, Xiongqi Pang b,c, Yuexia Dong f, Tao Hu b,c a
Strategic Research Center of Oil and Gas Resources, Ministry of Land and Resources, Beijing 100034, China Research Center of Basin and Reservoir, China University of Petroleum, Beijing 102249, China State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China d Australian School of Petroleum, The University of Adelaide, SA 5005, Australia e Sinochem Petroleum Exploration & Production Co., Ltd., Beijing 100031, China f PetroChina Jidong Oilfield Company, Tangshan 063004, China b c
art ic l e i nf o
a b s t r a c t
Article history: Received 5 December 2015 Accepted 14 December 2015 Available online 18 December 2015
The proposed functional-element constraint hydrocarbon distribution model consists of four basic functional elements including regional cap rock (C), favorable sedimentary facies (D), interfacial potential (P) and source kitchen (S). The combination of the four functional elements controls the formation and distribution of stratigraphic reservoirs in a basin. Regions with spatial and temporal overlaps of the four functional elements are the favorable zones for stratigraphic reservoirs. The geometric mean of the frequency of the four functional elements could indicate the possible distribution of stratigraphic reservoirs in a target zone. This paper describes constraint functions of the four functional elements on the hydrocarbon accumulations and their quantitative characterization. The hydrocarbon distribution model based on functional elements can predict development of stratigraphic reservoirs using T-CDPS, and the possibility for reservoir formation is determined by the index, Tcdps, in this paper. Based on the model, we have predicted seven areas of the Paleogene Ed3 in Nanpu Sag, which are favorable or moderately favorable for stratigraphic reservoir distribution. Among all the seven areas, five areas located in the Gaoshangpu structural belt, south of Laoyemiao structural belt and Nanpu I, II, V structural belt were favorable areas. Two moderately favorable areas were located in Nanpu III structural belt and Nanpu IV structural belt. & 2015 Elsevier B.V. All rights reserved.
Keywords: Functional-elements constraint model Stratigraphic reservoir Prediction of favorable hydrocarbon accumulation area The 3rd member of Dongying Formation Nanpu Sag
1. Introduction Stratigraphic reservoirs are an important type of subtle reservoir plays which not only represent an important research field in modern petroleum geology, but have also become the primary target of contemporary hydrocarbon exploration worldwide. Stratigraphic reservoirs are accumulations of hydrocarbons in traps formed by the change of reservoir lithology, lithic facies and property, which consist of updip pinch-out and lenticular sand reservoirs (Tissot and Welte, 1978). We mainly talk about the conventional stratigraphic reservoirs. Unconventional stratigraphic reservoirs such as tight gas reservoir is not discussed in this paper. With increasing exploration degree and decreasing n
Corresponding author. E-mail address: [email protected] (J. Guo).
http://dx.doi.org/10.1016/j.petrol.2015.12.017 0920-4105/& 2015 Elsevier B.V. All rights reserved.
possbility of discovering large-scale structural reservoirs, stratigraphic reservoirs have become increasingly important in oil-gas exploration. The recent Oil and Gas Resource Assessment showed that the proportion of litho-stratigraphic reservoir plays has reached 42% of the remaining onshore oil and gas resources in China (Zhao et al., 2004). Litho-stratigraphic reservoirs are becoming the most realistic potential and universal oil and gas plays in China (Jia et al., 2004). Petroleum geologists in China have recently achieved fruitful results in research on stratigraphic reservoir formation and distribution. Fu et al. (2002) put forward three mechanisms for the formation of stratigraphic reservoirs: (1) oil or gas migrating from the source rock, or source kitchen into stratigraphic traps in the source rock and forming oil or gas reservoirs via capillary pressure; (2) oil or gas generated from the source rock migrating into stratigraphic traps above the source rock and forming oil and gas reservoirs under the dual influence of abnormal pore fluid
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pressure and buoyancy; and (3) oil or gas generated from the source migrating into stratigraphic traps below the source rock and forming oil or gas reservoirs via abnormal pore fluid pressure. Chen et al. (2003a) proposed a ternary genetic mechanism for the formation of stratigraphic reservoirs, which are mainly controlled by the hydrocarbon source, the reservoir's petrophysical properties, and the sandbody genetic type. Liu et al. (2006) put forward
the notion of a quaternary control mechanism for stratigraphic reservoirs, believing that their formation is determined by four key factors: hydrocarbon migration pathway conditions, fluid dynamics conditions, critical physical properties of reservoirs, and the sealing conditions of the traps. Pang et al. (2007) proposed a geological model in which reservoir formation and distribution are controlled by favorable facies–low potential coupling, and applied
Fig. 1. (A) Location map of the study area showing the sub-tectonic units of the Bohai Bay Basin (modified from Dong et al. (2010)); (B) distribution of main structural elements, normal faults and discovered oilfields within the Nanpu Sag (modified from Dong et al. (2010) and Xu et al. (2008)). The sections’ and wells’ locations are also shown.
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it to predict the distribution of stratigraphic reservoirs in continental faulted basins. The Napu Sag is a well-known small but petroliferous sag located in the northwestern Bohai Bay Basin. The Neogene, Paleogene sandstones and pre-Paleogene buried hills are the most important exploration targets. After nearly 40-year oil and gas exploration and development, the proved rate of Nanpu Sag is higher and higher. While previous hydrocarbon reservoirs were mainly discovered in structural traps, major breakthroughs have been made in the exploration for the Paleogene stratigraphic reservoirs in recent years (Xu et al., 2008; Liu, 2008). To date, reserve in place in the Nanpu Sag has been proved more than 10 108t, and that of stratigraphic reservoirs is about 3 108t (Xu et al., 2008). However, the complex formation and distribution mechanisms of stratigraphic reservoirs have become a bottleneck in stratigraphic oil and gas reservoir exploration, which makes the prediction of favorable areas extremely challenging. Therefore, new effective technologies and methods are needed. The proposed functional-element constraint hydrocarbon distribution model in this paper defines four basic functional elements including regional cap rock (C), favorable sedimentary facies (D), interfacial potential (P, The interfacial potential control function refers to hydrocarbon accumulation in zones of relatively high-porosity and permeability through capillary pressure due to the coexistence of multiphase fluids (England et al., 1987). Hubbert (1953) has shown that hydrocarbon migration is bounded by the capillary properties of the reservoir rock and the boundary rock, which bears displacement pressure differences. England et al. (1987) later integrated interfacial tension as a driving force when using the fluid potentials to describe the migration of petroleum fluids. We call this contribution of fluid potential caused by interfacial tension the interfacial potential, which is quite significant), and source kitchen (S) to be the key elements affecting the hydrocarbon accumulation in stratigraphic reservoirs in a basin. We have established a new conceptual geologic model, “T-CDPS”, a functional-element constraint hydrocarbon distribution model for quantitatively predicting favorable areas of stratigraphic reservoir distribution in the Nanpu Sag.
2. Geological setting The Bohai Bay Basin, an important hydrocarbon-producing province in China, is located on the eastern coast of China and
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covers an area of approximately 200,000 km2 appearing as a north-east-trending “lazy-Z” pattern on the regional geologic map (Dong et al., 2010). It consists of six major sub-basins or depressions, including Liaohe–Liaodong, Bozhong, Jiyang, Jizhong, Huanghua, and Linqing-Dongpu sub-basins or depressions, and five major uplifted blocks including Cheng-ning, Shaleitian, Cangxian, Xing-heng, and Neihuang, from the northeast to the southwest (Gong, 1997) (Fig. 1A). The Nanpu Sag, one of the many small sags within the giant Bohai Bay Basin, is located in the northeast part of Huanghua Depression and covers an area of only 1930 km2. It is bounded by the Shaleitian fault to the south and the Xinanzhuang–Baigezhuang fault to the north and east. Structurally, the sag is a half-graben, and the latter two faults serve as border faults that have a steep dip toward the south and southwest (Wang et al., 2002). Eight northeast-trending major structures have been identified in the sag, including the Gaoshangpu, Liuzan, Laoyemiao onshore, and Nanpu 1, Nanpu 2, Nanpu 3, Nanpu 4, and Nanpu 5 structures offshore (Wang et al., 2002) (Figs. 1B and 2). The sedimentary stratigraphy of Nanpu Sag has been extensively studied mostly through drilling for hydrocarbon exploration. It is filled with a thick sequence of Cenozoic strata (5000–9000 m) which comprises the Eocene Shahejie Formation (Es), the Oligocene Dongying Formation (Ed), and the Miocene Guantao (Ng) and Minghuazhen Formations (Nm), and the Quaternary Pingyuan Formation (Qp) (Wang et al., 2002; Jiang et al., 2009) (Fig. 3). The Shahejie Formation contains the main source rocks and sandstone reservoir rocks and is divided into three intervals, Es1, Es2, and Es3 (from top to base). The lower member, Es3, is further divided into five submembers, Es31, Es32, Es33, Es34, and Es35, from top to bottom, and the lithologic description of each submember is provided in Fig. 3 (Wang et al., 2002; Jiang et al., 2009). The middle member, Es2, is a suite of alluvial sediments composed of dominantly reddish mudstone interbedded with thin layers of sandstone. The upper member, Es1, is characterized by shallow lacustrine lithofacies (Dong et al., 2010). The Dongying Formation (Ed) consists of three members, Ed1, Ed2, and Ed3, from top to bottom. This formation is a set of lacustrine deposits up to 500–600 m onshore and 1500–2000 m offshore (Wang et al., 2002). The Neogene Guantao and Minghuazhen formations throughout the whole Bohai Bay Basin are deposited in a braided fluvial system and a low-sinuosity fluvial system, respectively (Wang et al., 2002).
Fig. 2. Cross-section (AA′ in Fig. 1) of the Nanpu Sag showing the various tectonic–structural zones and source–reservoir–seal combination.
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Fig. 3. Generalized Cainozoic stratigraphy of the Nanpu Sag, showing depositional environment, tectonic evolution stages and the major petroleum system elements including the Es3, Es1, and Ed3 source rocks, multiple reservoir intervals and sealing units (modified from Dong et al. (2010) and Wang et al. (2002)).
The gray to black mudstones, calcareous mudstones and oil shales in the lower Es34 and upper Es1 intervals of the Eocene Shahejie Formation and Ed3 interval of the Oligocene Dongying Formation are considered as the main source rocks (Zheng et al., 2007; Zhu et al., 2011). Eocene–Oligocene syn-rifting lacustrine fan-delta sands and subaqueous fans and Miocene–Pliocene postrifting fluvial facies serve as major reservoir rocks (Dong, 2002).
The thick and widely distributed basalts and mudstones in Guantao Formation and mudstones developed stably in the upper member of Minghuazhen Formation serve generally as two sets of regional seal (Zhu et al., 2011; Wan et al., 2013). Above-source play (Ed1–Nm), in-source play (Es4–Ed2), and below-source play (O–Mz) had been distinguished according to the source–reservoir configuration (Xu et al., 2008; Tan and Tian, 2000). There are anticlinal,
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faulted anticlinal, fault, stratigraphic, stratigraphic and buried hill reservoirs in the Nanpu Sag (Dong, 2002; Xu et al., 2008) (Fig. 2), and the 3rd member in Dongying Formation was one of the most petroliferous layers abundant of stratigraphic reservoirs (Xu et al., 2008; Liu, 2008).
3. Methods 3.1. Main controlling factors on stratigraphic reservoir formation and distribution and their quantitative characterization in the Nanpu Sag Hydrocarbon reservoir formation and distribution is the result of the combined action of six major geological factors: namely source condition, reservoir condition, caprock condition, migration condition, trap condition and conservation condition. Each of these may involve multiple minor discrete geological elements. For a given petroliferous basin or Sag, the factors controlling hydrocarbon reservoir formation and distribution may be more complex. Based on a study of the geological characteristics of the stratigraphic reservoirs in the Nanpu Sag, we conclude that regional caprock (C), favorable sedimentary facies (D), interfacial potential (P) and source kitchen (S) are the four key geological functional elements controlling stratigraphic reservoir formation and distribution. The term “functional elements” refers to fundamental geological factors controlling hydrocarbon reservoir formation and distribution that can be described objectively and characterized quantitatively. For the sake of discussion, we represent them here by the abbreviations C, D, P and S, respectively. 3.1.1. Hydrocarbon kitchen constraint and its quantitative characterization 3.1.1.1. Hydrocarbon kitchen control on the planar range of hydrocarbon reservoir distribution. Hydrocarbon kitchens refer to the range of conditions where the source rock generates and expels hydrocarbon at a particular geological time or during the period of reservoir formation. Some geologists define it as the effective range of source rock distribution at a particular geological period. Hydrocarbon kitchens provide source for reservoir formation, and their distribution ranges determine the planar ranges of hydrocarbon accumulation distribution. Previous researchers have carried out many studies of hydrocarbon kitchen controlling functions (e.g. Dai et al., 1996; Hu, 1982, 2005; Jin et al., 2003; Pang, 2003). Their results show that the size of a hydrocarbon kitchen and the quantity of hydrocarbons it generates and expels determine the scale, range and resource capabilities of the hydrocarbon reservoir formation. Three sets of source rocks appear in the Nanpu Sag: Paleogene Es34, Es1 and Ed3. Exploration results have shown that these source rocks supply abundant hydrocarbon resources to the reservoirs, and control how far the hydrocarbons migrate and the planar distribution of hydrocarbon reservoirs. The hydrocarbon expulsion intensity and volume from these three sets of source rocks are obtained by the petroleum generation potential method proposed by Guo et al. (2014). The generated and expelled hydrocarbons migrate over a relatively short range. These hydrocarbon reservoirs are distributed within 30 km of the source rock boundary with most of the distance less than 15 km (Fig. 4). They are basically located around, or within the hydrocarbon-generation sags in the Napu Sag. The Neogene-Paleogene reservoirs and the pre-Paleogene buried hill reservoirs, whose hydrocarbons come from Es3, Es1, and Ed3 source rocks, are found around the center of hydrocarbon expulsion of source rocks (Fig. 5). 3.1.1.2. Quantitative characterization of hydrocarbon kitchen control function. We propose the frequency of reservoir formation to be used to quantitatively characterize the hydrocarbon kitchen constraining
Fig. 4. Relationship between hydrocarbon reservoirs and hydrocarbon kitchens in the Nanpu Sag.
function. Research has shown that the reservoir formation frequency within the hydrocarbon distribution threshold is determined by three geological conditions (Jiang, 2008): the hydrocarbon-expulsion intensity center; the distance between the hydrocarbon-expulsion center and the reservoir; and the distance between the hydrocarbon-expulsion boundary and the reservoir. Combining these allows the reservoir formation frequency of hydrocarbon kitchen control to be calculated (Eq. (1), Jiang et al., 2013): 2
Ys = 0.046e 0.12qe − 0.16 ln (L ) + 0.65e−8.2357 (l + 0.1) + 0.1345
(1)
where Ys is the reservoir formation frequency at a point influenced by the hydrocarbon kitchen; L is the standardized distance between the hydrocarbon reservoir and the hydrocarbon-expulsion center, 0–2.5 (Jiang et al., 2013); l is the standardized distance between the hydrocarbon reservoir and the hydrocarbon-expulsion boundary (positive when the hydrocarbon reservoir is outside the hydrocarbon-expulsion boundary, and negative when the hydrocarbon reservoir is within the hydrocarbon-expulsion boundary), 1 to 1 (Jiang et al., 2013); and qe is the maximum hydrocarbon-expulsion intensity of the hydrocarbon kitchen (106 t/km2). 3.1.2. The interfacial potential constraint and its quantitative characterization 3.1.2.1. Interfacial potential as the key to the formation and distribution of stratigraphic reservoirs. Hydrocarbon migration is controlled by the fluid potential field in sedimentary basins. Migration is always directed towards low potential zones from zones of higher potential. Fluid potential energy may be divided into four components: namely potential energy, interfacial potential energy, pressure energy and dynamic energy (Berg, 1975; Toth, 1978; Law and Dickison, 1985; England et al., 1987; Hunt, 1990; Bachu, 1995; Hao, 2005; Pang et al., 2012). The effect of interfacial potential on petroleum migration is actually attributed to the capillary force (England et al., 1987). When petroleum migrates through the reservoir pore space, which consists of many capillary tubes of different size, it bears capillary force differences. It has long been debated whether the capillary force is a driving force or resistance for the migration of fluids. Actually, the capillary force effect varies as the situation changes. The capillary force could act as both driving force and resistance for petroleum expulsion, which depends on whether the generated petroleum could saturate the source rock for adsorption. Before the source rock was saturated by the generated petroleum, the capillary force is resistance for petroleum expulsion; on the other hand, when the source rock was saturated, the capillary force could promote the petroleum to expel form the source rocks. Due to the radius difference of pore space between sandstone and shales, there is capillary force difference in the contact zone of these two rocks. Under the effect of this capillary force difference, petroleum generated from the shales will enter into the larger
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Fig. 5. Distribution of hydrocarbons and the hydrocarbon-expulsion intensity of source rocks (including Es3, Es2, Ed3) in the Nanpu Sag.
pores in sandstones and displace the existing water, which will be forced into the smaller pores in shales (Pang et al., 2003). Therefore, interfacial potential is the critical controlling factor in the formation and distribution of stratigraphic reservoirs (Pang et al., 2012). The interfacial potential control function refers to hydrocarbon accumulation in zones of high-porosity and permeability through capillary pressure due to the coexistence of multiphase fluids. For example, hydrocarbons generated in, and expelled from high potential energy mudstone is accumulated in sandstone with lower potential energy by migration along porous and permeable conduits, forming a stratigraphic reservoir. Fig. 6 shows the relationship between effective reservoir porosity and depth in the Nanpu Sag. The effective critical reservoir porosity decreases with depth. At any depth, hydrocarbon reservoirs can only form in relatively high-porosity zones for conventional reservoirs. This illustrates that the low-potential controls the reservoir formation: hydrocarbon reservoirs can form only when the mean porosity is greater than some critical values. 3.1.2.2. Quantitative characterization of the interfacial potential control function. Capillary pressure may be considered as a category of fluid pressure that drives the fluid through the spaces between the pores in the rock, displacing the liquid previously in the pores. For immiscible oil, gas and water, the two-phase interface is always curved. The degree of curvature is determined by the capillary pressure (Washburn, 1921; Yu et al., 2015), that is, the difference between the interfacial potentials, and is expressed by:
⎛1 1⎞ Pc = 2 cos θσ ⎜ − ⎟ ⎝ rn rs ⎠
(2)
where Pc is the capillary pressure, or interfacial potential difference (Pa); θ is the angle between the two-phase surface and the horizontal
plane (degrees); s is the interfacial tension (N/m); rn is the interstitial radius of the mudstone (μm); and rs is the interstitial radius of the sandstone (μm). From Eq. (2), we can see that the interfacial potential difference increases with increasing difference between the interstitial radii. Therefore, it is more favorable for hydrocarbon to migrate from small pores to larger pores, resulting in accumulation (Berg, 1975; Malcolm, 1990). The interfacial potential index, PSI, is recommended as a relative measure of potential-controlled hydrocarbon function. PSI takes a value between 0 and 1: the smaller the index, the more favorable the physical properties of the rock for the formation of a stratigraphic reservoir, and vice-versa. The relationship is given by:
PSI = (P − Pmin )/(Pmax − Pmin )
(3)
where P is the interfacial potential of the target (J); Pmax is the critical maximum interfacial potential at a depth (J); and Pmin is the critical minimum interfacial potential at a depth (J). We have calculated PSI for 43 Neogene-Paleogene stratigraphic reservoirs discovered in the Nanpu Sag. PSI of most reservoirs is less than 0.6 (Fig. 7). The relationship between the ratio of the stratigraphic reservoirs discovered and the distribution of the interfacial potential indices gives the reservoir control frequency of the interfacial potential as:
Yp = − 0.254 × ln (PSI ) + 0.4511
(4)
where Yp is the reservoir control frequency of the interfacial potential, and PSI is the interfacial potential index. 3.1.3. Sedimentary facies as a hydrocarbon accumulation constraint and its quantitative characterization 3.1.3.1. Relatively high-porosity and high-permeability sedimentary facies: favorable for hydrocarbon accumulation. Sedimentary facies
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hydrocarbon accumulation and for its formation and distribution, and for its control of the formation and distribution of hydrocarbon reservoirs. Generally speaking, carbonate and clastic rocks tend to form high-porosity and high-permeability formations in high-energy environments. For example, coarse-grained and wellsorted sandstone reservoirs are developed in high-energy shoreface environments, and form reef and bank sediments, or even carbonate reef sediments, in marine environments. The more favorable the original reservoir depositional conditions of these formations are, the more readily they will form high-porosity and high-permeability zones after their modification by subsequent geological activity. Therefore, favorable sedimentary facies always show a consistent distribution of appropriate properties, and reservoirs with such properties are the preferred locations for hydrocarbon migration and accumulation. There are several types of sedimentary facies developed in the Nanpu Sag, such aslake facies, subaqueous fan turbidite, delta, channel, fan delta, interchannel and alluvial fan facies (Xu et al., 2006; Liang et al., 2008; Wang et al., 2012). Stratigraphic reservoirs are mainly found in the fan delta facies, braided delta facies, alluvial fan facies, lake facies, and turbidite. Of the stratigraphic reservoirs in the Nanpu Sag, 41.9% occur in fan delta front, 30.2% in braided delta front and 11.6% in turbidite. Fewer than 20% of all stratigraphic reservoirs are found in the other facies (Fig. 8a). Reservoir lithofacies are mainly medium sandstone, fine sandstone and gritstone (Fig. 8b). Their physical properties are quite good with porosity ranging from 15% to 35% and permeability over 10 mD (Fig. 8c and d).
Fig. 6. Porosity distribution characteristics of stratigraphic reservoirs in the Nanpu Sag.
3.1.3.2. Quantitative characterization of facies-controlled hydrocarbon reservoir distribution. The facies’ control on hydrocarbon reservoir distribution is quantitatively characterized by the reservoir formation controlling frequency of different facies. By statistical analysis of discovered reservoirs in various facies, we established the quantification standard between facies and hydrocarbon accumulation frequency (Table 1). The number of discovered reservoirs in different facies is different from, which is same of their percentage in the total reservoirs. The higher the percentage of discovered reservoir in a certain facies is, the larger its control on hydrocarbon accumulation is, and vice versa. With standardization of this percentage, we obtained the relative frequency for hydrocarbon accumulation of different facies (Eq. (5), Table 1). Specifically, we give the maximum value of 1 to the facies where we found the most reservoir or the highest percentage, while the minimum value of 0 was given to the facies where no reservoirs were identified; frequency of other facies are between 0 and 1 (Table 1). But we should caution that the 0 frequency of a certain facies does not mean that no hydrocarbons will be found or exist in this facies, and the relative frequency just gives us a comparative relationship between different facies. Therefore, the controlling ratio of certain sedimentary facies ranges from 0 to 1.
Ydi = (dni /dnt )/(dnmax /dnt ) Fig. 7. Relationship between stratigraphic reservoirs and indices of interfacial potential in the Nanpu Sag.
represent specific environments and processes, formed under specific conditions (Feng, 1993). The hydrocarbon control function of sedimentary facies is distinguished by various lithofacies, combinations of lithofacies and diagenesis for different sedimentary facies or microfacies. The “sedimentary facies control function for hydrocarbon accumulation” means that relatively high-porosity and high-permeability sedimentary facies are favorable for
(5)
where Ydi is the reservoir control frequency of a certain sedimentary facies i, dni is the number of discovered reservoirs in a certain sedimentary facies i; dnmax is the number of the discovered reservoirs within a certain facies that has the most discovered reservoirs; dnt is the number of total discovered reservoir within all the facies. 3.1.4. Hydrocarbon control function of regional cap rock and its quantitative characterization 3.1.4.1. Geological characteristics of regional cap rock-controlled hydrocarbon reservoir distribution. Regional cap rock is an essential condition for the formation and conservation of hydrocarbon
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Fig. 8. Hydrocarbon control characteristics by the Neogene–Paleogene sedimentary facies in the Nanpu Sag.
Table 1 Reservoir control frequency of different sedimentary facies. Sedimentary facies
The number of reservoirs discovered
Percentage (%) Reservoir control frequency
Fan delta front Braided delta front Turbidite Lake Fan delta plain Alluvial fan Braided delta plain
18 13
41.86 30.23
1.00 0.72
5 4 2 1 0
11.63 9.30 4.65 2.33 0.00
0.28 0.22 0.11 0.06 0.00
reservoirs. Depending on their lateral distribution and other features controlling the hydrocarbon reservoir distribution, cap rocks are described as directly-overlying local cap rocks and regional cap rocks. For most petroliferous basins, widely distributed, thick and stable regional cap rocks play an important role in hydrocarbon migration and accumulation in basins (Chen et al., 2003b; Dou and Xu, 1992; Tong and Niu, 1989; Zhou, 1997; Zhou and Wang, 2002), and determine the hydrocarbon reservoirs’ planar distributions. According to the present exploration results of the Nanpu Sag, four sets of regional cap rocks have great effects on hydrocarbon accumulations (Xu et al., 2008; Zhu et al., 2011). One is the dark Es3mudstone. As an important set of cap rock and high-quality source rock, it is widely distributed over most of the Nanpu Sag, and plays an important role in conserving pre-Paleogene buried hill reservoirs. The second set is the Ed2 lake flooding mudstone. It is widely distributed in the south of Nanpu Sag, and is regional cap rocks for the reservoirs in Shahejie Formation and 3rd member of Dongying Formation, with the greatest thickness over 300 m. The third set is the tight basalt cap rock of Guantao Formation, and it is mainly distributed in the west of Nanpu Sag, with the greatest thickness over 500 m. This set of cap rock is better than any other one in sags of Bohaiwan basin, below which it has a great
enrichment of hydrocarbons, with the maximum height of hydrocarbon column of 1000 m. On the other hand, hydrocarbons discovered above this set of cap rocks are mostly related to the later faulting activities. The fourth set is mudstone cap rocks in Lower Minghuazhen Formation, which is distributed in the whole sag, with the maximum thickness over 600 m. Above this set of caprocks, there are no industrial hydrocarbon reservoirs. 3.1.4.2. Quantitative characterization of cap rock-controlled hydrocarbon reservoir distribution. Hydrocarbon sealing capacity by a regional cap rock is here quantified by geostatistical analysis. A quantitative relationship was established between the thickness of regional cap rocks in the Nanpu Sag and the cumulative frequency commercial oil wells under these cap rocks, by studying their relationship (Fig. 9). The cumulative frequency commercial oil wells increases with increasing thickness of the regional cap rock; for areas with thickness over 400 m, the cumulative frequency commercial oil wells gradually increases, or is constant. According to the relationship between the cumulative frequency commercial oil wells and cap rock thickness, the frequency of reservoir control by the single factor of regional cap rock thickness has been determined. The frequency takes the value “1” if the thickness of the regional cap rock exceeds 400 m. If the thickness of the regional
Fig. 9. Relationship between cumulative daily outputs of hydrocarbons and regional cap rock thickness.
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cap rock is less than 400 m, the frequency can be obtained from Eq. (6):
Yc = 0.5627 × ln (X c ) − 2.3726
(6)
where Yc is the reservoir control frequency under the control of the single factor of the regional cap rock, and Xc is the thickness of the regional cap rock. 3.2. Functional-element constraint hydrocarbon distribution model and its procedure 3.2.1. Basic concept and characteristics of the functional-element constraint hydrocarbon distribution model Functional elements refer to indispensable geological factors that control hydrocarbon reservoir formation and distribution and can be described objectively and characterized quantitatively. The formation and distribution of stratigraphic reservoirs are jointly controlled by the four geological functional elements: regional cap rock (C), favorable sedimentary facies (D), interfacial potential (P) and source rock (S). Among the four factors low interfacial potential is the key factor. The vertical sequential superposition of CDPS functional elements determine the horizons of stratigraphic reservoir formation; their planar overlaps determine the planar range of formation; and their concomitant co-presence determine the time (T) of stratigraphic reservoir formation. The integrated reservoir effect of CDPS is termed the “functional-element constraint hydrocarbon distribution model”, and is expressed as T-CDPS (Fig. 10). To characterize the comprehensive T-CDPS model, we propose a quantitative Tcdps index to represent its possibility for hydrocarbon accumulation. Tcdps is from 0 to 1 and can be obtained from the geometric mean of the CDPS individual-factor
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reservoir formation frequencies during a main reservoir formation period as expressed by Eq. (7). On the one hand, the proposed Tcdps indicates that the four elements are inevitable during the formation of a petroleum reservoir. On the other hand, it also gives a relatively comparison of chances whether a petroleum reservoir will form or not on the basis of effects of four elements together. The greater the value of Tcdps, the more favorable, the more possible the zone is for reservoir formation, and vice-versa. Based on the Tcdps index value, we propose that stratigraphic reservoir formation areas can be divided into four types: the “favorable area”, where Tcdps lies in the range 1–0.75; the “moderately favorable area”, where Tcdps lies in the range 0.75–0.5; the “less favorable area”, where Tcdps lies in the range 0.5–0; and the “unfavorable area”, where Tcdps is 0. These values are obtained from:
Tcdps =
4
Yc × Yd × Yp × Ys
(7)
where Tcdps is the comprehensive assessment index of the T-CDPS functional-element constraint hydrocarbon distribution model; Yc is the reservoir control frequency of the regional cap rock; Yd is the reservoir control frequency of sedimentary facies; Yp is the reservoir control frequency of the interfacial potential; and Ys is the reservoir control frequency of the hydrocarbon kitchen. Vertically, sequential combinations of CDPS functional elements determine the horizons of stratigraphic reservoir formation. The state of the downward sequence of C, D, P and S is the favorable condition for stratigraphic reservoir formation (Fig. 10a). After hydrocarbons are generated and expelled from the lowest source rock (S), they initially migrate into stratigraphic sand traps by the action of interfacial potential. Various relatively high-porosity and high-permeability sedimentary facies provide favorable
Fig. 10. T-CDPS functional-elements constraint reservoir formation model for stratigraphic reservoirs.
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Fig. 11. Relationship between stratigraphic reservoir distribution and planar superimpositions of functional elements in the Nanpu Sag.
reservoir conditions for hydrocarbon migration to their perimeter, and accumulated hydrocarbons are preserved and sealed by the overlying regional cap rock. In practice, the four main geologic functional elements may occur in other vertical combinations, but CDPS is the combination that is most likely to facilitate stratigraphic reservoir formation (for example, the sequence DSCP would be unfavorable for stratigraphic reservoir formation because the regional cap rock, C, occurs under the source rocks, S, and could not effectively preserve the hydrocarbon resources generated in the source rocks). Planar/lateral superimpositions and combinations of the CDPS functional elements determine the range of stratigraphic reservoir formation (Fig. 10b). Of the 43 stratigraphic reservoirs discovered in the Nanpu Sag, statistical data shows that areas superimposed by all four functional elements C, D, P and S occupy 98%. Stratigraphic reservoirs discovered in areas where only three functional elements are superimposed account for the other 2%. No stratigraphic reservoirs have been discovered in areas where two functional elements, or less, are superimposed (Fig. 11). In summary, areas with superposition of more functional elements have a
higher possibility of stratigraphic reservoir formation, and areas with fewer functional elements have a lower possibility of stratigraphic reservoir formation. In theory, all four elements C, D, P and S must be satisfied for the formation of stratigraphic reservoirs. Thus the question arises as to why reservoir formation also sometimes occurs in areas where only three, two or even one reservoir formation factors exist. This is determined by the complexity of geologic conditions. Firstly, when we determine the extent of a hydrocarbon reservoir formation based on individual factors, the conclusions are not absolute “yes” or “no”, but are attached with certain frequencies. Therefore, when considering reservoir formation by superimposing the four functional elements, we can only get a possibility. Secondly, the T-CDPS model is only suitable for predictions of formation and distribution of stratigraphic reservoirs, and is not suitable for predictions of other types of reservoirs. Concomitant presence of the CDPS functional elements in geohistory determine the time of stratigraphic reservoir formation (Fig. 10c), both in the vertical sequential combinations and the planar/lateral superimpositions. The co-presence of the reservoir formation factors through time are preconditions for, and the key to, hydrocarbon reservoir formation. 3.2.2. Basic procedures of the functional-element constraint hydrocarbon distribution model to predict favorable formation areas of stratigraphic reservoirs The method and procedures for applying the functional-element constraint hydrocarbon distribution model to predict favorable reservoir formation areas are shown in Fig. 12. There are five steps: (1) analysis of petroliferous basins or sub-basins to determine the basic geological conditions (e.g. C, D, P and S) for hydrocarbon reservoir formation and their development histories and distribution characteristics. (2) Analysis of the mass of hydrocarbon generation and expulsion from the source rocks to determine the main geohistorical reservoir formation periods in petroliferous basins or sub-
Fig. 12. Method and procedures for applying the T-CDPS functional-element constraint hydrocarbon distribution model to predict favorable areas for stratigraphic reservoir formation.
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Fig. 13. Distribution of reservoir-forming frequency controlled by each functional element for the Paleogene Ed3 in the Nanpu Sag (A-regional cap rock (C), B-favorable sedimentary facies (D), modified from Wang et al. (2012), C-interfacial potential (P) and D-source kitchen (S)).
basins (T1, T2, …, Tn). (3) Analysis of the distribution characteristics of discovered hydrocarbon reservoirs to establish the geological model of hydrocarbon control function of the four functional elements, and to determine the reservoir control extent and frequency of every functional element for each reservoir formation period. (4) For each target formation, predict the favorable reservoir areas in different reservoir formation periods. Determine the favorable, moderately favorable, less favorable and unfavorable reservoir formation areas by superimposing the individual favorable functional elements with the same formation in different reservoir formation periods. (5) For an individual basin or sub-basin, predict the favorable exploration areas in different zones of interest. Finally, determine the favorable tectonic unit by superimposing favorable reservoir formation areas of various zones of interest.
4. Results 4.1. Reservoir formation period in the Paleogene Ed3, Nanpu Sag The first step in applying the T-CDPS functional-element constraint hydrocarbon distribution model is to determine the reservoir formation period. Late-stage accumulation is the most
important characteristic of reservoir formation in the Nanpu Sag, and the time of oil and gas charging into Ed3 was at the end of Paleogene Ed, about 25–23 Ma (Liu et al., 2000). 4.2. Quantitative prediction of the favorable Paleogene stratigraphic reservoir formation areas in the Paleogene Ed3, Nanpu Sag After determining the reservoir formation period, the planar characteristics and the constraints on hydrocarbons by the four functional elements need to be studied. Using the method described above, in the present work we investigated the geological characteristics of the CDPS functional elements of the Paleogene Ed3 strata in the Nanpu Sag over the main reservoir formation period, and calculated their reservoir-forming frequencies under the influence of each factor in turn. Fig. 13 shows the planar distribution of reservoir-forming frequencies in Ed3 strata for each of the functional elements, the sedimentary facies of which is adapted from Wang et al. (2012). The Tcdps indices were obtained from Eq. (7) and the planar distributions are shown in Fig. 14. Finally, areas favorable to the presence of stratigraphic reservoirs were predicted for the target. Prediction results show that there are 5 favorable reservoir formation areas in the target in the Nanpu Sag, with Tcdps values between 1 and 0.75.
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Fig. 14. T-CDPS model prediction of the possibility for stratigraphic reservoir formation as compared with oil-bearing locations (Paleogene Ed3 in the Nanpu Sag).
Table 2 Statistics of the possibility of forming Paleogene Ed3 stratigraphic reservoirs in the Nanpu Sag. Reservoirs Frequency of Frequency of facies concap rock trol function control function
Frequency of Frequency of Tcdps source con- index potential trol function control function
R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 R18
0.52 0.65 0.60 0.40 0.30 0.10 0.64 0.70 0.60 0.57 0.64 0.70 0.90 0.81 0.69 0.83 0.65 0.40
0.52 0.53 0.50 0.73 0.82 0.80 0.76 0.72 0.87 0.85 0.83 0.68 0.60 0.74 0.60 0.69 0.43 0.52
0.11 0.11 1.00 0.61 0.56 0.11 1.00 1.00 1.00 1.00 1.00 0.28 0.72 0.72 0.72 0.28 1.00 1.00
0.65 0.70 0.82 0.70 0.61 0.67 0.79 0.85 0.78 0.80 0.83 0.82 0.83 0.81 0.65 0.47 0.55 0.71
0.37 0.40 0.70 0.59 0.54 0.28 0.79 0.81 0.80 0.79 0.81 0.57 0.75 0.77 0.66 0.52 0.63 0.62
4.3. Reliability analysis of quantitative prediction by the T-CDPS model We calculated the single-factor frequency of every functional element for 18 discovered stratigraphic reservoirs from the Paleogene Ed3 in the Nanpu Sag (if a reservoirs is located between two sedimentary facies, we give it the value of the mean of the frequencies of these two facies) and obtained the Tcdps indices representing the overall reservoir-forming possibility, taken as the geometric mean of all the CDPS single-factor frequencies (Table 2). Results show that 7 of the 18 discovered stratigraphic reservoirs occur in areas designated as “favorable”, that is, where the estimated possibility is 1–0.75 (Fig. 14). 8 are found in the “moderately favorable” areas for which the estimated possibility is 0.75–0.5 (Fig. 14). Only 3 are found in the “less favorable” areas for which the estimated possibility is 0.5–0 (Fig. 14). No stratigraphic reservoirs have been found in the “unfavorable” areas for which the estimated possibility is 0 (Fig. 14). The results demonstrate the feasibility and effectiveness of the T-CDPS functional-element constraint hydrocarbon distribution model for the quantitative prediction of stratigraphic reservoir distribution.
5. Discussion The five favorable areas are Gaoshangpu structural belt, southern Laoyemiao structural belt and Nanpu I, II, V structural belt, respectively (Fig. 14). Meanwhile, there are two moderately favorable areas, with Tcdps values between 0.75 and 0.5, which are Nanpu III structural belt and Nanpu IV structural belt (Fig. 14).
The proposed “T-CDPS” model effectively predicts the favorable distribution of stratigraphic reservoirs in Es3, Nanpu Sag. Compared with the basin modeling method, this simple approach is easy to use and does not need too many parameters. On the
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contrary, lots of more accurate data on various parameters, e.g. source rock, reservoir, and structure, are needed to conduct basin modelings, or it may cause great errors in accuracy. Meanwhile, on the basis of traditional petroleum geology analysis method (e.g. petroleum system analysis), this approach attempts to quantify various control factors, which makes the final result more apparent and comparative. However, we have to admit that some problems still exist, such as how to make the standardization and value assignment more reasonable, which will be the further focus we will try to resolve.
6. Conclusions Functional elements refer to indispensable geological factors controlling hydrocarbon reservoir formation and distribution, which can be described objectively and characterized quantitatively. Regional cap rock (C), favorable sedimentary facies (D), interfacial potential (P) and source rock (S) are the most important functional elements controlling the formation and distribution of stratigraphic reservoirs in the Nanpu Sag. Regions of overlapped CDPS functional elements indicate the favorable zones for stratigraphic reservoir formation and distribution. The geometric mean of the four functional element control frequencies is the possibility of stratigraphic reservoir distribution in a target zone. The T-CDPS functional-element model is a new method and model for quantitative prediction of favorable areas for stratigraphic reservoir formation and distribution. There are 5 favorable exploratory areas for stratigraphic reservoirs distributed in Paleogene Ed3 in the Nanpu Sag. The five favorable areas are Gaoshangpu structural belt, southern Laoyemiao structural belt and Nanpu I, II, V structural belt, respectively. Meanwhile, there are two moderately favorable areas, with Tcdps values between 0.75 and 0.5, which are Nanpu III structural belt and Nanpu IV structural belt. This T-CDPS functional-element constraint model is proved to be feasible and effective in quantitatively predicting the stratigraphic reservoir distributions. Specifically, 15 out of 18 discovered stratigraphic reservoir are in the favorable and moderately favorable area, which have an estimated possibility of 0.5–1, while only 3 reservoirs are found in the less favorable area, whose relative possibility for hydrocarbon accumulation is 0–0.5.
Acknowledgments This work was supported by the National Natural Science Foundation of China Project (Nos. 41102085 and U1262205), China National Key Basic Research and Development 973 Program Project (No. 2011CB201102), and China National Science and Technology Major Project (No. 2011ZX05006-006). We appreciate the CNPC Jidong Oilfield Exploration and Development Research Institute for providing background geologic data and the permission to publish the results.
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Journal of Petroleum Science and Engineering journal homepage: www.elsevier.com/locate/petrol
Functional-element constraint hydrocarbon distribution model and its application in the 3rd member of Dongying Formation, Nanpu Sag, Bohai Bay Basin, eastern China Jigang Guo a,n, Jing Xu b,c, Fengtao Guo d, Jianhua Li e, Xiongqi Pang b,c, Yuexia Dong f, Tao Hu b,c a
Strategic Research Center of Oil and Gas Resources, Ministry of Land and Resources, Beijing 100034, China Research Center of Basin and Reservoir, China University of Petroleum, Beijing 102249, China State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China d Australian School of Petroleum, The University of Adelaide, SA 5005, Australia e Sinochem Petroleum Exploration & Production Co., Ltd., Beijing 100031, China f PetroChina Jidong Oilfield Company, Tangshan 063004, China b c
art ic l e i nf o
a b s t r a c t
Article history: Received 5 December 2015 Accepted 14 December 2015 Available online 18 December 2015
The proposed functional-element constraint hydrocarbon distribution model consists of four basic functional elements including regional cap rock (C), favorable sedimentary facies (D), interfacial potential (P) and source kitchen (S). The combination of the four functional elements controls the formation and distribution of stratigraphic reservoirs in a basin. Regions with spatial and temporal overlaps of the four functional elements are the favorable zones for stratigraphic reservoirs. The geometric mean of the frequency of the four functional elements could indicate the possible distribution of stratigraphic reservoirs in a target zone. This paper describes constraint functions of the four functional elements on the hydrocarbon accumulations and their quantitative characterization. The hydrocarbon distribution model based on functional elements can predict development of stratigraphic reservoirs using T-CDPS, and the possibility for reservoir formation is determined by the index, Tcdps, in this paper. Based on the model, we have predicted seven areas of the Paleogene Ed3 in Nanpu Sag, which are favorable or moderately favorable for stratigraphic reservoir distribution. Among all the seven areas, five areas located in the Gaoshangpu structural belt, south of Laoyemiao structural belt and Nanpu I, II, V structural belt were favorable areas. Two moderately favorable areas were located in Nanpu III structural belt and Nanpu IV structural belt. & 2015 Elsevier B.V. All rights reserved.
Keywords: Functional-elements constraint model Stratigraphic reservoir Prediction of favorable hydrocarbon accumulation area The 3rd member of Dongying Formation Nanpu Sag
1. Introduction Stratigraphic reservoirs are an important type of subtle reservoir plays which not only represent an important research field in modern petroleum geology, but have also become the primary target of contemporary hydrocarbon exploration worldwide. Stratigraphic reservoirs are accumulations of hydrocarbons in traps formed by the change of reservoir lithology, lithic facies and property, which consist of updip pinch-out and lenticular sand reservoirs (Tissot and Welte, 1978). We mainly talk about the conventional stratigraphic reservoirs. Unconventional stratigraphic reservoirs such as tight gas reservoir is not discussed in this paper. With increasing exploration degree and decreasing n
Corresponding author. E-mail address: [email protected] (J. Guo).
http://dx.doi.org/10.1016/j.petrol.2015.12.017 0920-4105/& 2015 Elsevier B.V. All rights reserved.
possbility of discovering large-scale structural reservoirs, stratigraphic reservoirs have become increasingly important in oil-gas exploration. The recent Oil and Gas Resource Assessment showed that the proportion of litho-stratigraphic reservoir plays has reached 42% of the remaining onshore oil and gas resources in China (Zhao et al., 2004). Litho-stratigraphic reservoirs are becoming the most realistic potential and universal oil and gas plays in China (Jia et al., 2004). Petroleum geologists in China have recently achieved fruitful results in research on stratigraphic reservoir formation and distribution. Fu et al. (2002) put forward three mechanisms for the formation of stratigraphic reservoirs: (1) oil or gas migrating from the source rock, or source kitchen into stratigraphic traps in the source rock and forming oil or gas reservoirs via capillary pressure; (2) oil or gas generated from the source rock migrating into stratigraphic traps above the source rock and forming oil and gas reservoirs under the dual influence of abnormal pore fluid
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pressure and buoyancy; and (3) oil or gas generated from the source migrating into stratigraphic traps below the source rock and forming oil or gas reservoirs via abnormal pore fluid pressure. Chen et al. (2003a) proposed a ternary genetic mechanism for the formation of stratigraphic reservoirs, which are mainly controlled by the hydrocarbon source, the reservoir's petrophysical properties, and the sandbody genetic type. Liu et al. (2006) put forward
the notion of a quaternary control mechanism for stratigraphic reservoirs, believing that their formation is determined by four key factors: hydrocarbon migration pathway conditions, fluid dynamics conditions, critical physical properties of reservoirs, and the sealing conditions of the traps. Pang et al. (2007) proposed a geological model in which reservoir formation and distribution are controlled by favorable facies–low potential coupling, and applied
Fig. 1. (A) Location map of the study area showing the sub-tectonic units of the Bohai Bay Basin (modified from Dong et al. (2010)); (B) distribution of main structural elements, normal faults and discovered oilfields within the Nanpu Sag (modified from Dong et al. (2010) and Xu et al. (2008)). The sections’ and wells’ locations are also shown.
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it to predict the distribution of stratigraphic reservoirs in continental faulted basins. The Napu Sag is a well-known small but petroliferous sag located in the northwestern Bohai Bay Basin. The Neogene, Paleogene sandstones and pre-Paleogene buried hills are the most important exploration targets. After nearly 40-year oil and gas exploration and development, the proved rate of Nanpu Sag is higher and higher. While previous hydrocarbon reservoirs were mainly discovered in structural traps, major breakthroughs have been made in the exploration for the Paleogene stratigraphic reservoirs in recent years (Xu et al., 2008; Liu, 2008). To date, reserve in place in the Nanpu Sag has been proved more than 10 108t, and that of stratigraphic reservoirs is about 3 108t (Xu et al., 2008). However, the complex formation and distribution mechanisms of stratigraphic reservoirs have become a bottleneck in stratigraphic oil and gas reservoir exploration, which makes the prediction of favorable areas extremely challenging. Therefore, new effective technologies and methods are needed. The proposed functional-element constraint hydrocarbon distribution model in this paper defines four basic functional elements including regional cap rock (C), favorable sedimentary facies (D), interfacial potential (P, The interfacial potential control function refers to hydrocarbon accumulation in zones of relatively high-porosity and permeability through capillary pressure due to the coexistence of multiphase fluids (England et al., 1987). Hubbert (1953) has shown that hydrocarbon migration is bounded by the capillary properties of the reservoir rock and the boundary rock, which bears displacement pressure differences. England et al. (1987) later integrated interfacial tension as a driving force when using the fluid potentials to describe the migration of petroleum fluids. We call this contribution of fluid potential caused by interfacial tension the interfacial potential, which is quite significant), and source kitchen (S) to be the key elements affecting the hydrocarbon accumulation in stratigraphic reservoirs in a basin. We have established a new conceptual geologic model, “T-CDPS”, a functional-element constraint hydrocarbon distribution model for quantitatively predicting favorable areas of stratigraphic reservoir distribution in the Nanpu Sag.
2. Geological setting The Bohai Bay Basin, an important hydrocarbon-producing province in China, is located on the eastern coast of China and
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covers an area of approximately 200,000 km2 appearing as a north-east-trending “lazy-Z” pattern on the regional geologic map (Dong et al., 2010). It consists of six major sub-basins or depressions, including Liaohe–Liaodong, Bozhong, Jiyang, Jizhong, Huanghua, and Linqing-Dongpu sub-basins or depressions, and five major uplifted blocks including Cheng-ning, Shaleitian, Cangxian, Xing-heng, and Neihuang, from the northeast to the southwest (Gong, 1997) (Fig. 1A). The Nanpu Sag, one of the many small sags within the giant Bohai Bay Basin, is located in the northeast part of Huanghua Depression and covers an area of only 1930 km2. It is bounded by the Shaleitian fault to the south and the Xinanzhuang–Baigezhuang fault to the north and east. Structurally, the sag is a half-graben, and the latter two faults serve as border faults that have a steep dip toward the south and southwest (Wang et al., 2002). Eight northeast-trending major structures have been identified in the sag, including the Gaoshangpu, Liuzan, Laoyemiao onshore, and Nanpu 1, Nanpu 2, Nanpu 3, Nanpu 4, and Nanpu 5 structures offshore (Wang et al., 2002) (Figs. 1B and 2). The sedimentary stratigraphy of Nanpu Sag has been extensively studied mostly through drilling for hydrocarbon exploration. It is filled with a thick sequence of Cenozoic strata (5000–9000 m) which comprises the Eocene Shahejie Formation (Es), the Oligocene Dongying Formation (Ed), and the Miocene Guantao (Ng) and Minghuazhen Formations (Nm), and the Quaternary Pingyuan Formation (Qp) (Wang et al., 2002; Jiang et al., 2009) (Fig. 3). The Shahejie Formation contains the main source rocks and sandstone reservoir rocks and is divided into three intervals, Es1, Es2, and Es3 (from top to base). The lower member, Es3, is further divided into five submembers, Es31, Es32, Es33, Es34, and Es35, from top to bottom, and the lithologic description of each submember is provided in Fig. 3 (Wang et al., 2002; Jiang et al., 2009). The middle member, Es2, is a suite of alluvial sediments composed of dominantly reddish mudstone interbedded with thin layers of sandstone. The upper member, Es1, is characterized by shallow lacustrine lithofacies (Dong et al., 2010). The Dongying Formation (Ed) consists of three members, Ed1, Ed2, and Ed3, from top to bottom. This formation is a set of lacustrine deposits up to 500–600 m onshore and 1500–2000 m offshore (Wang et al., 2002). The Neogene Guantao and Minghuazhen formations throughout the whole Bohai Bay Basin are deposited in a braided fluvial system and a low-sinuosity fluvial system, respectively (Wang et al., 2002).
Fig. 2. Cross-section (AA′ in Fig. 1) of the Nanpu Sag showing the various tectonic–structural zones and source–reservoir–seal combination.
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Fig. 3. Generalized Cainozoic stratigraphy of the Nanpu Sag, showing depositional environment, tectonic evolution stages and the major petroleum system elements including the Es3, Es1, and Ed3 source rocks, multiple reservoir intervals and sealing units (modified from Dong et al. (2010) and Wang et al. (2002)).
The gray to black mudstones, calcareous mudstones and oil shales in the lower Es34 and upper Es1 intervals of the Eocene Shahejie Formation and Ed3 interval of the Oligocene Dongying Formation are considered as the main source rocks (Zheng et al., 2007; Zhu et al., 2011). Eocene–Oligocene syn-rifting lacustrine fan-delta sands and subaqueous fans and Miocene–Pliocene postrifting fluvial facies serve as major reservoir rocks (Dong, 2002).
The thick and widely distributed basalts and mudstones in Guantao Formation and mudstones developed stably in the upper member of Minghuazhen Formation serve generally as two sets of regional seal (Zhu et al., 2011; Wan et al., 2013). Above-source play (Ed1–Nm), in-source play (Es4–Ed2), and below-source play (O–Mz) had been distinguished according to the source–reservoir configuration (Xu et al., 2008; Tan and Tian, 2000). There are anticlinal,
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faulted anticlinal, fault, stratigraphic, stratigraphic and buried hill reservoirs in the Nanpu Sag (Dong, 2002; Xu et al., 2008) (Fig. 2), and the 3rd member in Dongying Formation was one of the most petroliferous layers abundant of stratigraphic reservoirs (Xu et al., 2008; Liu, 2008).
3. Methods 3.1. Main controlling factors on stratigraphic reservoir formation and distribution and their quantitative characterization in the Nanpu Sag Hydrocarbon reservoir formation and distribution is the result of the combined action of six major geological factors: namely source condition, reservoir condition, caprock condition, migration condition, trap condition and conservation condition. Each of these may involve multiple minor discrete geological elements. For a given petroliferous basin or Sag, the factors controlling hydrocarbon reservoir formation and distribution may be more complex. Based on a study of the geological characteristics of the stratigraphic reservoirs in the Nanpu Sag, we conclude that regional caprock (C), favorable sedimentary facies (D), interfacial potential (P) and source kitchen (S) are the four key geological functional elements controlling stratigraphic reservoir formation and distribution. The term “functional elements” refers to fundamental geological factors controlling hydrocarbon reservoir formation and distribution that can be described objectively and characterized quantitatively. For the sake of discussion, we represent them here by the abbreviations C, D, P and S, respectively. 3.1.1. Hydrocarbon kitchen constraint and its quantitative characterization 3.1.1.1. Hydrocarbon kitchen control on the planar range of hydrocarbon reservoir distribution. Hydrocarbon kitchens refer to the range of conditions where the source rock generates and expels hydrocarbon at a particular geological time or during the period of reservoir formation. Some geologists define it as the effective range of source rock distribution at a particular geological period. Hydrocarbon kitchens provide source for reservoir formation, and their distribution ranges determine the planar ranges of hydrocarbon accumulation distribution. Previous researchers have carried out many studies of hydrocarbon kitchen controlling functions (e.g. Dai et al., 1996; Hu, 1982, 2005; Jin et al., 2003; Pang, 2003). Their results show that the size of a hydrocarbon kitchen and the quantity of hydrocarbons it generates and expels determine the scale, range and resource capabilities of the hydrocarbon reservoir formation. Three sets of source rocks appear in the Nanpu Sag: Paleogene Es34, Es1 and Ed3. Exploration results have shown that these source rocks supply abundant hydrocarbon resources to the reservoirs, and control how far the hydrocarbons migrate and the planar distribution of hydrocarbon reservoirs. The hydrocarbon expulsion intensity and volume from these three sets of source rocks are obtained by the petroleum generation potential method proposed by Guo et al. (2014). The generated and expelled hydrocarbons migrate over a relatively short range. These hydrocarbon reservoirs are distributed within 30 km of the source rock boundary with most of the distance less than 15 km (Fig. 4). They are basically located around, or within the hydrocarbon-generation sags in the Napu Sag. The Neogene-Paleogene reservoirs and the pre-Paleogene buried hill reservoirs, whose hydrocarbons come from Es3, Es1, and Ed3 source rocks, are found around the center of hydrocarbon expulsion of source rocks (Fig. 5). 3.1.1.2. Quantitative characterization of hydrocarbon kitchen control function. We propose the frequency of reservoir formation to be used to quantitatively characterize the hydrocarbon kitchen constraining
Fig. 4. Relationship between hydrocarbon reservoirs and hydrocarbon kitchens in the Nanpu Sag.
function. Research has shown that the reservoir formation frequency within the hydrocarbon distribution threshold is determined by three geological conditions (Jiang, 2008): the hydrocarbon-expulsion intensity center; the distance between the hydrocarbon-expulsion center and the reservoir; and the distance between the hydrocarbon-expulsion boundary and the reservoir. Combining these allows the reservoir formation frequency of hydrocarbon kitchen control to be calculated (Eq. (1), Jiang et al., 2013): 2
Ys = 0.046e 0.12qe − 0.16 ln (L ) + 0.65e−8.2357 (l + 0.1) + 0.1345
(1)
where Ys is the reservoir formation frequency at a point influenced by the hydrocarbon kitchen; L is the standardized distance between the hydrocarbon reservoir and the hydrocarbon-expulsion center, 0–2.5 (Jiang et al., 2013); l is the standardized distance between the hydrocarbon reservoir and the hydrocarbon-expulsion boundary (positive when the hydrocarbon reservoir is outside the hydrocarbon-expulsion boundary, and negative when the hydrocarbon reservoir is within the hydrocarbon-expulsion boundary), 1 to 1 (Jiang et al., 2013); and qe is the maximum hydrocarbon-expulsion intensity of the hydrocarbon kitchen (106 t/km2). 3.1.2. The interfacial potential constraint and its quantitative characterization 3.1.2.1. Interfacial potential as the key to the formation and distribution of stratigraphic reservoirs. Hydrocarbon migration is controlled by the fluid potential field in sedimentary basins. Migration is always directed towards low potential zones from zones of higher potential. Fluid potential energy may be divided into four components: namely potential energy, interfacial potential energy, pressure energy and dynamic energy (Berg, 1975; Toth, 1978; Law and Dickison, 1985; England et al., 1987; Hunt, 1990; Bachu, 1995; Hao, 2005; Pang et al., 2012). The effect of interfacial potential on petroleum migration is actually attributed to the capillary force (England et al., 1987). When petroleum migrates through the reservoir pore space, which consists of many capillary tubes of different size, it bears capillary force differences. It has long been debated whether the capillary force is a driving force or resistance for the migration of fluids. Actually, the capillary force effect varies as the situation changes. The capillary force could act as both driving force and resistance for petroleum expulsion, which depends on whether the generated petroleum could saturate the source rock for adsorption. Before the source rock was saturated by the generated petroleum, the capillary force is resistance for petroleum expulsion; on the other hand, when the source rock was saturated, the capillary force could promote the petroleum to expel form the source rocks. Due to the radius difference of pore space between sandstone and shales, there is capillary force difference in the contact zone of these two rocks. Under the effect of this capillary force difference, petroleum generated from the shales will enter into the larger
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Fig. 5. Distribution of hydrocarbons and the hydrocarbon-expulsion intensity of source rocks (including Es3, Es2, Ed3) in the Nanpu Sag.
pores in sandstones and displace the existing water, which will be forced into the smaller pores in shales (Pang et al., 2003). Therefore, interfacial potential is the critical controlling factor in the formation and distribution of stratigraphic reservoirs (Pang et al., 2012). The interfacial potential control function refers to hydrocarbon accumulation in zones of high-porosity and permeability through capillary pressure due to the coexistence of multiphase fluids. For example, hydrocarbons generated in, and expelled from high potential energy mudstone is accumulated in sandstone with lower potential energy by migration along porous and permeable conduits, forming a stratigraphic reservoir. Fig. 6 shows the relationship between effective reservoir porosity and depth in the Nanpu Sag. The effective critical reservoir porosity decreases with depth. At any depth, hydrocarbon reservoirs can only form in relatively high-porosity zones for conventional reservoirs. This illustrates that the low-potential controls the reservoir formation: hydrocarbon reservoirs can form only when the mean porosity is greater than some critical values. 3.1.2.2. Quantitative characterization of the interfacial potential control function. Capillary pressure may be considered as a category of fluid pressure that drives the fluid through the spaces between the pores in the rock, displacing the liquid previously in the pores. For immiscible oil, gas and water, the two-phase interface is always curved. The degree of curvature is determined by the capillary pressure (Washburn, 1921; Yu et al., 2015), that is, the difference between the interfacial potentials, and is expressed by:
⎛1 1⎞ Pc = 2 cos θσ ⎜ − ⎟ ⎝ rn rs ⎠
(2)
where Pc is the capillary pressure, or interfacial potential difference (Pa); θ is the angle between the two-phase surface and the horizontal
plane (degrees); s is the interfacial tension (N/m); rn is the interstitial radius of the mudstone (μm); and rs is the interstitial radius of the sandstone (μm). From Eq. (2), we can see that the interfacial potential difference increases with increasing difference between the interstitial radii. Therefore, it is more favorable for hydrocarbon to migrate from small pores to larger pores, resulting in accumulation (Berg, 1975; Malcolm, 1990). The interfacial potential index, PSI, is recommended as a relative measure of potential-controlled hydrocarbon function. PSI takes a value between 0 and 1: the smaller the index, the more favorable the physical properties of the rock for the formation of a stratigraphic reservoir, and vice-versa. The relationship is given by:
PSI = (P − Pmin )/(Pmax − Pmin )
(3)
where P is the interfacial potential of the target (J); Pmax is the critical maximum interfacial potential at a depth (J); and Pmin is the critical minimum interfacial potential at a depth (J). We have calculated PSI for 43 Neogene-Paleogene stratigraphic reservoirs discovered in the Nanpu Sag. PSI of most reservoirs is less than 0.6 (Fig. 7). The relationship between the ratio of the stratigraphic reservoirs discovered and the distribution of the interfacial potential indices gives the reservoir control frequency of the interfacial potential as:
Yp = − 0.254 × ln (PSI ) + 0.4511
(4)
where Yp is the reservoir control frequency of the interfacial potential, and PSI is the interfacial potential index. 3.1.3. Sedimentary facies as a hydrocarbon accumulation constraint and its quantitative characterization 3.1.3.1. Relatively high-porosity and high-permeability sedimentary facies: favorable for hydrocarbon accumulation. Sedimentary facies
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hydrocarbon accumulation and for its formation and distribution, and for its control of the formation and distribution of hydrocarbon reservoirs. Generally speaking, carbonate and clastic rocks tend to form high-porosity and high-permeability formations in high-energy environments. For example, coarse-grained and wellsorted sandstone reservoirs are developed in high-energy shoreface environments, and form reef and bank sediments, or even carbonate reef sediments, in marine environments. The more favorable the original reservoir depositional conditions of these formations are, the more readily they will form high-porosity and high-permeability zones after their modification by subsequent geological activity. Therefore, favorable sedimentary facies always show a consistent distribution of appropriate properties, and reservoirs with such properties are the preferred locations for hydrocarbon migration and accumulation. There are several types of sedimentary facies developed in the Nanpu Sag, such aslake facies, subaqueous fan turbidite, delta, channel, fan delta, interchannel and alluvial fan facies (Xu et al., 2006; Liang et al., 2008; Wang et al., 2012). Stratigraphic reservoirs are mainly found in the fan delta facies, braided delta facies, alluvial fan facies, lake facies, and turbidite. Of the stratigraphic reservoirs in the Nanpu Sag, 41.9% occur in fan delta front, 30.2% in braided delta front and 11.6% in turbidite. Fewer than 20% of all stratigraphic reservoirs are found in the other facies (Fig. 8a). Reservoir lithofacies are mainly medium sandstone, fine sandstone and gritstone (Fig. 8b). Their physical properties are quite good with porosity ranging from 15% to 35% and permeability over 10 mD (Fig. 8c and d).
Fig. 6. Porosity distribution characteristics of stratigraphic reservoirs in the Nanpu Sag.
3.1.3.2. Quantitative characterization of facies-controlled hydrocarbon reservoir distribution. The facies’ control on hydrocarbon reservoir distribution is quantitatively characterized by the reservoir formation controlling frequency of different facies. By statistical analysis of discovered reservoirs in various facies, we established the quantification standard between facies and hydrocarbon accumulation frequency (Table 1). The number of discovered reservoirs in different facies is different from, which is same of their percentage in the total reservoirs. The higher the percentage of discovered reservoir in a certain facies is, the larger its control on hydrocarbon accumulation is, and vice versa. With standardization of this percentage, we obtained the relative frequency for hydrocarbon accumulation of different facies (Eq. (5), Table 1). Specifically, we give the maximum value of 1 to the facies where we found the most reservoir or the highest percentage, while the minimum value of 0 was given to the facies where no reservoirs were identified; frequency of other facies are between 0 and 1 (Table 1). But we should caution that the 0 frequency of a certain facies does not mean that no hydrocarbons will be found or exist in this facies, and the relative frequency just gives us a comparative relationship between different facies. Therefore, the controlling ratio of certain sedimentary facies ranges from 0 to 1.
Ydi = (dni /dnt )/(dnmax /dnt ) Fig. 7. Relationship between stratigraphic reservoirs and indices of interfacial potential in the Nanpu Sag.
represent specific environments and processes, formed under specific conditions (Feng, 1993). The hydrocarbon control function of sedimentary facies is distinguished by various lithofacies, combinations of lithofacies and diagenesis for different sedimentary facies or microfacies. The “sedimentary facies control function for hydrocarbon accumulation” means that relatively high-porosity and high-permeability sedimentary facies are favorable for
(5)
where Ydi is the reservoir control frequency of a certain sedimentary facies i, dni is the number of discovered reservoirs in a certain sedimentary facies i; dnmax is the number of the discovered reservoirs within a certain facies that has the most discovered reservoirs; dnt is the number of total discovered reservoir within all the facies. 3.1.4. Hydrocarbon control function of regional cap rock and its quantitative characterization 3.1.4.1. Geological characteristics of regional cap rock-controlled hydrocarbon reservoir distribution. Regional cap rock is an essential condition for the formation and conservation of hydrocarbon
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Fig. 8. Hydrocarbon control characteristics by the Neogene–Paleogene sedimentary facies in the Nanpu Sag.
Table 1 Reservoir control frequency of different sedimentary facies. Sedimentary facies
The number of reservoirs discovered
Percentage (%) Reservoir control frequency
Fan delta front Braided delta front Turbidite Lake Fan delta plain Alluvial fan Braided delta plain
18 13
41.86 30.23
1.00 0.72
5 4 2 1 0
11.63 9.30 4.65 2.33 0.00
0.28 0.22 0.11 0.06 0.00
reservoirs. Depending on their lateral distribution and other features controlling the hydrocarbon reservoir distribution, cap rocks are described as directly-overlying local cap rocks and regional cap rocks. For most petroliferous basins, widely distributed, thick and stable regional cap rocks play an important role in hydrocarbon migration and accumulation in basins (Chen et al., 2003b; Dou and Xu, 1992; Tong and Niu, 1989; Zhou, 1997; Zhou and Wang, 2002), and determine the hydrocarbon reservoirs’ planar distributions. According to the present exploration results of the Nanpu Sag, four sets of regional cap rocks have great effects on hydrocarbon accumulations (Xu et al., 2008; Zhu et al., 2011). One is the dark Es3mudstone. As an important set of cap rock and high-quality source rock, it is widely distributed over most of the Nanpu Sag, and plays an important role in conserving pre-Paleogene buried hill reservoirs. The second set is the Ed2 lake flooding mudstone. It is widely distributed in the south of Nanpu Sag, and is regional cap rocks for the reservoirs in Shahejie Formation and 3rd member of Dongying Formation, with the greatest thickness over 300 m. The third set is the tight basalt cap rock of Guantao Formation, and it is mainly distributed in the west of Nanpu Sag, with the greatest thickness over 500 m. This set of cap rock is better than any other one in sags of Bohaiwan basin, below which it has a great
enrichment of hydrocarbons, with the maximum height of hydrocarbon column of 1000 m. On the other hand, hydrocarbons discovered above this set of cap rocks are mostly related to the later faulting activities. The fourth set is mudstone cap rocks in Lower Minghuazhen Formation, which is distributed in the whole sag, with the maximum thickness over 600 m. Above this set of caprocks, there are no industrial hydrocarbon reservoirs. 3.1.4.2. Quantitative characterization of cap rock-controlled hydrocarbon reservoir distribution. Hydrocarbon sealing capacity by a regional cap rock is here quantified by geostatistical analysis. A quantitative relationship was established between the thickness of regional cap rocks in the Nanpu Sag and the cumulative frequency commercial oil wells under these cap rocks, by studying their relationship (Fig. 9). The cumulative frequency commercial oil wells increases with increasing thickness of the regional cap rock; for areas with thickness over 400 m, the cumulative frequency commercial oil wells gradually increases, or is constant. According to the relationship between the cumulative frequency commercial oil wells and cap rock thickness, the frequency of reservoir control by the single factor of regional cap rock thickness has been determined. The frequency takes the value “1” if the thickness of the regional cap rock exceeds 400 m. If the thickness of the regional
Fig. 9. Relationship between cumulative daily outputs of hydrocarbons and regional cap rock thickness.
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cap rock is less than 400 m, the frequency can be obtained from Eq. (6):
Yc = 0.5627 × ln (X c ) − 2.3726
(6)
where Yc is the reservoir control frequency under the control of the single factor of the regional cap rock, and Xc is the thickness of the regional cap rock. 3.2. Functional-element constraint hydrocarbon distribution model and its procedure 3.2.1. Basic concept and characteristics of the functional-element constraint hydrocarbon distribution model Functional elements refer to indispensable geological factors that control hydrocarbon reservoir formation and distribution and can be described objectively and characterized quantitatively. The formation and distribution of stratigraphic reservoirs are jointly controlled by the four geological functional elements: regional cap rock (C), favorable sedimentary facies (D), interfacial potential (P) and source rock (S). Among the four factors low interfacial potential is the key factor. The vertical sequential superposition of CDPS functional elements determine the horizons of stratigraphic reservoir formation; their planar overlaps determine the planar range of formation; and their concomitant co-presence determine the time (T) of stratigraphic reservoir formation. The integrated reservoir effect of CDPS is termed the “functional-element constraint hydrocarbon distribution model”, and is expressed as T-CDPS (Fig. 10). To characterize the comprehensive T-CDPS model, we propose a quantitative Tcdps index to represent its possibility for hydrocarbon accumulation. Tcdps is from 0 to 1 and can be obtained from the geometric mean of the CDPS individual-factor
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reservoir formation frequencies during a main reservoir formation period as expressed by Eq. (7). On the one hand, the proposed Tcdps indicates that the four elements are inevitable during the formation of a petroleum reservoir. On the other hand, it also gives a relatively comparison of chances whether a petroleum reservoir will form or not on the basis of effects of four elements together. The greater the value of Tcdps, the more favorable, the more possible the zone is for reservoir formation, and vice-versa. Based on the Tcdps index value, we propose that stratigraphic reservoir formation areas can be divided into four types: the “favorable area”, where Tcdps lies in the range 1–0.75; the “moderately favorable area”, where Tcdps lies in the range 0.75–0.5; the “less favorable area”, where Tcdps lies in the range 0.5–0; and the “unfavorable area”, where Tcdps is 0. These values are obtained from:
Tcdps =
4
Yc × Yd × Yp × Ys
(7)
where Tcdps is the comprehensive assessment index of the T-CDPS functional-element constraint hydrocarbon distribution model; Yc is the reservoir control frequency of the regional cap rock; Yd is the reservoir control frequency of sedimentary facies; Yp is the reservoir control frequency of the interfacial potential; and Ys is the reservoir control frequency of the hydrocarbon kitchen. Vertically, sequential combinations of CDPS functional elements determine the horizons of stratigraphic reservoir formation. The state of the downward sequence of C, D, P and S is the favorable condition for stratigraphic reservoir formation (Fig. 10a). After hydrocarbons are generated and expelled from the lowest source rock (S), they initially migrate into stratigraphic sand traps by the action of interfacial potential. Various relatively high-porosity and high-permeability sedimentary facies provide favorable
Fig. 10. T-CDPS functional-elements constraint reservoir formation model for stratigraphic reservoirs.
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Fig. 11. Relationship between stratigraphic reservoir distribution and planar superimpositions of functional elements in the Nanpu Sag.
reservoir conditions for hydrocarbon migration to their perimeter, and accumulated hydrocarbons are preserved and sealed by the overlying regional cap rock. In practice, the four main geologic functional elements may occur in other vertical combinations, but CDPS is the combination that is most likely to facilitate stratigraphic reservoir formation (for example, the sequence DSCP would be unfavorable for stratigraphic reservoir formation because the regional cap rock, C, occurs under the source rocks, S, and could not effectively preserve the hydrocarbon resources generated in the source rocks). Planar/lateral superimpositions and combinations of the CDPS functional elements determine the range of stratigraphic reservoir formation (Fig. 10b). Of the 43 stratigraphic reservoirs discovered in the Nanpu Sag, statistical data shows that areas superimposed by all four functional elements C, D, P and S occupy 98%. Stratigraphic reservoirs discovered in areas where only three functional elements are superimposed account for the other 2%. No stratigraphic reservoirs have been discovered in areas where two functional elements, or less, are superimposed (Fig. 11). In summary, areas with superposition of more functional elements have a
higher possibility of stratigraphic reservoir formation, and areas with fewer functional elements have a lower possibility of stratigraphic reservoir formation. In theory, all four elements C, D, P and S must be satisfied for the formation of stratigraphic reservoirs. Thus the question arises as to why reservoir formation also sometimes occurs in areas where only three, two or even one reservoir formation factors exist. This is determined by the complexity of geologic conditions. Firstly, when we determine the extent of a hydrocarbon reservoir formation based on individual factors, the conclusions are not absolute “yes” or “no”, but are attached with certain frequencies. Therefore, when considering reservoir formation by superimposing the four functional elements, we can only get a possibility. Secondly, the T-CDPS model is only suitable for predictions of formation and distribution of stratigraphic reservoirs, and is not suitable for predictions of other types of reservoirs. Concomitant presence of the CDPS functional elements in geohistory determine the time of stratigraphic reservoir formation (Fig. 10c), both in the vertical sequential combinations and the planar/lateral superimpositions. The co-presence of the reservoir formation factors through time are preconditions for, and the key to, hydrocarbon reservoir formation. 3.2.2. Basic procedures of the functional-element constraint hydrocarbon distribution model to predict favorable formation areas of stratigraphic reservoirs The method and procedures for applying the functional-element constraint hydrocarbon distribution model to predict favorable reservoir formation areas are shown in Fig. 12. There are five steps: (1) analysis of petroliferous basins or sub-basins to determine the basic geological conditions (e.g. C, D, P and S) for hydrocarbon reservoir formation and their development histories and distribution characteristics. (2) Analysis of the mass of hydrocarbon generation and expulsion from the source rocks to determine the main geohistorical reservoir formation periods in petroliferous basins or sub-
Fig. 12. Method and procedures for applying the T-CDPS functional-element constraint hydrocarbon distribution model to predict favorable areas for stratigraphic reservoir formation.
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Fig. 13. Distribution of reservoir-forming frequency controlled by each functional element for the Paleogene Ed3 in the Nanpu Sag (A-regional cap rock (C), B-favorable sedimentary facies (D), modified from Wang et al. (2012), C-interfacial potential (P) and D-source kitchen (S)).
basins (T1, T2, …, Tn). (3) Analysis of the distribution characteristics of discovered hydrocarbon reservoirs to establish the geological model of hydrocarbon control function of the four functional elements, and to determine the reservoir control extent and frequency of every functional element for each reservoir formation period. (4) For each target formation, predict the favorable reservoir areas in different reservoir formation periods. Determine the favorable, moderately favorable, less favorable and unfavorable reservoir formation areas by superimposing the individual favorable functional elements with the same formation in different reservoir formation periods. (5) For an individual basin or sub-basin, predict the favorable exploration areas in different zones of interest. Finally, determine the favorable tectonic unit by superimposing favorable reservoir formation areas of various zones of interest.
4. Results 4.1. Reservoir formation period in the Paleogene Ed3, Nanpu Sag The first step in applying the T-CDPS functional-element constraint hydrocarbon distribution model is to determine the reservoir formation period. Late-stage accumulation is the most
important characteristic of reservoir formation in the Nanpu Sag, and the time of oil and gas charging into Ed3 was at the end of Paleogene Ed, about 25–23 Ma (Liu et al., 2000). 4.2. Quantitative prediction of the favorable Paleogene stratigraphic reservoir formation areas in the Paleogene Ed3, Nanpu Sag After determining the reservoir formation period, the planar characteristics and the constraints on hydrocarbons by the four functional elements need to be studied. Using the method described above, in the present work we investigated the geological characteristics of the CDPS functional elements of the Paleogene Ed3 strata in the Nanpu Sag over the main reservoir formation period, and calculated their reservoir-forming frequencies under the influence of each factor in turn. Fig. 13 shows the planar distribution of reservoir-forming frequencies in Ed3 strata for each of the functional elements, the sedimentary facies of which is adapted from Wang et al. (2012). The Tcdps indices were obtained from Eq. (7) and the planar distributions are shown in Fig. 14. Finally, areas favorable to the presence of stratigraphic reservoirs were predicted for the target. Prediction results show that there are 5 favorable reservoir formation areas in the target in the Nanpu Sag, with Tcdps values between 1 and 0.75.
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Fig. 14. T-CDPS model prediction of the possibility for stratigraphic reservoir formation as compared with oil-bearing locations (Paleogene Ed3 in the Nanpu Sag).
Table 2 Statistics of the possibility of forming Paleogene Ed3 stratigraphic reservoirs in the Nanpu Sag. Reservoirs Frequency of Frequency of facies concap rock trol function control function
Frequency of Frequency of Tcdps source con- index potential trol function control function
R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 R18
0.52 0.65 0.60 0.40 0.30 0.10 0.64 0.70 0.60 0.57 0.64 0.70 0.90 0.81 0.69 0.83 0.65 0.40
0.52 0.53 0.50 0.73 0.82 0.80 0.76 0.72 0.87 0.85 0.83 0.68 0.60 0.74 0.60 0.69 0.43 0.52
0.11 0.11 1.00 0.61 0.56 0.11 1.00 1.00 1.00 1.00 1.00 0.28 0.72 0.72 0.72 0.28 1.00 1.00
0.65 0.70 0.82 0.70 0.61 0.67 0.79 0.85 0.78 0.80 0.83 0.82 0.83 0.81 0.65 0.47 0.55 0.71
0.37 0.40 0.70 0.59 0.54 0.28 0.79 0.81 0.80 0.79 0.81 0.57 0.75 0.77 0.66 0.52 0.63 0.62
4.3. Reliability analysis of quantitative prediction by the T-CDPS model We calculated the single-factor frequency of every functional element for 18 discovered stratigraphic reservoirs from the Paleogene Ed3 in the Nanpu Sag (if a reservoirs is located between two sedimentary facies, we give it the value of the mean of the frequencies of these two facies) and obtained the Tcdps indices representing the overall reservoir-forming possibility, taken as the geometric mean of all the CDPS single-factor frequencies (Table 2). Results show that 7 of the 18 discovered stratigraphic reservoirs occur in areas designated as “favorable”, that is, where the estimated possibility is 1–0.75 (Fig. 14). 8 are found in the “moderately favorable” areas for which the estimated possibility is 0.75–0.5 (Fig. 14). Only 3 are found in the “less favorable” areas for which the estimated possibility is 0.5–0 (Fig. 14). No stratigraphic reservoirs have been found in the “unfavorable” areas for which the estimated possibility is 0 (Fig. 14). The results demonstrate the feasibility and effectiveness of the T-CDPS functional-element constraint hydrocarbon distribution model for the quantitative prediction of stratigraphic reservoir distribution.
5. Discussion The five favorable areas are Gaoshangpu structural belt, southern Laoyemiao structural belt and Nanpu I, II, V structural belt, respectively (Fig. 14). Meanwhile, there are two moderately favorable areas, with Tcdps values between 0.75 and 0.5, which are Nanpu III structural belt and Nanpu IV structural belt (Fig. 14).
The proposed “T-CDPS” model effectively predicts the favorable distribution of stratigraphic reservoirs in Es3, Nanpu Sag. Compared with the basin modeling method, this simple approach is easy to use and does not need too many parameters. On the
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contrary, lots of more accurate data on various parameters, e.g. source rock, reservoir, and structure, are needed to conduct basin modelings, or it may cause great errors in accuracy. Meanwhile, on the basis of traditional petroleum geology analysis method (e.g. petroleum system analysis), this approach attempts to quantify various control factors, which makes the final result more apparent and comparative. However, we have to admit that some problems still exist, such as how to make the standardization and value assignment more reasonable, which will be the further focus we will try to resolve.
6. Conclusions Functional elements refer to indispensable geological factors controlling hydrocarbon reservoir formation and distribution, which can be described objectively and characterized quantitatively. Regional cap rock (C), favorable sedimentary facies (D), interfacial potential (P) and source rock (S) are the most important functional elements controlling the formation and distribution of stratigraphic reservoirs in the Nanpu Sag. Regions of overlapped CDPS functional elements indicate the favorable zones for stratigraphic reservoir formation and distribution. The geometric mean of the four functional element control frequencies is the possibility of stratigraphic reservoir distribution in a target zone. The T-CDPS functional-element model is a new method and model for quantitative prediction of favorable areas for stratigraphic reservoir formation and distribution. There are 5 favorable exploratory areas for stratigraphic reservoirs distributed in Paleogene Ed3 in the Nanpu Sag. The five favorable areas are Gaoshangpu structural belt, southern Laoyemiao structural belt and Nanpu I, II, V structural belt, respectively. Meanwhile, there are two moderately favorable areas, with Tcdps values between 0.75 and 0.5, which are Nanpu III structural belt and Nanpu IV structural belt. This T-CDPS functional-element constraint model is proved to be feasible and effective in quantitatively predicting the stratigraphic reservoir distributions. Specifically, 15 out of 18 discovered stratigraphic reservoir are in the favorable and moderately favorable area, which have an estimated possibility of 0.5–1, while only 3 reservoirs are found in the less favorable area, whose relative possibility for hydrocarbon accumulation is 0–0.5.
Acknowledgments This work was supported by the National Natural Science Foundation of China Project (Nos. 41102085 and U1262205), China National Key Basic Research and Development 973 Program Project (No. 2011CB201102), and China National Science and Technology Major Project (No. 2011ZX05006-006). We appreciate the CNPC Jidong Oilfield Exploration and Development Research Institute for providing background geologic data and the permission to publish the results.
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