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Fuel 257 (2019) 116027

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Full Length Article

Oil physical status in lacustrine shale reservoirs – A case study on Eocene Shahejie Formation shales, Dongying Depression, East China

T

⁎

Hong Zhanga,b, Haiping Huanga,b, , Zheng Lic, Mei Liua a

School of Energy Resource, China University of Geosciences (Beijing), Beijing 100083, China Department of Geoscience, University of Calgary, Calgary, Alberta T2N 1N4, Canada c Geology Scientific Research Institute of Shengli Oilfield Company, Sinopec, Dongying 257015, China b

A R T I C LE I N FO

A B S T R A C T

Keywords: Shale oil Sequential extraction Thermal maturity Shahejie Formation Dongying Depression

A suite of 24 lacustrine shale core samples from the Eocene Shahejie Formation of the Dongying Depression, East China have been geochemically and petrologically characterized to investigate shale oil production potential and its constraints. Rock-Eval analysis indicates that majority samples are organic-rich with average TOC content of 3.69 wt%, dominated by Type II kerogen at early to peak oil generation stage. Shale oil physical status was defined as free, adsorbed and residual oils based on sequential extraction from different particle sizes under cold and Soxhlet extraction conditions. Quantitative data illustrate that free oil dominates the total extractable organic matter (EOM) yields (with an average of 66%). EOM bulk compositions are dominated by the saturated hydrocarbons, which decreases sequentially from free to residual status, corresponding to the increase of polar fractions. Several major factors, including TOC content, brittleness index, clay mineral content and thermal maturity, which may control relative proportions of different status oils in shale reservoirs are discussed herein. TOC and clay mineral content exert critical impact on adsorption ability and retention proportion, while brittleness index shows a positive correlation to EOM amounts. Thermal maturity plays the principle role in controlling hydrocarbon generation and then the expulsion behavior which in turn have major impacts on the total extract yields. Relatively low maturity coupled with high clay mineral contents were considered as main restrictions on shale oil producibility in the study area. Our sequential extraction results also demonstrated marked compositional fractionation during primary migration in shale reservoirs.

1. Introduction

continental rift basins, East China have a good potential of shale oil resource. Compared to extensive studies on pore microstructures, however, fluid characterization within shale reservoir has rarely been performed. Routine geochemical analysis focuses on hydrocarbon generation potential and source rock quality assessment, while mechanisms and processes of oil expelled from kerogen and stored in shale reservoir have rarely been investigated. Sequential extraction, currently used in conventional oil-bearing reservoir studies to reconstruct oil charge history based on compositional heterogeneities in reservoir rocks [4–8], is primarily designed for source rock assessment [9,10]. The first documented sequential extraction experiments performed by Beletskaya and Syrova [9] on rock chips (≥1 cm) with carbon dioxide at high pressure, subsequent Soxhlet extraction of the chips with chloroform, and final Soxhlet extraction of powder (< 60 μm) with chloroform to characterize bitumen fractionation within source rocks. Later, Sajgó et al. [10] defined the bitumen from l to 2 cm shale chips of

An upsurge of shale oil and gas resource exploration and development has been triggered by the successful precedent of shale gas exploration and development in North America [1]. Meanwhile, during the conventional petroleum prospection in past decades, numerous fractured shale reservoirs and shale oil shows have been discovered in Mesozoic-Cenozoic continental rift basins of eastern China, such as those in the Songliao, Bohai Bay and Nanxiang basins [2]. Several representative wells with considerable shale oil flows were discovered, for instance, well Pushen-1 in the Dongpu Depression (420 m3/d), well Shugu-165 in the Liaohe Sub-basin (24 m3/d after fracturing), and wells Biye-HF-1 (maximum 23.6 m3/d after fracturing) and Anshen-1 (4.68 m3/d) in the Biyang Depression [3]. Though shale oil occurrence, enrichment mechanism and oil producibility in lacustrine shale systems are largely unknown and shale oil prospections in China are still uncertain, these breakthroughs may indicate lacustrine shales in

⁎

Corresponding author at: School of Energy Resource, China University of Geosciences (Beijing), Beijing 100083, China. E-mail address: [email protected] (H. Huang).

https://doi.org/10.1016/j.fuel.2019.116027 Received 11 April 2019; Received in revised form 13 August 2019; Accepted 14 August 2019 Available online 24 August 2019 0016-2361/ © 2019 Elsevier Ltd. All rights reserved.

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Soxhlet extraction for 40 h as “coarse extracts” from “open pores”, while that from ground powder after initial extraction as “fine extracts” from “closed pores”. Significant compositional differences among these bitumens have been observed. Wilhelms et al. [4] put forward a schematic conceptual model depicting the progressive oil charges filling a porous media (the onion skin model) via a three step sequential extraction based on the crushed reservoir sandstone samples and a suite of solvents with increasing polarity. Schwark et al. [5] proposed a novel sequential extraction approach to obtain multiple extract fractions from intact cores and primary pore system by using a high-pressure solvent flow-through cell, which can also elucidate molecular memory effects [6]. By carrying out sequential extraction on the reservoir sample with different particle sizes, the free, adsorbed and inclusion oils have been recovered to characterize various charge pulses and reconstruct the filling history [7]. As shale reservoirs become a research focus recently, sequential extraction has become an important approach to elucidate the accumulation mechanism of shale oil. Sequential EOM extraction from lacustrine shales has been typically done by using increasing solvent polarity [11]. While such tests do recover more EOM and may help understand kerogen thermal evolution process [12], the nature of each fraction from different solvents has no practical implication in terms of shale reservoir characterization. The present study uses cold and Soxhlet extractions with constant solvent suite to sequentially recover EOM from variable particle sizes aiming to build links between shale oil physical status and its producibility. Shale oil exploration in the Dongying Depression of the Bohai Bay Basin, East China was initiated in 2013 with three boreholes (i.e., wells A, B and C) targeting the Eocene Shahejie Formation within the three main hydrocarbon generation sags. Though oil shows had been observed within shale intervals over 300 exploration wells incidentally and commercial hydrocarbon flows were achieved in over 30 wells in Jiyang Sub-basin [13], the production of shale oil from these newly drilled wells has turned out to be unsatisfactory. The drill stem test (DST, studied samples are not within the test interval) results show that cumulative oil production from wells A, B and C are 4.34, 0.002 and 0.17 tons, respectively. After hydraulic fracturing of well A, cumulative oil production was increased to 171 ton. The failure of commercial shale oil production from high quality source rocks raises some potential scientific issues on sweet spot recognition within these shale reservoirs. Thus, the aim of our study is to help understand shale oil mobility mechanisms by quantifying the proportions of different physical status of oil in a shale reservoir and shed light on constraints of shale oil producibility.

most active within episodes II and III, resulting in rapid-subsidence of the lacustrine depression and large-scale lake expansion [14]. The Es4s and Es3x subunits are formed during the maximum lake expansion period [19]. The humid and warm paleoclimate during this period promoted the blooming of mainly lacustrine algae [19]. Meanwhile, semi-closed saline water in an anoxic environment provided ideal conditions for the preservation of organic matter (OM) [2]. Six lithofacies of Es shales, including laminated calcareous mudstone, laminated gypsum mudstone, laminated clay mudstone, laminated marl, laminated dolomitic mudstone and massive mudstone were identified by previous investigations [15]. Shale oil reservoirs mainly consist of dissolution pores, interparticle pores, intracrystalline pores, organicmatter pores, tectonic fractures, abnormal-pressure fractures, mineralcontraction fractures and interlaminar fractures. Among those, dissolution pores and secondary recrystallized intercrystal pores, formed during the OM thermal evolution might be the principal matrix pores for hydrocarbon storage [15]. The porosities (for all lithofacies) generally vary from 3% to 10%, while permeabilities of laminated calcareous-, laminated marl mudstones are generally > 1.0 md, whereas those of laminated dolomitic-, laminated gypsum- and massive mudstones are < 0.5 md [15]. With regard to the diagenesis of the Shahejie shales, particularly for the laminated calcareous mudstone, recrystallization is the primary diagenetic attribute associating with the organic acid generation during kerogen thermal evolution. While for the laminated clay mudstone, clay mineral transformation is the principal diagenetic process [19]. In summary, Es4s-Es3x organic-rich shales in the Dongying Depression, as the main source rock intervals with thickness up to 400 m, has a great potential of shale oil resource [15]. 3. Samples and methods 3.1. Samples A suite of 24 shale core samples was collected from 3 exploration wells (A, B and C) in the Dongying Depression. Twelve samples were from the lower subunit of the Es3 member (Es3x) and other 12 samples were from the upper subunit of the Es4 member (Es4s) (Table 1). 3.2. Rock-Eval pyrolysis The Rock-Eval pyrolysis was performed on Rock-Eval 6 apparatus equipped with a flame ionization detector. Un-extracted samples were cleaned and powdered to 100 mesh. About 50 mg of sample was heated in a standard programmed pyrolysis oven at 25 °C/min to release hydrocarbons and CO2. Details of Rock-Eval 6 pyrolysis procedures and parameters derived from such analysis referred to Lafargue et al. [22] and Behar et al. [23].

2. Geological background Dongying Depression, with an area of approximately 5700 km2, is a typical half-graben lacustrine depression located in southeast Jiyang Sub-basin, Bohai Bay Basin, East China (Fig. 1) [14–17]. It is bounded by Chenjiazhuang High to the north, Luxi Uplift to the south, Qingtuozi High to the east, and Binxian-Linfanjia-Qingcheng High to the west. The northern side is a steeply faulted zone, while the southern side is a gentle slope, forming an asymmetric dustpan shaped depression [18,19]. The depression can be further divided into several structural units, including northern steep slope, southern gentle slope, Lijin sag, Minfeng sag, Niuzhuang sag, Boxing sag and central anticline [15]. The Cenozoic sediments reach a maximum thicknesses of 5 km in the depocenter [20] with the Eocene Shahejie (Es) Formation as the most important source kitchen and reservoir, which can be further divided into four members (i.e., Es1, Es2, Es3, and Es4 from top to bottom). The Es4 member consists of Upper (Es4s) and Lower (Es4x) subunits while the Es3 member comprises Upper, Middle and Lower (Es3s, Es3z and Es3x, respectively) subunits [19]. Four rifting episodes (i.e., I, II, III, and IV) in the syn-rift stage correspond to deposition of Ek, Es4, Es3‑Es2x, and Es2s-Ed intervals (Fig. 2) [19,21]. The faults are the

3.3. Vitrinite reflectance measurement Measurement of vitrinite reflectance (%Ro) was performed by using the MSP-400 Microscopic-fluorescence spectrometer in Shengli Oilfield Company. The experiment was performed at a temperature of 22 °C and a relative humidity of 20%. One sample had insufficient vitrinite particles; thereby only 23 reflectance data were obtained. 3.4. Sequential extraction and bulk composition (SARA) Shale cores were crushed gently to obtain the samples with decreasing particle sizes. The core was initially crushed and sieved into 8–10 mm size and weighed. The core chips were extracted with dichloromethane:methanol (DCM:MeOH, 9:1 v/v) at room temperature for 48 h and the solution was agitated discontinuously in the meantime. The first extract was considered as free oil in the present study. Then, the extracted samples were air-dried, further crushed, sieved to particle size of 2–5 mm and a weighed aliquot was cold extracted again at room 2

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Fig. 1. Location map of the study area. (a) Schematic map of the Bohai Bay Basin and its location in China (modified after Hao et al.) [16] (b) Tectonic setting map of the Dongying Depression showing the uplifts, sags, main faults and shale oil well locations where the samples were obtained (modified after Zou et al.) [17].

ethanol (9:1, v/v) and chloroform as eluents to yield the saturated, aromatic hydrocarbon and resin fractions, respectively.

temperature with DCM:MeOH (9:1 v/v) for 48 h to obtain the second extract, which was regarded as adsorbed oil. Finally, the residual chips after twice extraction were ground to powder (60–80 mesh, 0.18–0.25 mm) and Soxhlet extracted with DCM:MeOH (9:1 v/v) for 48 h to obtain the third extract, which was considered as residual oil. All extracts were air-dried and weighed to obtain the extraction yields. The asphaltenes were precipitated with excess cold hexane, filtered and weighted. The deasphalted maltene fraction was further separated on a silica gel:alumina column using hexane, DCM:anhydrous

3.5. X-ray diffraction (XRD) analysis Mineral XRD analysis was performed by using a D/max-2500 TTR anode X-ray diffractometer. Before the analysis, each sample was ovendried at 40 °C for 48 h and ground into powder with a particle size less than 40 μm by using an agate mortar in order to disperse minerals 3

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4. Results 4.1. Source rock geochemical characters Rock-Eval pyrolysis results are shown in Table 1. The TOC contents in Es3x subunit range from 1.98 to 7.22 wt% (with an average value of 3.98 wt%), while the TOC contents of Es4s subunit range from 1.44 to 7.66 wt% (average 3.41 wt%), indicating the good to excellent source rock quality [24]. The hydrogen index (HI, S2/TOC) values of Es3x subunit vary from 349 to 588 mg HC/g TOC, while those of the Es4s subunit range from 178 to 630 mg HC/g TOC, with an average value of 415 and 350 mg HC/g TOC, respectively. The HI vs. OI (Oxygen Index, S3/TOC) plot shows that majority of the studied samples fall into the mixed Type II/III kerogen region but are dominated by Type II kerogen with one exceptional sample in each subunit whose HI value is around 600 mg HC/g TOC and can be regarded as Type I kerogen (Fig. 3a). The HI vs. Tmax plot delivers the same conclusion that Type II kerogen dominates the studied sample suite (Fig. 3b). The %Ro values of the studied intervals in wells A, B and C are in the range of 0.48–0.76%, 0.44–0.67% and 0.52–0.86%, respectively. Majority samples are currently situated in the early to main oil generation maturity. The production index (PI, S1/ [S1 + S2]) values of 0.11–0.53 (average 0.32) also indicate marginal mature to main oil generation maturity level [24].

4.2. EOM yields and bulk compositions The amounts of the free (EOM-1), adsorbed (EOM-2) and residual (EOM-3) oils derived from sequential extraction of shale samples are shown in Table 2. The amount of EOM-1 varies from 0.4 to 29.1 mg/g rock and accounts for about 66% of total extractable yield. The amount of EOM-2 and EOM-3 range from 1.0 to 5.8 mg/g rock and 0.6–7.4 mg/ g rock, and account for 16% and 17% of total extractable yield, respectively. Most samples (> 70%) show a decreasing yield in sequential extraction with EOM-1 being significantly higher than those of EOM-2 and EOM-3, while samples such as AS-2, AS-3, AS-4, BS-5 and BS-15 show an increasing trend from free to residual oils (Fig. 4). The bulk compositions of saturated hydrocarbon, aromatic hydrocarbon, resins and asphaltenes (SARA) fractions in free, adsorbed and residual oils are shown in Table 2. The saturated hydrocarbons are the dominant fraction in all samples, except AS-3 which has resins as the highest proportion. The relative proportions of saturated hydrocarbons range from 28.0 to 72.5% (average 57.4%) in EOM-1, 21.1 to 72.4% (average 59.2%) in EOM-2 and 17.0 to 65.5% (average 42.8%) in EOM3, respectively. The relative proportions of aromatic hydrocarbons range from 8.9 to 27.1% (average 17.4%) in EOM-1, 9.6 to 26.2% (average 15.9%) in EOM-2 and 10.0 to 19.1% (average 14.9%) in EOM3, respectively. The polar fractions (resins and asphaltenes) vary from 13.9 to 62.2% (average 25.3%) in EOM-1, from 16.1 to 52.8% (average 24.9%) in EOM-2 and from 22.2 to 72.0% (average 42.3%) in EOM-3, respectively (Fig. 4). Different types of compounds in kerogen have different expulsion efficiencies and a general order of expulsion is saturated hydrocarbons > aromatic hydrocarbons > polar compounds, which was verified by various case studies [25] and laboratory simulations [26]. Hence, the ratio between the sum contents of saturated plus aromatic hydrocarbons and the sum contents of resins plus asphaltenes compounds [(Sat + Aro)/(Res + Asp)] is adopted herein to characterize the compositional fractionation and estimate the expulsion efficiency roughly. The higher value of this ratio is, the higher expulsion efficiency of source rocks is. This ratio decreases from EOM-1 to EOM-3 in most studied samples, however, a reverse trend of this ratio with more polar fractions in the EOM-1 has been observed from samples of AS-13 and CS-19, indicating a different expulsion behavior (Fig. 5).

Fig. 2. General stratigraphy column of the Dongying Depression (modified after Feng et al.) [21].

thoroughly. Subsequent computer processing of the diffractograms provided identification of various mineral phases and also semi-quantitative evaluation of their relative abundance (wt%). Based on the contents of brittle minerals such as quartz, feldspar and carbonate, brittleness index (BI) is defined herein to estimate brittleness of shale reservoirs. The calculation formula of BI is as follows:

BI=

VQtz + VPla + VCal + VDol + VAnk + VPyr + VSid VQtz + VPla + VCal + VDol + VAnk + VPyr + VSid + VClay

× 100%

VQtz, VPla, VCal, VDol, VAnk, VPyr, VSid and VClay represent volume proportion of quartz, plagioclase, calcite, dolomite, ankerite, pyrite, siderite and clay minerals, respectively.

4

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Table 1 Rock pyrolysis, vitrinite reflectance (%Ro), strata and depth data of shale samples. Sample

Strata

Depth (m)

TOC (wt%)

S1 (mg HC/g rock)

S2 (mg HC/g rock)

S3 (mg CO2/g rock)

Tmax (°C)

Ro (%)

HI (mg HC/g TOC)

OI (mg CO2/g TOC)

S1/TOC

PI

AS-1 AS-2 AS-3 AS-4 BS-5 CS-6 CS-7 CS-8 CS-9 CS-10 CS-11 CS-12 AS-13 BS-14 BS-15 BS-16 BS-17 CS-18 CS-19 CS-20 CS-21 CS-22 CS-23 CS-24

ES3X ES3X ES3X ES3X ES3X ES3X ES3X ES3X ES3X ES3X ES3X ES3X ES4S ES4S ES4S ES4S ES4S ES4S ES4S ES4S ES4S ES4S ES4S ES4S

3059.92 3125.65 3170.14 3233.29 3304.10 3313.86 3586.16 3593.01 3598.15 3658.46 3672.38 3674.34 3316.23 3333.04 3372.90 3402.73 3462.58 3751.14 3768.15 3771.65 3771.81 3786.16 3815.76 3830.45

3.40 1.98 7.22 2.17 2.81 3.64 3.79 4.51 4.77 5.63 3.27 4.54 1.44 2.50 1.99 7.66 1.88 3.08 5.05 4.32 2.77 2.97 3.63 3.57

4.43 2.88 4.58 2.68 2.49 7.22 6.93 7.46 8.18 14.64 8.47 8.83 2.67 3.40 3.19 8.69 3.44 4.93 10.41 8.74 4.77 7.14 5.88 5.68

16.36 8.86 35.55 7.58 16.51 13.72 13.53 17.61 18.08 20.74 11.65 17.88 4.97 12.85 9.98 48.27 5.09 9.88 13.52 7.67 9.37 8.38 9.66 10.36

0.26 0.25 0.31 0.23 0.52 0.37 0.19 0.09 0.19 0.60 0.41 0.45 0.20 0.56 0.56 0.47 0.66 0.59 1.13 0.53 0.45 0.46 0.61 0.57

443 445 447 445 440 444 439 445 443 442 433 442 433 439 443 446 N/A 431 431 N/A 434 442 429 441

0.48 0.54 0.58 0.65 0.44 N/A 0.52 0.53 0.53 0.6 0.62 0.62 0.76 0.47 0.53 0.57 0.67 0.73 0.76 0.76 0.76 0.78 0.83 0.86

481 447 492 349 588 377 357 390 379 368 356 394 345 514 502 630 271 321 268 178 338 282 266 290

8 13 4 11 19 10 5 2 4 11 13 10 14 22 28 6 35 19 22 12 16 15 17 16

130 145 63 124 89 198 183 165 171 260 259 194 185 136 160 113 183 160 206 202 172 240 162 159

0.21 0.25 0.11 0.26 0.13 0.34 0.34 0.3 0.31 0.41 0.42 0.33 0.35 0.21 0.24 0.15 0.4 0.33 0.44 0.53 0.34 0.46 0.38 0.35

AS: Samples from Well A; BS: Samples from Well B; CS: Samples from Well C; TOC = total organic carbon; Ro = vitrinite reflectance; HI = hydrocarbon index; OI = oxygen index; PI = production index; N/A: not applicable.

selected in the present study can not only illustrate primary migration mechanisms and expulsion fractionation, but also elucidate adsorptiondesorption processes. Data in the present study illustrated that the first extraction step (8–10 mm) removes most of the soluble OM, which resides in the open and semi-open pores. The amount released from the second (2–5 mm) and third extraction (60–80 mesh) facilitates storage mechanism illustration. Hydrocarbon generated from kerogen can be directly adsorbed onto the surface of kerogen due to its oil-wet nature [30]. A certain sorption capacity of kerogen reflecting the adsorption level was inferred by observing the EOM/OM ratios and generated petroleum cannot be expelled from source rocks unless the amount exceeds the adsorption capacity [31,32]. The adsorption/absorption effect which retains the hydrocarbon onto or allows it to diffuse through the kerogen surface is jointly controlled by the content, type and thermal maturity of kerogen (particularly in gas adsorption, [33]) and type of organic compounds to be adsorbed [34]. The adsorbed oil content shows a pronounced linear correlation with TOC content, suggesting that TOC plays a major role on the adsorbed oil proportion (Fig. 6b). While the amount of free oil is also positively correlated with TOC content, the trend is deviated at high oil content (Fig. 6a), likely above the OM saturation threshold. Free oil in pore space is not limited by TOC content and resulted from oil expulsion or primary migration. Thus, the constraints on free oil are more complicated than adsorbed oil, since the former is not only controlled by abundance, type and maturity of OM as is the latter, but it is also affected by the development and connectivity of the pore-fracture system, hydrocarbon expulsion and primary migration efficiency. Clay minerals, with unique interlayer structure and surface characteristics, also play an important role in hydrocarbon retention. The comparison between TOC and mineral surface area and adsorption oil amount illustrated that mineral surface area provides a first-order control on adsorption capability [35]. On the other hand, clay minerals may also reduce reservoir porosity and permeability which may induce the retention of hydrocarbons and further affect expulsion efficiency [36]. In engineering field, contrary to brittle minerals, clay minerals play an inverse role in fracturing, as the ductile deformation is prone to occur thereby clogging the seepage channel which is detrimental to the

4.3. Mineral composition Mineral compositions of the studied samples are shown in Table 3. Quartz, calcite, dolomite, ankerite, plagioclase, pyrite, siderite and clay are commonly present in the shales with clay, calcite and quartz as dominant minerals. The clay mineral contents range from 20.4% to 50.4% with an average value of 33.5%, while the proportions of calcite and quartz can be up to 53.1% (average 25.5%) and 27.9% (average 20.6%), respectively. Dolomite and ankerite have a maximum proportion of 35.1% (average 4.1%) and 29.3% (average 9.6%), respectively. Pyrite presents in all samples with an average proportion of 4.2%. The BI of the studied samples ranges from 49.7% to 79.6% (average 66.5%) (Table 3).

5. Discussion 5.1. Petrological controls on EOM yields Previous studies have demonstrated the influence of shale particle size on extraction yields and molecular component distributions. Extractions on coarse (1–2 cm) versus fine (ground to < 60 μm) particle sizes performed by Sajgó et al. [10] illustrated the mechanism of primary migration, while core chip (0.12–1.02 cm) versus ground source rock extractions conducted by Price and Clayton [27] elucidated the degree of fractionation within source rocks. Particle size was regarded as the primary control on EOM yields and bulk compositions, which is directly related to total available surface for extraction and constrains the accessibility of solvent. The fragmentation of particles increases the specific surface area and breaks solid-liquid interfacial tension (between the bitumen and the solid kerogen or mineral), which enables more efficient OM extraction [28]. With the pulverization proceeding, some isolated pores become accessible to solvent flow inside. The finer the particle size is, the higher the efficiency of solvent extraction, since the smaller grains have larger surface area which not only shorten the pathway for solvent percolation but also for solute diffusion [28,29]. The particle sizes of 8–10 mm, 2–5 mm and powder (60–80 mesh) 5

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facilitates shale oil production via natural and/or induced fractures after artificial fracturing [38,39]. The contents of free and adsorbed oils in our samples show a negative correlation with brittleness index, suggesting that the higher brittle mineral content in the shale reservoir, the more potential fractures exist, and thereby the less mobile hydrocarbons retained in the shale system (Fig. 6e and f). This negative correlation might be elucidated from two aspects (permeability and pressure). Since fractures can increase the cross-sectional area to flow to the utmost extent than those of micro-pores in shales, as the Darcy's law indicates, the occurrence of natural and/or artificial hydraulic fractures could enhance the reservoir permeability significantly. Meanwhile, abnormally higher formation pressures than ambient intervals or carriers frequently occur in mature organic-rich shales, as a result of the generation of gaseous and other low molecular weight liquid hydrocarbons [40]. The abnormaly high pressure in shales not only facilitates more fracture development to release the pressure, but also can provide natural driving energy to expel movable oils outside, which is quite different from fractures-occurred conventional reservoirs in normal formation pressure régime [41]. Thereby, high permeability fractures, coupled with the relatively high formation pressure, in shales will be the dominant migration pathway for hydrocarbon expulsions. Moreover, with increasing brittleness of shale, hydrocarbon expulsion into carrier beds or an adjacent reservoir (i.e., secondary migration) is more likely to occur, resulting in the low contents of the EOM in the source, whereas matrix pores will result in the retention of oil to a certain extent. It is worth noting that certain samples demonstrated a reverse yield trend (i.e. EOM-3 is abnormally higher than or equal to EOM-1 as indicated by samples of AS-2, AS-3, AS-4, BS-5, AS-13, BS-15). The abnormal EOM-3 may indicate that shales had generated hydrocarbons but the expulsion was limited by the petrological factors resulting in relatively higher residual oil than free and/or adsorbed oil. For instance, sample AS-13 has almost the lowest TOC and clay mineral content but highest BI value which has the lowest adsorption ability but high potential for the occurrence of natural fractures. Hydrocarbons prefer to be expelled outside rather than retained in such type of rock. Thus, the EOM displays an overall low amount and somewhat reverse trend between EOM-1 and EOM-3. The reverse trend of (Sat + Aro)/ (Res + Asp) ratio between EOM-1 and EOM-3 may provide supplementary evidence for the loss of hydrocarbons (saturated and aromatic hydrocarbons) in free oils due to the migration. Sample BS-5, an immature source rock characterized by the highest HI and lowest PI and S1/TOC values, has high hydrocarbon potential but has not generated significant amount of hydrocarbons, which may reduce kerogen adsorption ability. Meanwhile, non-indigenous oil charge has not been observed. Thereby, the EOMs are low with EOM-3 (residual oil) being the highest yield and polars being the most enriched fraction as demonstrated in Fig. 4. Sample AS-3 shows the same features as sample BS-5. Sample CS-19 is distinct from others due to the highest polar content within EOM-1, which is contradictory to the mature nature of the sample with %Ro of 0.76%. Coupled with the abnormally high S1/ TOC value (≫120 mg HC/g TOC), a non-indigenous, polar enriched source was inferred [42], but further investigation is still required.

Fig. 3. Rock-Eval hydrogen index vs. oxygen index plot (a). Rock-Eval hydrogen index vs. Tmax plot (b) for samples from the Dongying Depression, Bohai Bay Basin.

reservoir stimulation. In the present study, generally positive correlation between clay mineral contents and EOM amounts can be observed (Fig. 6c and d), which may also reveal the adsorption capacity on hydrocarbons. This positive correlation might be elucidated by previous molecular dynamic analysis. With the significantly larger specific surface area than common brittle minerals, clay minerals normally result in higher enrichment but lower mobility of hydrocarbons (i.e., stronger adsorption capacity) around their surface [37]. Various surface characters of clay minerals (e.g., montmorillonite, illite, kaolinite and chlorite) lead to an impact on hydrocarbon retention to different degree, and further have a significant impact on resource assessment in nanopore scale. Positive correlation herein demonstrates that adsorption effect may not only retain residual/adsorbed oils but also exert an impact on free oils resided in large pores, to some extent. Meanwhile, the free oil amount increases with clay mineral content also suggests a limitation of oil migration. Mineralogy, especially the brittle mineral content in shale, has a significant impact on the exploration and development of shale oil [38]. The higher the content of brittle minerals, the higher tendency for the occurrence of natural fractures will be under in situ stress, which in turn

5.2. Maturity controls on EOM yields Thermal maturity exerts great influence on petroleum systems, including on most of fluid and solid elements and geological/ geochemical processes. It is generally accepted that with thermal maturation, the HI of OM in source rocks decreases due to the thermochemical conversion of kerogen to oil and gas [43]. Accompanied by reduction of the hydrogen content within residual OM, at high maturation stage, the kerogen structure becomes intensively aromatized and polymerized and the proportion of gaseous hydrocarbons increases rapidly as a result of thermal cracking of liquid hydrocarbons [41]. On the other hand, contrary to conventional reservoirs, the shale 6

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Table 2 The EOM amount and gross composition data from sequential extraction on samples. Sample

Strata

Depth

Extract

(m) AS-1

ES3X

3059.92

AS-2

ES3X

3125.65

AS-3

ES3X

3170.14

AS-4

ES3X

3233.29

BS-5

ES3X

3304.1

CS-6

ES3X

3313.86

CS-7

ES3X

3586.16

CS-8

ES3X

3593.01

CS-9

ES3X

3598.15

CS-10

ES3X

3658.46

CS-11

ES3X

3672.38

CS-12

ES3X

3674.34

AS-13

ES4S

3316.23

BS-14

ES4S

3333.04

BS-15

ES4S

3372.9

BS-16

ES4S

3402.73

BS-17

ES4S

3462.58

CS-18

ES4S

3751.14

CS-19

ES4S

3768.15

CS-20

ES4S

3771.65

CS-21

ES4S

3771.81

CS-22

ES4S

3786.16

CS-23

ES4S

3815.76

EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3 EOM-1 EOM-2 EOM-3

EOM Amount

Gross Composition

(Sat + Aro)/(Res + Asp)

(mg/g rock)

Sat(%)

Aro(%)

Res(%)

Asp(%)

5.08 3.03 4.6 1.83 1.76 4.55 4.07 1.85 7.37 0.38 1.15 1.78 2.58 3.32 3.75 16.15 3.91 3.61 7.95 4.36 4.66 11.49 3.99 4.79 21.28 4.27 2.34 13.26 3.18 2.48 27.7 3.26 1.54 12.66 5.81 3.68 3.28 0.97 3.01 5.18 2.57 2.98 3.18 1.57 5.01 16.42 4.09 4.09 6.63 1.63 1.99 29.13 1.75 1.61 27.64 4.09 1.45 10.36 3.15 2.82 9.74 2.31 3.59 14.86 1.58 0.57 20.74 1.89 0.77

46.6 56.5 39.5 47.6 57.8 40.0 28.0 21.1 29.2 59.8 58.9 17.0 55.6 55.7 26.2 57.7 62.1 46.6 62.3 64.7 48.7 59.9 60.0 42.2 60.0 58.5 49.5 55.2 49.8 18.0 59.8 59.4 53.8 60.9 61.3 34.4 55.1 58.1 58.9 56.0 55.7 47.9 59.8 63.1 48.9 51.9 42.3 21.5 58.1 63.6 51.3 71.7 72.4 62.0 29.0 55.5 36.4 70.0 63.4 42.1 68.9 72.1 65.5 62.5 68.1 50.4 72.5 71.4 52.6

21.5 21.8 15.4 19.1 16.8 16.2 27.1 26.2 10.8 21.7 20.2 12.4 20.6 18.6 11.7 17.6 17.6 13.4 18.6 16.5 16.0 18.7 17.0 13.5 18.1 17.7 16.5 14.3 15.8 10.0 17.7 15.3 13.5 20.0 15.6 10.5 13.3 12.1 17.5 20.2 14.0 16.9 18.2 18.3 17.7 20.4 19.5 11.6 18.4 18.2 19.1 14.0 9.6 14.0 8.9 11.8 18.2 16.2 13.2 18.5 14.9 11.8 12.3 14.6 10.4 17.1 10.4 11.3 15.8

25.9 18.1 34.3 19.8 18.5 31.0 33.1 37.6 33.3 14.5 16.2 33.3 19.2 18.6 42.8 18.5 14.5 29.8 15.4 13.5 29.9 16.9 16.2 24.4 15.7 17.4 20.7 25.3 23.7 20.7 18.3 17.9 27.8 14.4 16.8 21.4 18.9 18.1 17.1 16.0 21.4 24.5 18.5 15.3 25.3 22.4 28.2 49.3 17.2 12.1 21.4 11.0 12.5 19.1 16.4 15.4 31.8 10.6 12.7 23.6 11.4 10.1 18.3 18.6 15.6 22.8 8.7 11.3 22.2

6.0 3.7 10.8 13.5 6.9 12.8 11.7 15.1 26.7 4.0 4.6 37.3 4.6 7.2 19.3 6.2 5.8 10.3 3.8 5.3 5.4 4.5 6.8 19.8 6.2 6.4 13.3 5.3 10.8 51.3 4.2 7.4 4.9 4.7 6.4 33.7 12.8 11.6 6.5 7.8 9.0 10.7 3.5 3.3 8.2 5.2 9.9 17.6 6.4 6.1 8.2 3.3 5.5 4.9 45.7 17.3 13.6 3.3 10.8 15.7 4.8 5.9 3.9 4.3 5.9 9.8 8.4 6.0 9.4

2.14 3.59 1.22 2.00 2.93 1.28 1.23 0.90 0.67 4.41 3.79 0.42 3.19 2.88 0.61 3.06 3.94 1.50 4.23 4.31 1.84 3.67 3.35 1.26 3.57 3.20 1.94 2.27 1.91 0.39 3.44 2.95 2.06 4.22 3.32 0.82 2.16 2.36 3.24 3.20 2.30 1.84 3.54 4.37 1.99 2.62 1.62 0.50 3.24 4.50 2.37 5.98 4.55 3.16 0.61 2.06 1.20 6.21 3.26 1.54 5.15 5.24 3.51 3.37 3.64 2.08 4.85 4.78 2.17

(continued on next page)

7

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Table 2 (continued) Sample

Strata

Depth

Extract

(m) CS-24

ES4S

3830.45

EOM-1 EOM-2 EOM-3

EOM Amount

Gross Composition

(Sat + Aro)/(Res + Asp)

(mg/g rock)

Sat(%)

Aro(%)

Res(%)

Asp(%)

10.24 2.46 1.15

69.5 69.4 45.2

12.5 11.4 18.7

11.9 13.7 25.2

6.1 5.5 10.9

4.55 4.22 1.77

EOM = extractable organic matter; Sat (%) = saturated hydrocarbon; Aro (%) = aromatic hydrocarbon; Res (%) = resins; Asp (%) = asphaltenes; (S + A)/(R + A) = (saturated + aromatic) hydrocarbon/(resins + asphaltene) ratio.

Samples from well B have %Ro in the range of 0.44% to 0.67%, suggesting early oil generation window (Fig. 7a). EOM yields are low at the immature stage (%Ro < 0.5%). When %Ro is < 0.53%, yields of free, adsorbed and residual oils are low and particularly the amount of free oil is less than the other two. This early evolution stage illustrates a process that the generation of hydrocarbons was initiated whereas its amount was not sufficient to exceed the sorption capacity of kerogen [31,32]. The vast majority of generated hydrocarbons were retained inside or on the surface of kerogen, whereas only a little oil was expelled to the adjacent larger pores within the inorganic matrix of source rocks. The free oil yield reaches a peak value at 0.57 %Ro and drops significantly at 0.67 %Ro. This reflects a process that generated hydrocarbons have already exceeded the sorption capacity and then been expelled from the kerogen and accumulated in the pores closely adjacent to kerogen. Nevertheless, expulsion has not started yet or insignificant in the whole system. When the pressure build-up reaches the fracturing pressure limit, the microcracking and a subsequent pressure release occurs [45,46]. During this episodic occurrence process, the isolated oil-accumulation micro-units were connected by microcracks and the pathways for hydrocarbons were provided. This speculation is based on the pressure-driven, discrete hydrocarbon phase movement primary migration mode functioning in variable lithology of source rocks, which is also considered as the dominant primary migration mechanism [41]. The evolutionary trend of the suite of samples in this study is in accordance with the classical primary migration mode. The burial history of well A (%Ro 0.48–0.76%) is generally similar to that of well B but a higher amount of residual oil than free oil makes well A unique (Fig. 7b). A comprehensive comparison between wells A and B based on existing data (depth interval, TOC, HI, %Ro, clay mineral and BI) suggests that the most distinct difference is HI values

pore system is more complicated especially for the OM-hosted nanopore network closely connected with organic maturation and hydrocarbon generation, which plays a key role in the hydrocarbon storage [44]. The impact of maturity on shale properties has been documented by previous studies. Zhang et al. [33] proposed that the thermal maturation of OM can significantly affect gas-adsorption capacity in shales based on a series of methane adsorption experiments under various temperature and pressure conditions. Nevertheless, other investigations indicated that thermal maturity has a dual impact on porosity as the liquid hydrocarbon generated during maturation can occupy and/or obstruct the pore space [29]. Except for secondary porosity, the change in source rock chemistry during thermal maturation can also cause the pressure build-up and thereby induce microcracking mainly resulting from the generation of gaseous and light oils, and clay mineral transformation. These processes may have a significant impact on the amount of retained hydrocarbons [45,46]. At the immature or early oil generation window, corresponding to the diagenesis to early catagenesis stage of shale, compaction of shale is not as tight as the common shale reservoirs resulting in the relatively high porosity [41]. The generated hydrocarbons are rich in high molecular weight (HMW) products, particularly resins and asphaltenes which can plug the pores and reduce the permeability in shale even though no quantitative data are available [47]. With increasing thermal maturity, more and more low-molecular-weight products (saturated and aromatic hydrocarbons) have been generated. Consequently, maturity not only directly controls the OM evolution and hydrocarbon properties, along with compaction and diagenesis effects, but also plays a key role in altering the quality of shale reservoirs and controlling hydrocarbon expulsion behavior and composition distribution. Furthermore, it can also have an impact on EOM amounts.

Fig. 4. Sequential extract yields and their respective bulk compositions. 8

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Fig. 5. Bar chart of the ratio of saturated plus aromatic hydrocarbons to resins and asphaltene ([Sat + Aro]/[Res + Asp]) from sequential extracts yield.

retention capacity at this maturation level. Hence, neither the main hydrocarbon generation nor expulsion has occurred yet. Most of the generated hydrocarbons were bound to kerogen surfaces or trapped in micro-pores. Therefore, the residual oil represents the major physical status of shale oils. The %Ro values vary from 0.52 to 0.86% in well C, indicating early to peak oil generation stage (Fig. 7c). The free oil is apparently the dominant fraction among the EOMs even though its content fluctuates with thermal maturity while the other two are consistently low throughout the studied interval. One interesting feature has been observed from a few closely adjacent samples (same maturity) particularly for the samples CS-19, CS-20 and CS-21. These samples have very

which range from 346 to 493 mg HC/g TOC (average 424 mg HC/g TOC) in well A and from 271 to 631 mg HC/g TOC (average 501 mg HC/g TOC) in well B. The overall lower HI values in well A samples indicate a lower hydrocarbon generation potential. Lower hydrocarbon transformation ratio will result in relatively low formation pressure due to relatively shallower burial depth, therefore, the lack of natural energy can be inferred. In addition, as Sandvik et al. [30] suggested, rich source rocks (with higher HI and TOC values) normally can exceed the sorption capacity at a lower maturation stage and thus hydrocarbon expulsion may occur earlier at lower gas-oil ratios (GOR) than lean ones. Another speculation for the unusual yield distribution in samples of well A is that generated hydrocarbons have not exceeded the Table 3 The mineral composition data (wt%) of shale samples. Sample

AS-1 AS-2 AS-3 AS-4 BS-5 CS-6 CS-7 CS-8 CS-9 CS-10 CS-11 CS-12 AS-13 BS-14 BS-15 BS-16 BS-17 CS-18 CS-19 CS-20 CS-21 CS-22 CS-23 CS-24

Strata

ES3X ES3X ES3X ES3X ES3X ES3X ES3X ES3X ES3X ES3X ES3X ES3X ES4S ES4S ES4S ES4S ES4S ES4S ES4S ES4S ES4S ES4S ES4S ES4S

Depth

Mineral composition (%)

(m)

Quartz

Plagioclase

Calcite

Dolomite

Ankerite

Pyrite

Siderite

Clay Mineral

(%)

3059.92 3125.65 3170.14 3233.29 3304.1 3313.86 3586.16 3593.01 3598.15 3658.46 3672.38 3674.34 3316.23 3333.04 3372.9 3402.73 3462.58 3751.14 3768.15 3771.65 3771.81 3786.16 3815.76 3830.45

20.9 14.3 15.6 18.5 19.9 25.0 26.8 20.4 27.5 20.7 23.8 24.3 13.0 15.4 17.8 22.5 12.8 24.1 27.9 22.8 23.6 20.5 18.5 17.6

2.3 0.8 0.0 0.0 2.5 0.0 1.9 2.6 3.0 0.0 0.0 2.3 1.0 1.5 1.7 0.0 2.8 2.8 3.5 4.6 1.9 1.9 2.7 2.7

31.8 53.1 36.9 29.8 35.5 27.5 27.1 15.2 21.5 35.6 20.9 8.1 33.6 45.4 41.0 11.1 13.7 3.0 4.2 7.8 22.3 43.6 18.2 24.1

6.0 0.0 5.4 0.0 0.0 13.0 0.0 7.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 35.1 0.0 0.0 0.0 0.0 0.0 13.5 16.9

0.0 9.2 0.0 20.7 6.7 0.0 5.9 0.0 9.4 14.1 10.4 23.8 29.3 12.7 7.3 13.4 0.0 15.0 15.9 19.4 7.8 9.9 0.0 0.0

3.9 2.2 4.2 4.2 4.2 3.4 3.6 4.4 5.0 4.0 3.7 4.3 2.5 2.6 3.1 6.2 3.6 4.7 6.2 9.1 4.1 3.6 5.2 2.5

1.1 0.0 4.2 0.3 0.0 0.0 1.8 1.5 0.0 0.0 2.2 0.0 0.0 0.0 0.0 1.0 4.1 0.0 0.0 2.3 0.0 0.0 0.0 0.0

34.0 20.4 33.8 26.5 31.2 31.1 32.9 48.0 33.5 25.6 39.0 37.2 20.6 22.4 29.0 45.8 28.0 50.4 42.2 34.0 40.2 20.5 42.0 36.1

66.0 79.6 66.2 73.5 68.8 68.9 67.1 52.0 66.5 74.4 61.0 62.9 79.4 77.6 71.0 54.2 72.0 49.7 57.8 66.0 59.8 79.5 58.0 63.9

BI: brittleness index. The calculation formula of BI is as follows: BI =

BI

VQtz + VPla + VCal + VDol + VAnk + VPyr + VSid VQtz + VPla + VCal + VDol + VAnk + VPyr + VSid + VClay

× 100%

VQtz, VPla, VCal, VDol, VAnk, VPyr, VSid and VClay represent volume proportion of quartz, plagioclase, calcite, dolomite, ankerite, pyrite, siderite and clay minerals, respectively. 9

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Fig. 6. Correlation between free and adsorbed oil with TOC content, brittleness index and clay mineral content (Outliers have not been included in regression).

5.3. Assessment on shale oil producibility and its implications

similar rock properties: TOC (5.05, 4.32 and 2.77 wt%, respectively), clay mineral content (43%, 34% and 41%, respectively) and brittleness index (58%, 67% and 60%, respectively), while sample CS-19 has much higher free oil content than other two. Unusually high S1/TOC ratios (207, 203 and 173 mg HC/g TOC, respectively) suggest migration contamination from non-indigenous oil (i.e. oil from a deeper or adjacent interval charging into current shale [42]). Different proportion of free vs. residual oils is likely caused by different ratios of in situ vs. exsitu oils in different samples. It is worth noting that the amounts of adsorbed and residual oil in these 3 wells are low and stable, which is in accordance with Sandvik et al. [30] who observed that a critical saturation threshold for generated petroleum needs to be surpassed before expulsion can occur.

5.3.1. Comparison with typical shale-oil systems In order to illustrate the cause of poor producibility in the Shahejie shale reservoirs, the similarity and difference between present case study and well-known Eagle Ford shale-oil system have been briefly depicted here. The %Ro values of Eagle Ford shale samples are in the range of 0.75 to 0.95% [48], which is much higher than the average % Ro of 0.63% in the present study. Moreover, mineralogy analysis of the Eagle Ford shale shows an average clay mineral content of 15% [49], while clay mineral contents in the Dongying Depression source rocks vary from 20 to 50%. Another key factor which has great impact on production fluid type prediction in unconventional reservoirs is the 10

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Fig. 7. The EOM yield evolution profile against maturity of studied wells.

GOR. Normally, higher GORs (> 178 m3/m3 (1000 scf/stb)) are essential to move oil out of source rocks [50]. Based on both laboratory simulations and observations of sedimentary basins, the evolution of GOR value has close correlation with maturity, which is generally < 178 m3/m3 within the oil generation window (%Ro < 1.0%), then increases exponentially to 1335 m3/m3 at the beginning of gas generation window [51,52]. The GOR values in the studied samples are much lower than 178 m3/m3 as a result of lower maturity (%Ro < 1.0%). According to Javie [50], the most effective shale oil production requires GOR of 178 to 623 m3/m3, while GOR of < 178 m3/m3 is considered to be a typical black oil with high content of resins and asphaltenes and low API gravities (< 40°API). Moreover, a correlation between GOR and viscosity illustrated that the viscosity shows a similar negative logarithm correlation with GOR, particularly when GOR < 89 m3/m3 [53]. The overall low maturity of the studied samples determines relatively high oil viscosity which has a great impact on shale oil producibility. Meanwhile, underdeveloped fracture system due to low maturity level exerts another drawback on the Shahejie lacustrine shales [15].

(Fig. 8). However, little oil has been recovered from these wells. By conducting the experiment on the Bakken shale oil, which is verified as indigenous oil within the source interval itself, Noble et al. [42] suggested that the samples where S1/TOC > 120 mg HC/g TOC may contain some non-indigenous hydrocarbons and those with values > 200 mg HC/g TOC are deemed to have been stained with allogenic hydrocarbons. While our studied samples have high OSI values and some samples may retain the non-indigenous oil, no commercial production occurs due to multiple controlling factors such as mineralogical brittleness, kerogen or/and clay mineral adsorption and thermal maturity need to be taken into account [2]. The OSI of > 100 mg HC/g TOC is essential but not enough to ensure shale oil production. Based on the comparison and analysis above, the relatively low maturity, coupled with the high clay mineral content, is interpreted to be the main constraints on production in the study area although shale intervals retain high amount of generated oils. Oils generated at relatively low maturity level (early oil window) are enriched in HMW polar compounds with very low GOR. Relatively high viscosity and low mobility impede movement of these heavy products within the shale micro- to nanopores by natural energy even after artificial stimulation. For the successful development of a shale oil resource, thermal maturity is a critical controlling factor and the favorable shale intervals should be within the late oil to condense generation window (%Ro 0.9–1.3%) [48]. If natural fractures are pervasive in the shale system, such as Monterey shales in Santa Maria Basin [54], the maturity may be not an overriding restrictive factor due to the well-developed fractures in that reservoir. Nevertheless, low maturity, high clay content and undeveloped fracture system in the studied shale intervals in the Dongying Depression are all unfavourable factors and failure to shale oil production is inevitable.

5.3.2. Shale oil producibility assessment and its constraints The producibility assessment is the principal issue in shale oil production. Jarvie [48] proposed an oil saturation index (OSI = S1 × 100/ TOC) as a quantitative evaluation parameter to evaluate the producibility. This parameter has proven to be effective in fractured Monterey, Bazhenov and Cody shales; Antelope, Barnett, Monterey, Cane Creek, Tuscaloosa and Mowry tight shales; and hybrid Bakken and Eagle Ford Shale formation reservoirs. In the present study, the OSI index of all but two samples exceed 100 mg HC/g TOC and up to 260 mg HC/g TOC with marked oil crossover effect (OSI exceeds 100 mg oil/g TOC). Shale oil production seems ensured on the basis of Jarvie’s [48] criteria 11

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OSI 0

50

100

150

200

250

0

300

2

TOC (%); S1 (mg HC/g rock) 4 6 8 10 12 14

16

3050

3150

3250

Depth (m)

3350

3450

3550

3650

3750

Es3x

TOC S1

Es4s 3850

Fig. 8. The plot of oil saturation index (OSI, S1/TOC) value and crossover effect in the studied samples.

resource extent calculation model for shale oil systems in the Dongying Depression. Meanwhile, analysis on the oil physical status may help engineers to select suitable enhance oil recovery methods.

5.3.3. Implications for future studies Unconventional petroleum resource prospections have triggered an increasing focus on shale oil potential of the Dongying Depression. One of key issues for shale oil resource assessment is the estimation of oil-insitu resource, particularly for the movable shale oil resource, which was currently carried out by theoretical modelling, empirical statistics and other approaches [13,48,55]. Nevertheless, most of existing methods lack for the consideration on various oil physical statuses and merely simplify the adsorbed oil as immovable hydrocarbons. Hence, in the assessment of movable shale oil resource, it is essential to distinguish contributions from different oil statuses. The present sequential extraction study, focusing on shale oil physical status and its corresponding petrological and maturity constraints, presents not only the fractionation effect on bulk and molecular geochemical characteristic levels, but also a practical geochemical approach to characterize the shale oil occurrence. This can be applied in future shale oil exploration wells or the re-examination on oil and gas shows shale intervals in previous wells in study area. Further, combined with more thorough studies, the present study may provide more accurate approach to estimate the proportion of movable shale oils and then optimize the

6. Conclusions Sequential extraction on Es3x and Es4s lacustrine organic-rich shales from the Dongying Depression, East China demonstrated the variation on abundance and proportion of free, adsorbed and residual oils respectively, which also revealed the marked compositional fractionation effect within shale reservoirs during primary migration. Multiple constraints on the EOM yields include TOC and clay mineral content, which show positive correlations on EOM amounts due to the retention of hydrocarbons. The rock brittleness shows a negative relationship with the EOM amount. Thermal maturity plays the principal role in controlling hydrocarbon generation and thus the expulsion behavior, which has a major impact on the total extract yields. Compared to successful North American shale oil production, the relatively-low maturity, coupled with the high clay mineral content were considered to be the main constraints on the none productive shales in the 12

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Dongying Depression. The most attractive shale oil intervals should be highly matured (late oil to condensate generation window) and/or be highly fractured.

China. Sed Geol 2013;295:1–26. [22] Lafargue E, Marquis F, Pillot D. Rock-Eval 6 applications in hydrocarbon exploration, production, and soil contamination studies. Revue De L'Institut Français Du Pétrole 1998;53:421–37. [23] Behar F, Beaumont V, Penteado HLDB. Rock-Eval 6 technology: performances and developments. Oil Gas Sci Technol 2001;56:111–34. [24] Peters KE, Cassa MR. Applied source rock geochemistry. In: Magoon LB, Dow WG, editors. The petroleum system-from source to trap. AAPG memoir 60. 1994. p. 93–120. [25] Leythaeuser D, Schaefer RG, Radke M. Geochemical effects of primary migration of petroleum in Kimmeridge source rocks from Brae field area, North Sea. I: gross composition of C15+-soluble organic-matter and molecular composition of C15+saturated hydrocarbons. Geochim Cosmochim Acta 1988;52:701–13. [26] Lafargue E, Espitalie J, Jacobsen T, Eggen S. Experimental simulation of hydrocarbon expulsion. Org Geochem 1990;16:121–31. [27] Price LC, Clayton JL. Extraction of whole versus ground source rocks: Fundamental petroleum geochemical implications including oil-source rock correlation. Geochim Cosmochim Acta 1992;56:1213–22. [28] Tamimi A, Uysal BZ. Parametric investigation of oil-shale extraction with organic solvents. Sep Sci Technol 1990;25:1151–9. [29] Wei L, Mastalerz M, Schimmelmann A, Chen YY. Influence of Soxhlet-extractable bitumen and oil on porosity in thermally maturing organic-rich shales. Int J Coal Geol 2014;132:38–50. [30] Sandvik EI, Young WA, Curry DJ. Expulsion from hydrocarbon sources: the role of organic absorption. Org Geochem 1992;19:77–87. [31] Philippi GT. On the depth, time and mechanism of petroleum generation. Geochim Cosmochim Acta 1965;29:1021–49. [32] McAuliffe CD. Oil and gas migration–chemical and physical constraints. AAPG Bull 1979;63:761–81. [33] Zhang TW, Ellis GS, Ruppel SC, Milliken K, Yang RS. Effect of organic-matter type and thermal maturity on methane adsorption in shale-gas systems. Org Geochem 2012;47:120–31. [34] Collins SH, Melrose JC. Adsorption of asphaltenes and water on reservoir rock minerals. SPE oilfield and geothermal chemistry symposium. Society of Petroleum Engineers; 1983. [35] Kennedy MJ, Pevear DR, Hill RJ. Mineral surface control of organic carbon in black shale. Science 2002;295:657–60. [36] Pepper AS. Estimating the petroleum expulsion behaviour of source rocks: a novel quantitative approach. Geol Soc Lond Spec Publ 1991;59:9–31. [37] Wang S, Javadpour F, Feng QH. Molecular dynamics simulations of oil transport through inorganic nanopores in shale. Fuel 2016;171:74–86. [38] Bowker KA. Recent development of the barnett shale play, forth worth basin. W Tex Geol Soc Bull 2003;2:6. [39] Jarvie DM, Hill RJ, Ruble TE, Pollastro RM. Unconventional shale-gas systems: the Mississippian Barnett Shale of north-central Texas as one model for thermogenic shale-gas assessment. AAPG Bull 2007;91:475–99. [40] Hedberg HD. Relation of methane generation to undercompacted shales, shale diapirs, and mud volcanoes. AAPG Bull 1974;58:661–73. [41] Tissot BP, Welte DH. Petroleum formation and occurrence. 2nd ed. Berlin: SpringerVerlag; 1984. [42] Noble RA, Kaldi JG, Atkinson CD. Seals, traps, and the petroleum system. Chapter 2: oil saturation in shales: applications in seal evaluation. AAPG Memoir 67. 1997. [43] Behar F, Vandenbroucke M. Chemical modelling of kerogens. Org Geochem 1987;11:15–24. [44] Loucks RG, Reed RM, Ruppel SC, Hammes U. Spectrum of pore types and networks in mudrocks and a descriptive classification for matrix-related mudrock pores. AAPG Bull 2012;96:1071–98. [45] Snarsky AN. Die primäre migration des erdöls. Freib Forsch 1962;123:63–73. [46] Pelet R, Tissot B. Nouvelles donnees sur les mecanismes de genese et de migration du petrole simulation mathematique et application a la prospection. 8th World Petroleum Congress. 1971. [47] Mohnhoff D, Littke R, Krooss BM, Weniger P. Flow-through extraction of oil and gas shales under controlled stress using organic solvents: Implications for organic matter-related porosity and permeability changes with thermal maturity. Int J Coal Geol 2016;157:84–99. [48] Jarvie DM. Shale resource systems for oil and gas: part 2—shale-oil resource systems. In: Breyer JA, editor. Shale reservoirs—giant resources for the 21st century. AAPG Memoir 97. 2012. p. 89–119. [49] Jarvie DM. Shale resource systems for oil and gas: part 1—shale-gas resource systems. In: Breyer JA, editor. Shale reservoirs—Giant resources for the 21st century. AAPG Memoir 97. 2012. p. 69–87. [50] Jarvie DM. Components and processes affecting producibility and commerciality of shale resource systems. Geol Acta 2014;12:307–25. [51] England WA, Mackenzie AS, Mann DM, Quigley TM. The movement and entrapment of petroleum fluids in the subsurface. J Geol Soc 1987;144:327–47. [52] Di Primio R, Dieckmann V, Mills N. PVT and phase behaviour analysis in petroleum exploration. Org Geochem 1998;29:207–22. [53] Hemmati-Sarapardeh A, Khishvand M, Naseri A, Mohammadi AH. Toward reservoir oil viscosity correlation. Chem Eng Sci 2013;90:53–68. [54] Aydin A. Fractures, faults, and hydrocarbon entrapment, migration and flow. Mar Pet Geol 2000;17:797–814. [55] Wang YS, Li Z, Gong JQ, Zhu JJ, Hao YQ, Hao XF, et al. Discussion on an evaluation method of shale oil and gas in Jiyang depression:a case study on Luojia area in Zhanhua sag. Acta Petrol Sin 2013;34:83–91. (in Chinese with English abstract).

Acknowledgements This study is supported by National Natural Science Foundation of China (Grant Number: 41573035, 41873049) and the Mitacs project at University of Calgary. Drs. Steve Larter and Lloyd Snowdon are acknowledged for useful discussion and constructive comments. Houfei Lin, Li Ma, Chengyu Chai and Qin Wei from China University of Geosciences (Beijing) were acknowledged for the help of experiments. Two anonymous reviewers are acknowledged for their constructive comments that substantially improved the quality of this manuscript. References [1] Ross DJK, Bustin RM. Characterizing the shale gas resource potential of DevonianMississippian strata in the Western Canada sedimentary basin: application of an integrated formation evaluation. AAPG Bull 2008;92:87–125. [2] Wang M, Wilkins RWT, Song GQ, Zhang LY, Xu XY, Li Z, et al. Geochemical and geological characteristics of the Es3L lacustrine shale in the Bonan sag, Bohai Bay Basin, China. Int J Coal Geol 2015;138:16–29. [3] Zhang JC, Lin LM, Li YX, Tang X, Zhu LL, Xing YW, et al. Classification and evaluation of shale oil. Earth Sci Front 2012;19:322–31. (in Chinese with English abstract). [4] Wilhelms A, Horstad I, Karlsen D. Sequential extraction—a useful tool for reservoir geochemistry? Org Geochem 1996;24:1157–72. [5] Schwark L, Stoddart D, Keuser C, Spitthoff B, Leythaeuser D. A novel sequential extraction system for whole core plug extraction in a solvent flow-through cell—application to extraction of residual petroleum from an intact pore-system in secondary migration studies. Org Geochem 1997;26:19–31. [6] Leythaeuser D, Keuser C, Schwark L. Molecular memory effects recording the accumulation history of petroleum reservoirs: a case study of the Heidrun Field, offshore Norway. Mar Pet Geol 2007;24:199–220. [7] Pan CC, Liu DY. Molecular correlation of free oil, adsorbed oil and inclusion oil of reservoir rocks in the Tazhong Uplift of the Tarim Basin, China. Org Geochem 2009;40:387–99. [8] Yu S, Wang XL, Xiang BL, Ren JL, Li ET, Wang J, et al. Molecular and carbon isotopic geochemistry of crude oils and extracts from Permian source rocks in the northwestern and central Junggar Basin, China. Org Geochem 2017;113:27–42. [9] Beletskaya SN, Syrova GM. A study of the distributions of the disseminated bitumens in pore systems of rocks related to the assessment of the state of migration processes. A comparative study of the chloroform extracts from non-crushed and crushed rocks. Geol Nefti i Gaza 1972;16:44–52. [10] Sajgó C, Maxwell JR, Mackenzie AS. Evaluation of fractionation effects during the early stages of primary migration. Org Geochem 1983;5:65–73. [11] Pan YH, Li MW, Sun YG, Li ZM, Jiang QG, Liao YH. Geochemical characterization of soluble organic matter with different existing states in low-maturity argillaceous source rocks of lacustrine facies. Geochimica 2018;47:335–44. (In Chinese with English abstract). [12] Deng CP, Wang HT, Chen JP, Zhang DJ. Chemical features of extracts from source rocks in coal measures with different polarity solvents. Pet Explor Dev 2005;32:48–52. (in Chinese with English abstract). [13] Li Z, Zou YR, Xu XY, Sun JN, Li MW, Peng PA. Adsorption of mudstone source rock for shale oil–Experiments, model and a case study. Org Geochem 2016;92:55–62. [14] Guo XW, He S, Liu KY, Song GQ, Wang XJ, Shi ZS. Oil generation as the dominant overpressure mechanism in the Cenozoic Dongying depression, Bohai Bay Basin, China. AAPG Bull 2010;94:1859–81. [15] Liang C, Cao YC, Jiang ZX, Wu J, Song GQ, Wang YS. Shale oil potential of lacustrine black shale in the Eocene Dongying depression: implications for geochemistry and reservoir characteristics. AAPG Bull 2017;101:1835–58. [16] Hao F, Zhou XH, Zhu YM, Bao XH, Yang YY. Charging of the Neogene Penglai 19–3 field, Bohai Bay Basin, China: Oil accumulation in a young trap in an active fault zone. AAPG Bull 2009;93:155–79. [17] Zou YR, Sun JN, Li Z, Xu XY, Li MW, Peng PA. Evaluating shale oil in the Dongying Depression, Bohai Bay Basin, China, using the oversaturation zone method. J Pet Sci Eng 2018;161:291–301. [18] Li SM, Pang XQ, Li MW, Jin ZJ. Geochemistry of petroleum systems in the Niuzhuang South Slope of Bohai Bay Basin – part 1: source rock characterization. Org Geochem 2003;34:389–412. [19] Liang C, Jiang ZX, Cao YC, Wu J, Wang YS, Hao F. Sedimentary characteristics and origin of lacustrine organic-rich shales in the salinized Eocene Dongying Depression. Geol Soc Am Bull 2018;130:154–74. [20] Pang XQ, Li MW, Li SM, Jin ZJ. Geochemistry of petroleum systems in the Niuzhuang South Slope of Bohai Bay Basin: Part 3. Estimating hydrocarbon expulsion from the Shahejie formation. Org Geochem 2005;36:497–510. [21] Feng YL, Li ST, Lu YC. Sequence stratigraphy and architectural variability in late Eocene lacustrine strata of the Dongying Depression, Bohai Bay Basin, eastern

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