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A preliminary assessment on CO2 storage capacity in the Pearl River Mouth Basin offshore Guangdong, China
International Journal of Greenhouse Gas Control 5 (2011) 308–317
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A preliminary assessment on CO2 storage capacity in the Pearl River Mouth Basin offshore Guangdong, China Di Zhou ∗ , Zhongxian Zhao, Jie Liao, Zhen Sun CAS key Laboratory of Marginal Sea Geology, South China Sea Institute of Oceanology, 164 West Xingang Road, Guangzhou, China
a r t i c l e
i n f o
Article history: Received 17 May 2010 Received in revised form 4 September 2010 Accepted 25 September 2010 Available online 25 October 2010 Keywords: Carbon dioxide Capture and Storage (CCS) CO2 storage capacity Pearl River Mouth Basin Guangdong Province South China Sea
a b s t r a c t Guangdong has China’s highest GDP of any province and actively advocates low-carbon development. At present, Guangdong’s low-carbon roadmap emphasizes the adjustment of industrial structure, increased energy saving and efficiency, and renewable and nuclear energy, while CCS is not featured. This is partially due to the geographical gap in the existing body of research on CCS in China, as to date no substantial research on CCS has taken place in the regions south of the Yangtze River, including Guangdong. This paper presents the partial outcome of the first CCS-related research in Guangdong, which is aiming for a preliminary assessment on the effective CO2 storage capacity in the Pearl River Mouth Basin (PRMB) offshore Guangdong. As the storage capacity onshore Guangdong is limited as shown by a parallel study, the offshore sedimentary basins deserve particular attention. The PRMB is the largest sedimentary basin in the passive margin of the northern South China Sea, with a total area of nearly 200 000 km2 and maximum sediment thickness of over 14 km. Based on published data, geological conditions and parameters for CO2 storage are analyzed, volumes of potential formations are calculated on a GIS platform, and the storage capacity is calculated according to CSLF and USDOE formulations. The estimated effective storage capacity is 308 Gt in deep saline formations, including 0.06 Gt in oil and gas fields. This capacity is sufficiently large for storaging the CO2 emitted from the major point sources in Guangdong in many decades. Promising areas are suggested for further investigations. © 2010 Elsevier Ltd. All rights reserved.
1. Introduction Carbon dioxide Capture and Storage (CCS) technology is the most efficient technological option for greenhouse gas mitigation that allows continued use of fossil fuels. China is undertaking a range of technical research and development projects on CCS, including the national fundamental research and high-tech programs, as well as a large number of international programs. There is a geographical gap in the existing body of research on CCS in China. To date, all of the major CCS projects in China have focused on the regions north of the Yangtze River, with no substantial research having taken place in China’s wealthy manufacturing provinces in the south. Guangdong is China’s largest provincial economy, with an economy larger and more diverse than that of Saudi Arabia. In 2008 its GDP reached ∼D 357 billion, with roughly 50% of this coming from industry. Guangdong’s legacy within China is pioneering the reform and development of China’s economy. The current provin-
∗ Corresponding author. Tel.: +86 20 89023147. E-mail address: [email protected] (D. Zhou). 1750-5836/$ – see front matter © 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijggc.2010.09.011
cial government is keen to maintain this position of leadership and is actively promoting the importance of scientific development in upscaling the provincial economy. Guangdong’s conceptual model for low carbon economic development emphasizes the adjustment of industrial structure, increasing energy saving and efficiency, and deploying renewable and nuclear energy. While CCS is not currently featured in the roadmap of low-carbon economic development in Guangdong, there are needs for CCS. Guangdong’s electricity industry has been highly involved in the recent wave of promoting new IGCC plants, with three under consideration for Guangdong at present, including two of 1200 MW. To date there has been no consideration on how to deal with the CO2 captured in these plants. According to the USDOE formula for CO2 emission (USDOE, 2008a), a 1200 MW plant will emit ∼6 Mt CO2 annually, which would require 6 sites that matched the injection rate at the North Sea Sleipner West field if it was to be stored underground. In late 2009 to early 2010 we conducted a study on the CO2 storage capacity in the Sanshui Basin onshore Guangdong and the Pearl River Mouth Basin (PRMB) offshore. This is the first CCS-related research project in the Guangdong Province, and is also the first to take place in South China. The study has shown that the capacity onshore Guangdong is very small, while the capacity offshore
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is significant. In this paper the preliminary assessment of the CO2 storage capacity in the PRMB is presented. 2. Methodology of assessment Four classes of CO2 storage capacity, i.e. the theoretical, effective, practical, and matched capacity in the order of increasing accuracy, were defined by Carbon Sequestration Leadership Forum (CSLF) (Bachu et al., 2007). The theoretical capacity is the maximum upper limit for storage potential. It assumes that the system’s entire capacity to store CO2 in pore space, or dissolved at maximum saturation in formation fluids, or adsorbed at 100% saturation in the entire coal mass, is accessible and utilized to its full capacity. The effective capacity is similar to theoretical capacity, but with a number of geological and engineering limitations applied. In practice the effective capacity is obtained by the theoretical capacity multiplied by a storage efficiency factor that reflects the percentage of pore volume that CO2 is expected to actually contact. In this study, the effective capacities are assessed, and the data were collected from published sources. There are two types of storage sites in the PRMB: deep saline formations and oil and gas reservoirs. The deep saline formations are the porous rocks at depths below 800 m and with formation water having total dissolved solids > 10 000 ppm (USDOE, 2008b). The USDOE methodology (USDOE, 2008b) was used in the capacity calculation for saline formations. In this scheme the entire aquifer rather than only traps is considered. The storage capacities are given by: MCO2 = A × h × ϕ × CO2 × E
(1)
where A is the area of basin or region to be assessed, h is the gross thickness of the saline formations to be assessed and E is the storage efficiency factor. The estimation of CO2 storage capacity in oil and gas reservoirs follows the CLSF scheme (Bachu et al., 2007), which is based on the assumptions that the volume previously occupied by the produced hydrocarbons becomes available for CO2 storage, and that CO2 will be injected into depleted oil and gas reservoirs until the reservoir pressure is brought back to the original reservoir pressure. The effective storage capacity in each reservoir is calculated on the basis of its recoverable hydrocarbon reserves, its reservoir properties and in situ CO2 characteristics by the formula:
MCO2t = CO2r × Rf ×
OOIP − Viw + Vpw × E Bf
(2)
where MCO2t is the estimated storage capacity in million ton, CO2r is the density of CO2 in the reservoir, OOIP is the volume of original oil in place at standard temperature and pressure, Rf is the recovery factor, Bf is formation volume factor, Viw and Vpw are injected and produced water, and E is the storage efficiency factor. Bachu (2008) pointed out that the CSLF and USDOE methodologies are computationally equivalent. The capacity given by Eq. (1) should also be the effective capacity, as the effective coefficient E is included. In addition, the “saline formations to be assessed” in (1) is the formation that meets the requirement for CO2 storage, thus we think the h in (1) should be the formation thickness times the net/gross ratio, rather then being the gross formation thickness. These understandings will be followed in this study. 3. Geography and geology 3.1. Geography The Pearl River Mouth Basin (PRMB), 111◦ 20 –118◦ 0 E and 18◦ 30 –23◦ 00 N, is a NEE-elongated basin, 900 km long and
309
115–280 km wide, with total area of nearly 200 000 km2 . The basin resides offshore Guangdong Province in the shelf (∼68% of total area) and the slope of the northern South China Sea, with water depth ranging from 50 m to over 2000 m (Fig. 1). It is the largest sedimentary basin in the northern South China Sea, and is the offshore basin most proximal to the industrialized area of the Pearl River Delta in Guangdong. 3.2. General geology Geologically the PRMB is an extensional basin in the passive continental margin of the northern South China Sea. It was formed by rifting of the South China Block in the Paleogene and subsequent subsidence in the Neogene. Lithofacies in the basin was generally continental in the Paleogene and marine in the Neogene. The basement of the PRMB is composed of Mesozoic granites and secondary Paleozoic metamorphic rocks. Above the basement there are 4 depressions aligned in two NEE-running belts: The Zhu3 and Zhu-1 depressions in the northern depression belt, and the Zhu-2 and Chaoshan depressions in the Southern depression belt (Fig. 1). The two depression belts are separated by a NEE Central Uplift belt. In vertical sections the structures are composed of the lower section of Paleogene rifts (half-grabens and grabens) and the upper section of Neogene post-rift downwarps (Fig. 1). NEE faults often controlled the orientation of the depressions, while NWW-EW faults controlled the distribution of sags and traps. NW-running large crustal or lithospheric faults cut the depression belts into blocks. Cenozoic volcanism occurred episodically from the Early Eocene to Quaternary (Liang and Li, 1992). They are mostly acid and intermediate volcanic clasts, with mafic and intermediate lavas in the Paleogene, and basaltic lavas in the Neogene and Quaternary. Except for the Quaternary basalts these usually are small in size and in the vicinity of large NW faults. Earthquake activity has been sparse and weak in major portions of the PRMB. There was only one M ≥ 6 earthquake occurred in the western central uplift belt (September 1931, M6.75). 3.3. Stratigraphy and paleo-geography The PRMB is filled with Cenozoic sediments with a maximum thickness of >6 km in shelf areas and >14 km in slope areas (Chen et al., 2003; Zhou et al., 2009). The stratigraphic column of the PRMB is shown in Fig. 2. During the Paleogene the PRMB received fluvial and lacustrine clastic sedimentation in rifted basins and incised valleys. In Neogene the PRMB subsided to a marine environment. In general the sealevel has been rising (Qin, 2002), opposite to the global trend of sealevel dropping in this period. Paleo-Pearl River system supplied large quantity of terrigenous sands and muds to the basin. Frequent fluctuation of sealevel has resulted in cyclic sedimentations all through time, forming multiple deltas in the north and sequences of marine strata in the south. 3.4. Petroleum geology Major source rocks in the PRMB are the lacustrine dark mudstones of Middle Eocene Wenchang Formation and the coal-bearing sequences in Late Eocene to Early Oligocene Enping Formation. The dark mudstones in the Miocene Zhuhai and Zhujiang Formations are secondary source rocks (Cai, 2005). There are three source-reservoir-seal assemblages in the PRMB: (1) the self-contained Paleocene-Eocene continental assemblage which occurs sparsely in the northern PRMB; (2) the welldeveloped Paleogene-Eocene-Miocene assemblage with sources in continental Paleogene formations locally within sags, reservoirs in
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Fig. 1. Simplified geological map and cross-section AA of the Pearl River Mouth Basin. Data points used in the assessment are superimposed.
marine Zhuhai and Zhujiang Formations, and caprocks in upper Zhujiang Formation; (3) the Miocene marine assemblage with sources in Zhujiang Formation, reservoirs in Hanjiang Formation, and caprocks in upper Hanjiang Formation. Structural traps in sandstone and the cavities in carbonate buildups are the principal reservoir types in the PRMB. Oil fields have been found mainly in the Zhu-1 depression along the edges of the Central Uplift belt. Most oil fields are small, except the LH11-1 field with proved reserves over 100 Mt (0.73 billion barrels) (Zhu et al., 2008). In recent years, large gas fields have been discovered in the Zhu-3 and Zhu-2 depressions.
4. Capacity assessment for saline formations 4.1. Geological conditions for CO2 storage Regional seals are the mudstone layers in Miocene Hanjiang and Zhujiang formations. In the Zhu-1 depression the Hanjing Formation contains 400–600 m of mudstones, 70–80% of the formation thickness; while in the Zhu-2 depression these numbers are 700–800 m and 80–90%. The Zhujiang Formation contains both seals and reservoirs. Its delta front and transgressional mudstones have 57–90% of the formation thickness in most part of the basin (Cai, 2005). As the mudstones in the Hanjiang Formation form the uppermost regional seal, in this assessment the strata above the Hanjiang Formation will not be considered. Frequent cyclic sealevel changes in the PRMB produced a large amount of local seals. For example, the upper member of the Zhujiang Formation in the Wenchang A Sag of the Zhu-3 depression, which contains 42–75% mudstone with thickness of 191–655 m (Cai, 2005).
Potential reservoirs in the PRMB include deltaic, channel, transgressional, slope and low-stand fan sandstones, and reefal and platform carbonates. Sandstones are rich in transitional facies, decreases in neritic facies and poor in bathyal and abyssal facies (Gong and Li, 1997). Sandstone reservoirs have been found mostly in Zhuhai, Zhujiang, and Hanjiang formations, and possibly in the fluvial sandbars of the Enping Formation. Carbonate reservoirs are found in Miocene formations and mainly in the Dongsha Uplift. In the Late Oligocene Zhuhai Formation oil accumulations of 8 m and 4 m thick have been found, with sandstone porosity of 10–16% and permeability of 4–85 mD (Cai, 2005). The Miocene Zhujiang and Hanjiang Formations contains reservoirs of mainly delta-front sandstones, with porosity of 16.3–29.6% and permeability of 188–1732 mD. Among these the best reservoir was found in the Hanjiang Formation with a thickness of 8 m, porosity of 29.6%, and permeability of 1732 mD (Cai, 2005). Carbonate reservoirs in the PRMB have a porosity range of 9–28% and a permeability range of 7–1365 mD. The LH11-1 oil field has average porosity of 23% and permeability of 471.5 mD. Well LH41-1 has an average porosity of 23% and permeability of 471.5 mD. The LF15-1 limestones have an average porosity of 26% and a permeability range of 7–203 mD. Well LF22-1-1 has a porosity of 29% and a permeability of 54 mD (Cai, 2005).
4.2. Data sources A GIS-based database was built for the Cenozoic formations in the PRMB. The data were compiled from published sources, including those from 31 wells. As available well data are insufficient for depth and isopach mapping, published 23 regional seismic profiles (depth converted) and low-resolution isopach maps (e.g., the three
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Fig. 2. Stratigraphic column of the Pearl River Mouth Basin.
isopach maps from Gong and Li, 1997, as well as the isopach maps of the Baiyun Sag from Zhou et al., 2009) have been used to provide additional data points. Resulting isopach maps are used for assessing the effective capacity (see Fig. 1 for data point distribution). Water depths are from the Geographic Map of the South China Sea published by South China Sea Institute of Oceanology (SCSIO) in 1983.
4.3. Formation volumes For this assessment the Cenozoic formations of the PRMB are divided into three super sequences: Paleogene (Wenchang, Enping, and Zhuhai Formations), Early-Middle Miocene (Zhujiang and Hanjiang Formations), and Late Miocene to Holocene (Yuehai, Wanshan Formations and Quaternary). On a GIS platform, their isopach maps were constructed (Fig. 3), and their gross volumes and the volumes below 800 m from the seafloor were calculated (Fig. 4 and Table 1). In addition, volumes of the depth range 800–2500 m, as suggested
to be a positive indicator by Chadwick et al. (2008), were also calculated. This reduced the volume by 15% for the Lower-Middle Miocene and by as much as 65% for the Paleogene (Table 1).
4.4. Lithological parameters Published data on the net/gross ratio, the porosity, and the permeability of the rocks in the PRMB are sparse and thus have to be estimated based on several sets of incomplete or indirect data. Stratigraphic columns from 6 wells in the Zhu-1 and Zhu-2 depressions have been used to measure the net/gross ratio. Simple averages of net/gross ratios in these wells are 0.36, 0.49, and 0.64 for the super layers of the Paleogene, Early to Middle Miocene, and Upper Miocene to Holocene, respectively. Data of oil-tested sandstone segments from 11 wells and of sampled segments from 7 wells of the eastern PRMB (east of longitude 113◦ E) are published in Tables 5-2, 5-3, and 5-4 of Chen et al. (2003). The average values weighted by segment thickness are computed.
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Fig. 3. Isopach maps of the Pearl River Mouth Basin. (a) Sea water, (b) Upper Miocene to Quaternary, (c) Lower-Middle Miocene, and (d) Paleogene. Superimposed white lines show the boundaries of depressions and sags. Table 1 Areas and volumes of the super sequences in the Pearl River Mouth Basin. Super sequence
Area (km2 )
Depth of top (m)
Thickness (m)
Volume (km3 ) Gross
−800 m
−800 to 2500 m
Paleogene L.-M. Mioc. U. Mioc. To Q Total
197 290 174 856 30 185
0–2600 0–700 0
0–1700 0–2500 0–700
165 773 235 228 114 490 515 491
163 149 184 459 6242 353 850
56 924 157 288 6242 220 454
Petroleum systems have been delineated in the eastern PRMB, and their parameters are listed in Table 8-2 of Chen et al. (2003). Based on these data, the parameters of seals and reservoirs in the formations of the eastern PRMB are calculated by thicknessweighted averaging (Table 2). The parameters compiled from the above-mentioned sources are compared in Table 3. The porosities and permeabilities are reasonably consistent, but the net/gross ratio varies significantly. In this capacity calculation, the net/gross ratios from 6 wells were used.
4.5. CO2 density The density of CO2 varies with formation temperature and pressure (Bachu, 2003). The PRMB is in general in a normal pressure system. Overpressure is observed locally in deep-burring (>4600 m) Wenchang and Enping formations (Gong and Li, 2004). Thus in this paper we use the hydrostatic pressure to approximate the formation pressure. The formation temperature depends on the surface temperature and geothermal gradient. The seafloor temperature of the
Table 2 Parameters of oil-tested sandstone segments from the wells in eastern PRMB (thickness-weighted averages based on tables 5-2, 5-3, and 5-4 in Chen et al., 2003). Formation
Porosity (%) Range
Zhujiang Zhuhai Enping
13.3–23.9 2.3–22.7 0.7–22.0
Permeability (mD) Ave. 19.9 16.8 10.3
Range 20.2–2027.9 3.5–913 0.03–95
Net/gross ratio (%)
# of wells
92.6 87.8 No data
10 11 14
Ave. 916.5 318.0 7.0
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Fig. 4. Isopach maps of the formation below 800 m from the seafloor in the Pearl River Mouth Basin (a) Upper Miocene to Quaternary, (b) Lower-Middle Miocene, and (c) Paleogene. Superimposed white lines show the boundaries of depressions and sags.
northern SCS varies with water depth as shown in the inset of Fig. 5. The thermal gradient varies across the PRMB in the range of 26.2–50.6 ◦ C/km. A contour map of geothermal gradients in the PRMB was compiled based the data of 75 wells (Fig. 5) from Rao
and Li (1991). The gradient is in general lower than 35 ◦ C/km in the shallow-water Zhu 1 depression, while higher in the deep-water Zhu 2 and shallow-water Zhu 3 depressions. Accordingly we divide the basin into three regions (Fig. 5): the N-PRMB with relatively
Fig. 5. Contour map of geothermal gradient of the Pearl River Mouth Basin compiled based on drill hole measurements given in Rao and Li (1991) with minor additions. Thick dashed line divides the basin into 3 districts for constructing CO2 density curves. Numbers show the average gradient (in ◦ C/km) for individual sags. Inset is a curve of seafloor temperature in northern South China Sea measured by SCSIO.
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Table 3 Comparison of the reservoir parameters compiled from various data sources. Porosity (%) Hanjiang Zhujiang
Zhuhai
Enping a
Ave. 33.1 16.3–29.6a Ave. 19.9 20.8 16.3–29.6a Ave. 16.8 17.0 4.5–16.8 Ave. 10.3
Permeability (mD) a
188–1732 Ave. 916.5 624.1 188–1732a Ave. 318.0 431 4.4–2434 Ave. 7.0
Net/gross (%)
Data source
68.1 10–30 92.6 53.3 10–43 87.8 45.6
Chen et al. (2003) Cai (2005) Table 3 Chen et al. (2003) Cai (2005) Table 3 Chen et al. (2003) Cai (2005) Table 3
Table 4 CO2 density versus formation depth for the N-, S-, and SW-Pear River Mouth Basin. N-PRMB ◦
Parameters for combined Zhujiang and Hanjiang formations.
Therm. grad. ( C/km) Seafloor temp. (◦ C) Depth (m) 800–1000 1000–1200 1200–1400 1400–1600 1600–1800 1800–2000 2000–2200 2200–2500 2500–3000 3000–4600 4600–6600
S-PRMB
34 20 CO2 density (kg/m3 ) 288.9 386.3 460.1 504.5 528.5 543.6 556.0 565.7 574.5 589.0 599.5
SW-PRMB
40 8
40 20
334.3 422.7 467.6 495.6 513.4 524.4 530.2 532.4 535.4 542.8 548.4
267.6 348.5 414.3 455.1 478.7 494.6 507.1 519.0 531.0 545.0 555.5
4.6. Storage efficiency factor It is beyond the ability of this paper to estimate the storage efficiency factor E for the PRMB. The USDOE Subgroup through Monte Carlo simulations obtained a statistical distribution of E for deep saline aquifers with P15, P50, and P85 probability level at E = 0.01 0.024, and 0.04 respectively (Bachu, 2008). Recent thematic study (IEAGHG, 2009) suggests the overall mean value (P50) of E for all lithologies being 0.026 at the formation level (Wildgust, 2010). Combining these two results, in this paper we use E = 0.026 for mean and E = 0.01 and 0.04 for P15 and P85 probability level, respectively. 4.7. Capacity calculation On a GIS platform the effective capacity for CO2 storage in the saline formations in the Pearl River Mouth Basin is estimated using Eq. (1). In addition to the general assumptions stated in Section 2, the following assumptions are made: Fig. 6. Curves of CO2 density versus depth for N-, S-, and SW- Pearl River Mouth Basin compiled based on the data in Fig. 5, parameters in Table 1, and values in Table 45 of Span and Wagner (1996). Curves of “Typical” and “Hot” regions from Chadwick et al. (2008) are also shown for comparison.
high seafloor temperature and low thermal gradient, the S-PRMB with relatively low seafloor temperature and high thermal gradient, and the SW-PRMB with both high seafloor temperature and high thermal gradient. Curves of CO2 density versus formation depth were constructed respectively for each region (Fig. 6) based on Span and Wagner (1996). In Fig. 6 selected curves from other publications are also presented for comparison. The increase rate of CO2 density with depth in the PRMB is much slower than the 35 ◦ C/km curve of GeoCapacity (2009), and in between the “Typical” and “Hot” curve s of Chadwick et al. (2008).
(1) The Middle Miocene Hanjiang Formation forms the upper regional seal, and the delta-front and transgressional mudstone in the Zhujiang Formation form the lower regional seal; (2) CO2 reservoirs mainly reside in the sandstones and limestones of the Early Miocene Zhujiang and Zhuhai Formations, and secondarily in Middle Miocene Hanjiang Formation and in Oligocene Enping Formation; (3) Because no data are available for the Wenchang Formation, its parameters are assumed to be the same as those of the Enping Formation. Therefore, only the Paleogene (Wenchang and Enping) and Lower-Middle Miocene (Zhuhai, Zhujiang, and Hanjiang) formations are considered in the capacity calculation. Eq. (1) is used in the calculation with mean of E = 0.026, and 15% and 85% probability level of E = 0.01 and 0.04, respectively.
Table 5 Parameters and capacity assessments for the saline formations in the Pearl River Mouth Basin. Parameter Volume below 800 m V (m3 ) Net/gross ratio R Average porosity ϕ CO2 density CO2 (t/m3 ) Effective capacity (Gt), >800 m
Effective capacity (Gt), 800–2500 m
L.-M. Miocene
Paleogene
Total
E = 0.01 E = 0.026 E = 0.04 E = 0.01 E = 0.026 E = 0.04
187 000 × 109 0.5 0.2 As in Table 4 86 225 345 71 184 284
164 000 × 109 0.37 0.1 As in Table 4 32 83 128 10 26 40
118 308 473 81 210 324
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As the CO2 density varies with depth, for each of the 3 districts in Fig. 5 the formation body was cut into horizontal layers, and the average CO2 densities for individual depth layers were read from the curves in Fig. 6 and listed in Table 4. The volumes of these layers in each super sequences in the 3 districts were calculated on a GIS platform. Other parameters and estimations are listed in Table 5. The mean, P15 and P85 probability level estimations of the effective CO2 storage capacities in saline formations of the PRMB are 308 Gt, 118 Gt, and 473 Gt, respectively.
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Table 6 Parameters and capacity assessments of CO2 in oil and gas fields of the Pearl River Mouth Basin. Parameter
Value
OOIP (t) Oil density (t/m3 ) Recovery rate Rf Volume factor Bf CO2 density (t/m3 ) Efficiency factor E Capacity (t)
0.9 × 109 0.9 0.5 1.03 0.566 0.25 0.06 × 109
5. Capacity assessment of oil and gas fields Up to 2009 there have been ∼200 wells drilled in the PRMB, and ∼40 oil and gas fields have been found, with oil production over 10 million m3 (63 million barrels) since 1996. The estimations of geological resources in the PRMB are 2.3–3.2 billion tons (17–23 billion barrels) oil equivalent (MLR, 2008), and proved reserve (OOIP) is ∼0.9 billion tons (6.5 billion barrels) oil equivalent (informal data). The capacity of CO2 in oil and gas fields of the PRMB is estimated using the Eq. (2). As there has been no water flooding in the PRMB, Viw and Vpw are zero and (2) becomes:
MCO2t = CO2r × Rf ×
OOIP Bf
×E
The oil fields in the PRMB have a high recovery rate, and a conservative estimation of Rf = 0.5 is used in our calculation. The crude oil from the fields in the PRMB is light with average density of ∼900 kg/m3 and volume factor Bf = 1.02–1.05. The oil fields reside mostly in the Zhu 1 depression and within 2000–3000 m depth, only the LH11-1 field in 1252–1330 m depth (Chen et al., 2003; Zampetti et al., 2005). As the oil/gas reserves for individual fields are not publicly available, we do not know the reserve values for the 3 districted in Fig. 5. Thus we have to calculate for the entire basin, using the CO2 density of 565.7 kg/m3 , which is the CO2 density at 2200–2500 m depth in the N-PRMB (Table 4). There are very few studies of E for oil and gas fields. A study by Bachu and Shaw (2005) in western Canada estimated the capacity reduction in oil fields for strong aquifer as 0.19–0.75 and in average 0.5, and for mobility and
other factors as 0.5. Thus E = 0.5 × 0.5 = 0.25, which is used in this paper. The parameters and estimated effective capacity are listed in Table 6. The estimated effective storage of CO2 in the oil and gas fields in the PRMB is 0.06 Gt. This is likely an underestimated number because the proved reserve is used in the estimation. As the basin is still in the exploration stage, the un-proved reserve may be large. For example, the newly estimated resource of the Zhu-1 depression alone reaches 5.9 billion tons oil equivalent (Shi et al., 2009), and new gas fields have been discovered in the deepwater Baiyun Sag of the Zhu-2 depression (Pang et al., 2007).
6. Storage prospectivity At this preliminary stage, major concerns for assessing the storage prospectivity are the distribution of reservoirs and seals, the distance from major emission sources (the Pearl River Delta), the depth and size of possible reservoirs, and the possibility of CO2 -EOR. Under these criteria, the most promising area for CO2 storage in saline formations is the northern portion of the Lufeng and Hanjiang sags in the Zhu-1 depression (Fig. 7). In this area the Lower and Middle Miocene formations are thick and with good reservoir-seal assemblages (Fig. 4). A number of structural traps in the area have been proved dry, among which the large ones may be the first candidates for CO2 storage. The distance from Hongkong to this area is between 150 and 300 km.
Fig. 7. Map showing the distribution of oil/gas fields in the Pearl River Mouth Basin. The promising area for CO2 storage in saline formations is indicated by red polygon. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)
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The northern Xijiang Sag to the west is relatively dry and lies even closer to the industrialized Pearl River Delta, but the sag has been filled with large quantity of mostly sandy sediments from the paleo-Pearl River system, and the sealing condition there is poor. Within the promissing areas, reservoirs in the Middle Super sequence (Lower and Middle Miocene) deserve special attention, because they contain the most abundant, thick, and high quality sandstone or carbonate formations, covered by well developed mudstone seals. There may be some sandstone reservoirs in the Lower Super Layer (Paleogene), but those continental formations are usually deeper, less understood, and with poorer quality (lower porosity and permeability due to diagenesis) and smaller capacity. These make it a lower priority at this stage. The storage prospectivity in oil and gas fields in the PRMB is limited. Oil fields have been found in southern Huizhou and Lufeng sags, southwestern Dongsha Uplift, northern Panyu Low Uplift, southern Enping Sag, and the southeastern Wenchang Sag (Fig. 7). Most fields are small but distributed as clusters and contain high quality light oil. However the capacities in these oil fields are insufficient for large scale CO2 storage when compared to the size of emission sources. The largest LH11-1 field has a proved reserve >100 Mt (>0.7 billion barrels) in porous carbonate reservoirs. It is 220 km SE of Hongkong. The potential of CO2 -EOR in the PRMB is probably low, as the oil fields have high recovery rate (over 50%) in general, and strong water invasion occurs automatically during the production. The gas fields so far discovered are usually large. For example, the newly discovered LW3-1, LH34-2, and LH29-1 gas fields have a proved reserve >100 × 109 m3 each, and the PY30-1 gas field has proved reserve of 30 × 109 m3 and started production in early 2009. The produced gas has been transported to Zhuhai City through underwater pipelines. A disadvantage for CO2 storage is that these gas fields reside in deepwater areas, where the cost of drilling and infrastructure are likely to be much higher. These fields have the potential to be used as storage sites for CO2 only in a very long term.
7. Conclusions For the saline formations deeper than 800 m below seafloor in the Pearl River Mouth Basin, the estimated effective capacity for CO2 storage is 308 Gt in average, with P15 and P85 probability level of 118 Gt and 473 Gt. If only the formations shallower than 2500 m below the seafloor are considered, the estimated effective capacity is reduced by 27%, 210 Gt in average, with P15 and P85 probability level of 81 Gt and 324 Gt. About 73% of the effective capacity resides at depth <2500 m, and 88% of the effective capacity resides in Lower-Middle Miocene formations. The abovementioned effective capacity includes that in oil and gas fields, which is very small (0.06 Gt). But this is a conservative estimate as newly proved and unproved fields are not included. According to this assessment, the deep saline formations in the PRMB are able to storing 190 years of total CO2 emission from major point sources in Guangdong, if 10% of the effective storage capacity may be used and if the total emission keeps the 2006 level of 160 Mt/a (Bai et al., 2006). These estimates are of high uncertainty because they were obtained based on published incomplete data, and with the assumptions that all the formations are saline and all the pore space may be filled with injected CO2 . Compared with the estimates for other areas in the world, the estimated capacities for the saline formations in the PRMB are larger than those for the California state
(84–311 Gt) (USDOE, 2008c), but the estimated effective capacity for oil and gas fields in the PRMB is less than 1/100 of that for California (7.7 Gt) (USDOE, 2008c). The advantages common to all offshore storage of CO2 are applicable to the PRMB, such as no interference with population, agriculture, and industry, no damage to groundwater, and in technical issues such as the potential to manage pressure within the geological formation (Schrag, 2009). The disadvantages of the PRMB for CO2 storage are also common to all offshore storage sites, mainly the higher cost of the infrastructures and engineering operations compared with the onshore storage. But overall, storing CO2 in geological formations offshore may be easier, safer, and less expensive (Schrag, 2009). In addition, the advantages of the Pearl River Mouth Basin for CO2 storage are: (1) The mudstones in the Late Miocene Hanjiang Formation and the upper Middle Miocene Zhujiang Formation form excellent regional seals. Frequent sealevel fluctuation in Neogene resulted in multi-layers of local seals. Sandstones and limestones are wide spread in the Neogene and upper Paleogene formations, forming promising reservoirs. Multiple seal-reservoir assemblages have been proved by hydrocarbon exploration. (2) Extensive data and infrastructure (wells, pipelines, etc.) have been accumulated during a long period of exploration and may be used for CO2 storage. (3) Proximal to major CO2 point sources in the Pearl River Delta. As there is little capacity for CO2 storage in onshore Guangdong, the high potential for CO2 storage in the Pearl River Mouth Basin is even more important to the Guangdong Province. As the hydrocarbon exploration is still going on in the PRMB, the initial stage of CO2 storage should be concentrated on known dry traps in areas where the hydrocarbon source rocks are less developed. In consideration of the distribution of reservoirs and seals, the distance from major emission sources in the Pearl River Delta, and the depth and size of possible reservoirs, the promising areas for CO2 storage should be considered first are the Zhuhai and Zhujiang formations in the northern Lufeng and Hanjiang sags of the Zhu-1 depression. A detailed study on the dry traps in these areas should be conducted to identify target traps and their capacity. Additional data such as seal maps, reservoir maps, pressure, temperature, CO2 density, irreducible water saturation, etc. should be collected to make more accurate estimation for the CO2 storage capacity in these traps. Acknowledgements The study is funded by the Tactical Fund for Low Carbon and High Growth and administered by the UK Foreign & Commonwealth Office. The authors are indebted to Wayne Ives, Bill Senior, Jonathan Pearce, as well as Stefan Bachu and anonymous reviewers for their valuable suggestions on improving the manuscript. References Bachu, S., 2003. Screening and ranking of sedimentary basins for sequestration of CO2 in geological media. Environmental Geology 44 (3), 277–289. Bachu, S., 2008. Comparison between Methodologies Recommended for Estimation of CO2 Storage Capacity in Geological Media – Phase 3 CSLF Task Force on CO2 Storage Capacity Estimation and the USDOE Capacity and Fairways Subgroup of the Regional Carbon Sequestration Partnerships Program, p. 21. Bachu, S., Shaw, J.C., 2005. CO2 storage in oil and gas reservoirs in western Canada: effect of aquifers, potential for CO2 -flood enhanced oil recovery and practical capacity. In: Proceedings of the 7th International Conference on Greenhouse Gas Control Technologies (GHGT-7), September 5–9, 2004, Vancouver, Canada, pp. 361–370.
D. Zhou et al. / International Journal of Greenhouse Gas Control 5 (2011) 308–317 Bachu, S., Bonijoly, D., Bradshaw, J., Burruss, R., Christensen, N.P., Holloway, S., Mathiassen, O.-M., 2007. Estimation of CO2 Storage Capacity in Geological Media – Phase 2 Carbon Sequestration Leadership Forum (CSLF), p. 43. Bai, B., Li, X., Yang, Y., Zhang, Y., 2006. Preliminary study on CO2 industrial point sources and their distribution in China. Chinese Journal of Rock Mechanics and Engineering 25 (Suppl. 1), 2918–2923 (in Chinese). Cai, Q., 2005. Oil and Gas Geology in China Seas. Ocean Press, Beijing, 406 pp. (in Chinese). Chadwick, A., Arts, R., Bernstone, C., May, F., Thibeau, S., Zweigal, P., 2008. Best practice for the storage of CO2 in saline aquifers. Observations and guidelines from the SACS and CO2 STORE projects. British Geological Survey, 277. Chen, C., Shi, H., Xu, S., Chen, X., et al., 2003. Formation Conditions of Tertiary Oil/Gas Reservoirs in Pearl River Mouth Basin (East). Science Press, Beijing, 266 pp. (in Chinese). GeoCapacity, 2009. Capacity Standards and Site Selection Criteria. WP4 Report D26, 48 pp. Gong, Z., Li, S., 1997. Basin Analysis and Oil/Gas Accumulation in the Northern Margin of South China Sea. Science in China Press, Beijing, 510 pp. (in Chinese). Gong, Z., Li, S., 2004. Dynamic Research of Oil and Gas Accumulation in Northern Marginal Basins of South China Sea. Science in China Press, Beijing, 339 pp. (in Chinese). IEAGHG, 2009. Development of Storage Coefficients for Carbon Dioxide Storage in Deep Saline Formations, 118 pp. Liang, H., Li, P., 1992. Cenozoic magmatism in the Pearl River Mouth Basin. Guangdong Petroleum 16, 81–103 (in Chinese). MLR, PR China, 2008. Report on a New Round of National Oil and Gas Resource Assessment. Ministry of Land and Resources, PR China (in Chinese). Pang, X., Chen, C., Peng, D., Zhu, M., Shu, Y., He, M., Shen, J., Liu, B., 2007. Sequence stratigraphy of Pearl River Deep-water Fan System in the South China Sea. Earth Frontiers 20 (7), 220–229.
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Qin, G., 2002. Late Cenosoic Sequence Stratigraphy and Sealevel Changes in Pearl River Mouth Basin, South China Sea. China Offshore Oil and Gas (Geology) 16 (1), 1–18 (in Chinese). Rao, C., Li, P., 1991. Study of heat flow in Pearl River Mouth Basin. China Offshore Oil and Gas (Geology) 5 (6), 7–18 (in Chinese). Schrag, D.P., 2009. Storage of Carbon Dioxide in Offshore Sediments. Science 325, 1658. Shi, H., Zhu, J., Jiang, Z., Shu, Y., Xie, T., Wu, J., 2009. Hydrocarbon resources reassessment in Zhu I depression, Pearl River Mouth basin. China Offshore Oil and Gas 21 (1), 9–14. Span, P., Wagner, W., 1996. A new equation of state for carbon dioxide covering the fluid region from the triple-point temperature to 1100 K at pressures up to 800 MPa. Journal of Chemical Reference Data 25 (6), 1509–1596. USDOE, 2008a. CO2 Stationary Source Emission Estimation Methodologies Summary, Appendix A, Carbon Sequestration Program, 15 pp. USDOE, 2008b. Methodology for Development of Geologic Storage Estimates for Carbon Dioxide, Appendix B. Carbon Sequestration Program, pp. 18. USDOE, 2008c. Stationary Source and Geologic Storage Estimates for Carbon Dioxide by State/Province, Appendix C, Carbon Sequestration Program, 10 pp. Wildgust, N., 2010. Storage Capacity Coefficients (2009-13). IEAGHG Greenhouse Issues (96), 5. Zampetti, V., Sattler, U., Braaksma, H., 2005. Well log and seismic character of Liuhua 11-1 Field, South China Sea; relationship between diagenesis and seismic reflections. Sedimentary Geology 175, 217–236. Zhou, D., Sun, Z., Liao, J., Zhao, Z., He, M., Wu, X., Pang, X., 2009. Filling History and Post-Breakup Acceleration of Sedimentation in Baiyun Sag, Deepwater Northern South China Sea. Journal of Earth Science 20 (1), 160–171. Zhu, W., Mi, l., Gao, L., Gao, Y., 2008. A review of China offshore hydrocarbon exploration in 2007. China Offshore Oil and Gas 20 (1) (in Chinese).
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International Journal of Greenhouse Gas Control journal homepage: www.elsevier.com/locate/ijggc
A preliminary assessment on CO2 storage capacity in the Pearl River Mouth Basin offshore Guangdong, China Di Zhou ∗ , Zhongxian Zhao, Jie Liao, Zhen Sun CAS key Laboratory of Marginal Sea Geology, South China Sea Institute of Oceanology, 164 West Xingang Road, Guangzhou, China
a r t i c l e
i n f o
Article history: Received 17 May 2010 Received in revised form 4 September 2010 Accepted 25 September 2010 Available online 25 October 2010 Keywords: Carbon dioxide Capture and Storage (CCS) CO2 storage capacity Pearl River Mouth Basin Guangdong Province South China Sea
a b s t r a c t Guangdong has China’s highest GDP of any province and actively advocates low-carbon development. At present, Guangdong’s low-carbon roadmap emphasizes the adjustment of industrial structure, increased energy saving and efficiency, and renewable and nuclear energy, while CCS is not featured. This is partially due to the geographical gap in the existing body of research on CCS in China, as to date no substantial research on CCS has taken place in the regions south of the Yangtze River, including Guangdong. This paper presents the partial outcome of the first CCS-related research in Guangdong, which is aiming for a preliminary assessment on the effective CO2 storage capacity in the Pearl River Mouth Basin (PRMB) offshore Guangdong. As the storage capacity onshore Guangdong is limited as shown by a parallel study, the offshore sedimentary basins deserve particular attention. The PRMB is the largest sedimentary basin in the passive margin of the northern South China Sea, with a total area of nearly 200 000 km2 and maximum sediment thickness of over 14 km. Based on published data, geological conditions and parameters for CO2 storage are analyzed, volumes of potential formations are calculated on a GIS platform, and the storage capacity is calculated according to CSLF and USDOE formulations. The estimated effective storage capacity is 308 Gt in deep saline formations, including 0.06 Gt in oil and gas fields. This capacity is sufficiently large for storaging the CO2 emitted from the major point sources in Guangdong in many decades. Promising areas are suggested for further investigations. © 2010 Elsevier Ltd. All rights reserved.
1. Introduction Carbon dioxide Capture and Storage (CCS) technology is the most efficient technological option for greenhouse gas mitigation that allows continued use of fossil fuels. China is undertaking a range of technical research and development projects on CCS, including the national fundamental research and high-tech programs, as well as a large number of international programs. There is a geographical gap in the existing body of research on CCS in China. To date, all of the major CCS projects in China have focused on the regions north of the Yangtze River, with no substantial research having taken place in China’s wealthy manufacturing provinces in the south. Guangdong is China’s largest provincial economy, with an economy larger and more diverse than that of Saudi Arabia. In 2008 its GDP reached ∼D 357 billion, with roughly 50% of this coming from industry. Guangdong’s legacy within China is pioneering the reform and development of China’s economy. The current provin-
∗ Corresponding author. Tel.: +86 20 89023147. E-mail address: [email protected] (D. Zhou). 1750-5836/$ – see front matter © 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijggc.2010.09.011
cial government is keen to maintain this position of leadership and is actively promoting the importance of scientific development in upscaling the provincial economy. Guangdong’s conceptual model for low carbon economic development emphasizes the adjustment of industrial structure, increasing energy saving and efficiency, and deploying renewable and nuclear energy. While CCS is not currently featured in the roadmap of low-carbon economic development in Guangdong, there are needs for CCS. Guangdong’s electricity industry has been highly involved in the recent wave of promoting new IGCC plants, with three under consideration for Guangdong at present, including two of 1200 MW. To date there has been no consideration on how to deal with the CO2 captured in these plants. According to the USDOE formula for CO2 emission (USDOE, 2008a), a 1200 MW plant will emit ∼6 Mt CO2 annually, which would require 6 sites that matched the injection rate at the North Sea Sleipner West field if it was to be stored underground. In late 2009 to early 2010 we conducted a study on the CO2 storage capacity in the Sanshui Basin onshore Guangdong and the Pearl River Mouth Basin (PRMB) offshore. This is the first CCS-related research project in the Guangdong Province, and is also the first to take place in South China. The study has shown that the capacity onshore Guangdong is very small, while the capacity offshore
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is significant. In this paper the preliminary assessment of the CO2 storage capacity in the PRMB is presented. 2. Methodology of assessment Four classes of CO2 storage capacity, i.e. the theoretical, effective, practical, and matched capacity in the order of increasing accuracy, were defined by Carbon Sequestration Leadership Forum (CSLF) (Bachu et al., 2007). The theoretical capacity is the maximum upper limit for storage potential. It assumes that the system’s entire capacity to store CO2 in pore space, or dissolved at maximum saturation in formation fluids, or adsorbed at 100% saturation in the entire coal mass, is accessible and utilized to its full capacity. The effective capacity is similar to theoretical capacity, but with a number of geological and engineering limitations applied. In practice the effective capacity is obtained by the theoretical capacity multiplied by a storage efficiency factor that reflects the percentage of pore volume that CO2 is expected to actually contact. In this study, the effective capacities are assessed, and the data were collected from published sources. There are two types of storage sites in the PRMB: deep saline formations and oil and gas reservoirs. The deep saline formations are the porous rocks at depths below 800 m and with formation water having total dissolved solids > 10 000 ppm (USDOE, 2008b). The USDOE methodology (USDOE, 2008b) was used in the capacity calculation for saline formations. In this scheme the entire aquifer rather than only traps is considered. The storage capacities are given by: MCO2 = A × h × ϕ × CO2 × E
(1)
where A is the area of basin or region to be assessed, h is the gross thickness of the saline formations to be assessed and E is the storage efficiency factor. The estimation of CO2 storage capacity in oil and gas reservoirs follows the CLSF scheme (Bachu et al., 2007), which is based on the assumptions that the volume previously occupied by the produced hydrocarbons becomes available for CO2 storage, and that CO2 will be injected into depleted oil and gas reservoirs until the reservoir pressure is brought back to the original reservoir pressure. The effective storage capacity in each reservoir is calculated on the basis of its recoverable hydrocarbon reserves, its reservoir properties and in situ CO2 characteristics by the formula:
MCO2t = CO2r × Rf ×
OOIP − Viw + Vpw × E Bf
(2)
where MCO2t is the estimated storage capacity in million ton, CO2r is the density of CO2 in the reservoir, OOIP is the volume of original oil in place at standard temperature and pressure, Rf is the recovery factor, Bf is formation volume factor, Viw and Vpw are injected and produced water, and E is the storage efficiency factor. Bachu (2008) pointed out that the CSLF and USDOE methodologies are computationally equivalent. The capacity given by Eq. (1) should also be the effective capacity, as the effective coefficient E is included. In addition, the “saline formations to be assessed” in (1) is the formation that meets the requirement for CO2 storage, thus we think the h in (1) should be the formation thickness times the net/gross ratio, rather then being the gross formation thickness. These understandings will be followed in this study. 3. Geography and geology 3.1. Geography The Pearl River Mouth Basin (PRMB), 111◦ 20 –118◦ 0 E and 18◦ 30 –23◦ 00 N, is a NEE-elongated basin, 900 km long and
309
115–280 km wide, with total area of nearly 200 000 km2 . The basin resides offshore Guangdong Province in the shelf (∼68% of total area) and the slope of the northern South China Sea, with water depth ranging from 50 m to over 2000 m (Fig. 1). It is the largest sedimentary basin in the northern South China Sea, and is the offshore basin most proximal to the industrialized area of the Pearl River Delta in Guangdong. 3.2. General geology Geologically the PRMB is an extensional basin in the passive continental margin of the northern South China Sea. It was formed by rifting of the South China Block in the Paleogene and subsequent subsidence in the Neogene. Lithofacies in the basin was generally continental in the Paleogene and marine in the Neogene. The basement of the PRMB is composed of Mesozoic granites and secondary Paleozoic metamorphic rocks. Above the basement there are 4 depressions aligned in two NEE-running belts: The Zhu3 and Zhu-1 depressions in the northern depression belt, and the Zhu-2 and Chaoshan depressions in the Southern depression belt (Fig. 1). The two depression belts are separated by a NEE Central Uplift belt. In vertical sections the structures are composed of the lower section of Paleogene rifts (half-grabens and grabens) and the upper section of Neogene post-rift downwarps (Fig. 1). NEE faults often controlled the orientation of the depressions, while NWW-EW faults controlled the distribution of sags and traps. NW-running large crustal or lithospheric faults cut the depression belts into blocks. Cenozoic volcanism occurred episodically from the Early Eocene to Quaternary (Liang and Li, 1992). They are mostly acid and intermediate volcanic clasts, with mafic and intermediate lavas in the Paleogene, and basaltic lavas in the Neogene and Quaternary. Except for the Quaternary basalts these usually are small in size and in the vicinity of large NW faults. Earthquake activity has been sparse and weak in major portions of the PRMB. There was only one M ≥ 6 earthquake occurred in the western central uplift belt (September 1931, M6.75). 3.3. Stratigraphy and paleo-geography The PRMB is filled with Cenozoic sediments with a maximum thickness of >6 km in shelf areas and >14 km in slope areas (Chen et al., 2003; Zhou et al., 2009). The stratigraphic column of the PRMB is shown in Fig. 2. During the Paleogene the PRMB received fluvial and lacustrine clastic sedimentation in rifted basins and incised valleys. In Neogene the PRMB subsided to a marine environment. In general the sealevel has been rising (Qin, 2002), opposite to the global trend of sealevel dropping in this period. Paleo-Pearl River system supplied large quantity of terrigenous sands and muds to the basin. Frequent fluctuation of sealevel has resulted in cyclic sedimentations all through time, forming multiple deltas in the north and sequences of marine strata in the south. 3.4. Petroleum geology Major source rocks in the PRMB are the lacustrine dark mudstones of Middle Eocene Wenchang Formation and the coal-bearing sequences in Late Eocene to Early Oligocene Enping Formation. The dark mudstones in the Miocene Zhuhai and Zhujiang Formations are secondary source rocks (Cai, 2005). There are three source-reservoir-seal assemblages in the PRMB: (1) the self-contained Paleocene-Eocene continental assemblage which occurs sparsely in the northern PRMB; (2) the welldeveloped Paleogene-Eocene-Miocene assemblage with sources in continental Paleogene formations locally within sags, reservoirs in
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Fig. 1. Simplified geological map and cross-section AA of the Pearl River Mouth Basin. Data points used in the assessment are superimposed.
marine Zhuhai and Zhujiang Formations, and caprocks in upper Zhujiang Formation; (3) the Miocene marine assemblage with sources in Zhujiang Formation, reservoirs in Hanjiang Formation, and caprocks in upper Hanjiang Formation. Structural traps in sandstone and the cavities in carbonate buildups are the principal reservoir types in the PRMB. Oil fields have been found mainly in the Zhu-1 depression along the edges of the Central Uplift belt. Most oil fields are small, except the LH11-1 field with proved reserves over 100 Mt (0.73 billion barrels) (Zhu et al., 2008). In recent years, large gas fields have been discovered in the Zhu-3 and Zhu-2 depressions.
4. Capacity assessment for saline formations 4.1. Geological conditions for CO2 storage Regional seals are the mudstone layers in Miocene Hanjiang and Zhujiang formations. In the Zhu-1 depression the Hanjing Formation contains 400–600 m of mudstones, 70–80% of the formation thickness; while in the Zhu-2 depression these numbers are 700–800 m and 80–90%. The Zhujiang Formation contains both seals and reservoirs. Its delta front and transgressional mudstones have 57–90% of the formation thickness in most part of the basin (Cai, 2005). As the mudstones in the Hanjiang Formation form the uppermost regional seal, in this assessment the strata above the Hanjiang Formation will not be considered. Frequent cyclic sealevel changes in the PRMB produced a large amount of local seals. For example, the upper member of the Zhujiang Formation in the Wenchang A Sag of the Zhu-3 depression, which contains 42–75% mudstone with thickness of 191–655 m (Cai, 2005).
Potential reservoirs in the PRMB include deltaic, channel, transgressional, slope and low-stand fan sandstones, and reefal and platform carbonates. Sandstones are rich in transitional facies, decreases in neritic facies and poor in bathyal and abyssal facies (Gong and Li, 1997). Sandstone reservoirs have been found mostly in Zhuhai, Zhujiang, and Hanjiang formations, and possibly in the fluvial sandbars of the Enping Formation. Carbonate reservoirs are found in Miocene formations and mainly in the Dongsha Uplift. In the Late Oligocene Zhuhai Formation oil accumulations of 8 m and 4 m thick have been found, with sandstone porosity of 10–16% and permeability of 4–85 mD (Cai, 2005). The Miocene Zhujiang and Hanjiang Formations contains reservoirs of mainly delta-front sandstones, with porosity of 16.3–29.6% and permeability of 188–1732 mD. Among these the best reservoir was found in the Hanjiang Formation with a thickness of 8 m, porosity of 29.6%, and permeability of 1732 mD (Cai, 2005). Carbonate reservoirs in the PRMB have a porosity range of 9–28% and a permeability range of 7–1365 mD. The LH11-1 oil field has average porosity of 23% and permeability of 471.5 mD. Well LH41-1 has an average porosity of 23% and permeability of 471.5 mD. The LF15-1 limestones have an average porosity of 26% and a permeability range of 7–203 mD. Well LF22-1-1 has a porosity of 29% and a permeability of 54 mD (Cai, 2005).
4.2. Data sources A GIS-based database was built for the Cenozoic formations in the PRMB. The data were compiled from published sources, including those from 31 wells. As available well data are insufficient for depth and isopach mapping, published 23 regional seismic profiles (depth converted) and low-resolution isopach maps (e.g., the three
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311
Fig. 2. Stratigraphic column of the Pearl River Mouth Basin.
isopach maps from Gong and Li, 1997, as well as the isopach maps of the Baiyun Sag from Zhou et al., 2009) have been used to provide additional data points. Resulting isopach maps are used for assessing the effective capacity (see Fig. 1 for data point distribution). Water depths are from the Geographic Map of the South China Sea published by South China Sea Institute of Oceanology (SCSIO) in 1983.
4.3. Formation volumes For this assessment the Cenozoic formations of the PRMB are divided into three super sequences: Paleogene (Wenchang, Enping, and Zhuhai Formations), Early-Middle Miocene (Zhujiang and Hanjiang Formations), and Late Miocene to Holocene (Yuehai, Wanshan Formations and Quaternary). On a GIS platform, their isopach maps were constructed (Fig. 3), and their gross volumes and the volumes below 800 m from the seafloor were calculated (Fig. 4 and Table 1). In addition, volumes of the depth range 800–2500 m, as suggested
to be a positive indicator by Chadwick et al. (2008), were also calculated. This reduced the volume by 15% for the Lower-Middle Miocene and by as much as 65% for the Paleogene (Table 1).
4.4. Lithological parameters Published data on the net/gross ratio, the porosity, and the permeability of the rocks in the PRMB are sparse and thus have to be estimated based on several sets of incomplete or indirect data. Stratigraphic columns from 6 wells in the Zhu-1 and Zhu-2 depressions have been used to measure the net/gross ratio. Simple averages of net/gross ratios in these wells are 0.36, 0.49, and 0.64 for the super layers of the Paleogene, Early to Middle Miocene, and Upper Miocene to Holocene, respectively. Data of oil-tested sandstone segments from 11 wells and of sampled segments from 7 wells of the eastern PRMB (east of longitude 113◦ E) are published in Tables 5-2, 5-3, and 5-4 of Chen et al. (2003). The average values weighted by segment thickness are computed.
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Fig. 3. Isopach maps of the Pearl River Mouth Basin. (a) Sea water, (b) Upper Miocene to Quaternary, (c) Lower-Middle Miocene, and (d) Paleogene. Superimposed white lines show the boundaries of depressions and sags. Table 1 Areas and volumes of the super sequences in the Pearl River Mouth Basin. Super sequence
Area (km2 )
Depth of top (m)
Thickness (m)
Volume (km3 ) Gross
−800 m
−800 to 2500 m
Paleogene L.-M. Mioc. U. Mioc. To Q Total
197 290 174 856 30 185
0–2600 0–700 0
0–1700 0–2500 0–700
165 773 235 228 114 490 515 491
163 149 184 459 6242 353 850
56 924 157 288 6242 220 454
Petroleum systems have been delineated in the eastern PRMB, and their parameters are listed in Table 8-2 of Chen et al. (2003). Based on these data, the parameters of seals and reservoirs in the formations of the eastern PRMB are calculated by thicknessweighted averaging (Table 2). The parameters compiled from the above-mentioned sources are compared in Table 3. The porosities and permeabilities are reasonably consistent, but the net/gross ratio varies significantly. In this capacity calculation, the net/gross ratios from 6 wells were used.
4.5. CO2 density The density of CO2 varies with formation temperature and pressure (Bachu, 2003). The PRMB is in general in a normal pressure system. Overpressure is observed locally in deep-burring (>4600 m) Wenchang and Enping formations (Gong and Li, 2004). Thus in this paper we use the hydrostatic pressure to approximate the formation pressure. The formation temperature depends on the surface temperature and geothermal gradient. The seafloor temperature of the
Table 2 Parameters of oil-tested sandstone segments from the wells in eastern PRMB (thickness-weighted averages based on tables 5-2, 5-3, and 5-4 in Chen et al., 2003). Formation
Porosity (%) Range
Zhujiang Zhuhai Enping
13.3–23.9 2.3–22.7 0.7–22.0
Permeability (mD) Ave. 19.9 16.8 10.3
Range 20.2–2027.9 3.5–913 0.03–95
Net/gross ratio (%)
# of wells
92.6 87.8 No data
10 11 14
Ave. 916.5 318.0 7.0
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313
Fig. 4. Isopach maps of the formation below 800 m from the seafloor in the Pearl River Mouth Basin (a) Upper Miocene to Quaternary, (b) Lower-Middle Miocene, and (c) Paleogene. Superimposed white lines show the boundaries of depressions and sags.
northern SCS varies with water depth as shown in the inset of Fig. 5. The thermal gradient varies across the PRMB in the range of 26.2–50.6 ◦ C/km. A contour map of geothermal gradients in the PRMB was compiled based the data of 75 wells (Fig. 5) from Rao
and Li (1991). The gradient is in general lower than 35 ◦ C/km in the shallow-water Zhu 1 depression, while higher in the deep-water Zhu 2 and shallow-water Zhu 3 depressions. Accordingly we divide the basin into three regions (Fig. 5): the N-PRMB with relatively
Fig. 5. Contour map of geothermal gradient of the Pearl River Mouth Basin compiled based on drill hole measurements given in Rao and Li (1991) with minor additions. Thick dashed line divides the basin into 3 districts for constructing CO2 density curves. Numbers show the average gradient (in ◦ C/km) for individual sags. Inset is a curve of seafloor temperature in northern South China Sea measured by SCSIO.
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Table 3 Comparison of the reservoir parameters compiled from various data sources. Porosity (%) Hanjiang Zhujiang
Zhuhai
Enping a
Ave. 33.1 16.3–29.6a Ave. 19.9 20.8 16.3–29.6a Ave. 16.8 17.0 4.5–16.8 Ave. 10.3
Permeability (mD) a
188–1732 Ave. 916.5 624.1 188–1732a Ave. 318.0 431 4.4–2434 Ave. 7.0
Net/gross (%)
Data source
68.1 10–30 92.6 53.3 10–43 87.8 45.6
Chen et al. (2003) Cai (2005) Table 3 Chen et al. (2003) Cai (2005) Table 3 Chen et al. (2003) Cai (2005) Table 3
Table 4 CO2 density versus formation depth for the N-, S-, and SW-Pear River Mouth Basin. N-PRMB ◦
Parameters for combined Zhujiang and Hanjiang formations.
Therm. grad. ( C/km) Seafloor temp. (◦ C) Depth (m) 800–1000 1000–1200 1200–1400 1400–1600 1600–1800 1800–2000 2000–2200 2200–2500 2500–3000 3000–4600 4600–6600
S-PRMB
34 20 CO2 density (kg/m3 ) 288.9 386.3 460.1 504.5 528.5 543.6 556.0 565.7 574.5 589.0 599.5
SW-PRMB
40 8
40 20
334.3 422.7 467.6 495.6 513.4 524.4 530.2 532.4 535.4 542.8 548.4
267.6 348.5 414.3 455.1 478.7 494.6 507.1 519.0 531.0 545.0 555.5
4.6. Storage efficiency factor It is beyond the ability of this paper to estimate the storage efficiency factor E for the PRMB. The USDOE Subgroup through Monte Carlo simulations obtained a statistical distribution of E for deep saline aquifers with P15, P50, and P85 probability level at E = 0.01 0.024, and 0.04 respectively (Bachu, 2008). Recent thematic study (IEAGHG, 2009) suggests the overall mean value (P50) of E for all lithologies being 0.026 at the formation level (Wildgust, 2010). Combining these two results, in this paper we use E = 0.026 for mean and E = 0.01 and 0.04 for P15 and P85 probability level, respectively. 4.7. Capacity calculation On a GIS platform the effective capacity for CO2 storage in the saline formations in the Pearl River Mouth Basin is estimated using Eq. (1). In addition to the general assumptions stated in Section 2, the following assumptions are made: Fig. 6. Curves of CO2 density versus depth for N-, S-, and SW- Pearl River Mouth Basin compiled based on the data in Fig. 5, parameters in Table 1, and values in Table 45 of Span and Wagner (1996). Curves of “Typical” and “Hot” regions from Chadwick et al. (2008) are also shown for comparison.
high seafloor temperature and low thermal gradient, the S-PRMB with relatively low seafloor temperature and high thermal gradient, and the SW-PRMB with both high seafloor temperature and high thermal gradient. Curves of CO2 density versus formation depth were constructed respectively for each region (Fig. 6) based on Span and Wagner (1996). In Fig. 6 selected curves from other publications are also presented for comparison. The increase rate of CO2 density with depth in the PRMB is much slower than the 35 ◦ C/km curve of GeoCapacity (2009), and in between the “Typical” and “Hot” curve s of Chadwick et al. (2008).
(1) The Middle Miocene Hanjiang Formation forms the upper regional seal, and the delta-front and transgressional mudstone in the Zhujiang Formation form the lower regional seal; (2) CO2 reservoirs mainly reside in the sandstones and limestones of the Early Miocene Zhujiang and Zhuhai Formations, and secondarily in Middle Miocene Hanjiang Formation and in Oligocene Enping Formation; (3) Because no data are available for the Wenchang Formation, its parameters are assumed to be the same as those of the Enping Formation. Therefore, only the Paleogene (Wenchang and Enping) and Lower-Middle Miocene (Zhuhai, Zhujiang, and Hanjiang) formations are considered in the capacity calculation. Eq. (1) is used in the calculation with mean of E = 0.026, and 15% and 85% probability level of E = 0.01 and 0.04, respectively.
Table 5 Parameters and capacity assessments for the saline formations in the Pearl River Mouth Basin. Parameter Volume below 800 m V (m3 ) Net/gross ratio R Average porosity ϕ CO2 density CO2 (t/m3 ) Effective capacity (Gt), >800 m
Effective capacity (Gt), 800–2500 m
L.-M. Miocene
Paleogene
Total
E = 0.01 E = 0.026 E = 0.04 E = 0.01 E = 0.026 E = 0.04
187 000 × 109 0.5 0.2 As in Table 4 86 225 345 71 184 284
164 000 × 109 0.37 0.1 As in Table 4 32 83 128 10 26 40
118 308 473 81 210 324
D. Zhou et al. / International Journal of Greenhouse Gas Control 5 (2011) 308–317
As the CO2 density varies with depth, for each of the 3 districts in Fig. 5 the formation body was cut into horizontal layers, and the average CO2 densities for individual depth layers were read from the curves in Fig. 6 and listed in Table 4. The volumes of these layers in each super sequences in the 3 districts were calculated on a GIS platform. Other parameters and estimations are listed in Table 5. The mean, P15 and P85 probability level estimations of the effective CO2 storage capacities in saline formations of the PRMB are 308 Gt, 118 Gt, and 473 Gt, respectively.
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Table 6 Parameters and capacity assessments of CO2 in oil and gas fields of the Pearl River Mouth Basin. Parameter
Value
OOIP (t) Oil density (t/m3 ) Recovery rate Rf Volume factor Bf CO2 density (t/m3 ) Efficiency factor E Capacity (t)
0.9 × 109 0.9 0.5 1.03 0.566 0.25 0.06 × 109
5. Capacity assessment of oil and gas fields Up to 2009 there have been ∼200 wells drilled in the PRMB, and ∼40 oil and gas fields have been found, with oil production over 10 million m3 (63 million barrels) since 1996. The estimations of geological resources in the PRMB are 2.3–3.2 billion tons (17–23 billion barrels) oil equivalent (MLR, 2008), and proved reserve (OOIP) is ∼0.9 billion tons (6.5 billion barrels) oil equivalent (informal data). The capacity of CO2 in oil and gas fields of the PRMB is estimated using the Eq. (2). As there has been no water flooding in the PRMB, Viw and Vpw are zero and (2) becomes:
MCO2t = CO2r × Rf ×
OOIP Bf
×E
The oil fields in the PRMB have a high recovery rate, and a conservative estimation of Rf = 0.5 is used in our calculation. The crude oil from the fields in the PRMB is light with average density of ∼900 kg/m3 and volume factor Bf = 1.02–1.05. The oil fields reside mostly in the Zhu 1 depression and within 2000–3000 m depth, only the LH11-1 field in 1252–1330 m depth (Chen et al., 2003; Zampetti et al., 2005). As the oil/gas reserves for individual fields are not publicly available, we do not know the reserve values for the 3 districted in Fig. 5. Thus we have to calculate for the entire basin, using the CO2 density of 565.7 kg/m3 , which is the CO2 density at 2200–2500 m depth in the N-PRMB (Table 4). There are very few studies of E for oil and gas fields. A study by Bachu and Shaw (2005) in western Canada estimated the capacity reduction in oil fields for strong aquifer as 0.19–0.75 and in average 0.5, and for mobility and
other factors as 0.5. Thus E = 0.5 × 0.5 = 0.25, which is used in this paper. The parameters and estimated effective capacity are listed in Table 6. The estimated effective storage of CO2 in the oil and gas fields in the PRMB is 0.06 Gt. This is likely an underestimated number because the proved reserve is used in the estimation. As the basin is still in the exploration stage, the un-proved reserve may be large. For example, the newly estimated resource of the Zhu-1 depression alone reaches 5.9 billion tons oil equivalent (Shi et al., 2009), and new gas fields have been discovered in the deepwater Baiyun Sag of the Zhu-2 depression (Pang et al., 2007).
6. Storage prospectivity At this preliminary stage, major concerns for assessing the storage prospectivity are the distribution of reservoirs and seals, the distance from major emission sources (the Pearl River Delta), the depth and size of possible reservoirs, and the possibility of CO2 -EOR. Under these criteria, the most promising area for CO2 storage in saline formations is the northern portion of the Lufeng and Hanjiang sags in the Zhu-1 depression (Fig. 7). In this area the Lower and Middle Miocene formations are thick and with good reservoir-seal assemblages (Fig. 4). A number of structural traps in the area have been proved dry, among which the large ones may be the first candidates for CO2 storage. The distance from Hongkong to this area is between 150 and 300 km.
Fig. 7. Map showing the distribution of oil/gas fields in the Pearl River Mouth Basin. The promising area for CO2 storage in saline formations is indicated by red polygon. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)
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The northern Xijiang Sag to the west is relatively dry and lies even closer to the industrialized Pearl River Delta, but the sag has been filled with large quantity of mostly sandy sediments from the paleo-Pearl River system, and the sealing condition there is poor. Within the promissing areas, reservoirs in the Middle Super sequence (Lower and Middle Miocene) deserve special attention, because they contain the most abundant, thick, and high quality sandstone or carbonate formations, covered by well developed mudstone seals. There may be some sandstone reservoirs in the Lower Super Layer (Paleogene), but those continental formations are usually deeper, less understood, and with poorer quality (lower porosity and permeability due to diagenesis) and smaller capacity. These make it a lower priority at this stage. The storage prospectivity in oil and gas fields in the PRMB is limited. Oil fields have been found in southern Huizhou and Lufeng sags, southwestern Dongsha Uplift, northern Panyu Low Uplift, southern Enping Sag, and the southeastern Wenchang Sag (Fig. 7). Most fields are small but distributed as clusters and contain high quality light oil. However the capacities in these oil fields are insufficient for large scale CO2 storage when compared to the size of emission sources. The largest LH11-1 field has a proved reserve >100 Mt (>0.7 billion barrels) in porous carbonate reservoirs. It is 220 km SE of Hongkong. The potential of CO2 -EOR in the PRMB is probably low, as the oil fields have high recovery rate (over 50%) in general, and strong water invasion occurs automatically during the production. The gas fields so far discovered are usually large. For example, the newly discovered LW3-1, LH34-2, and LH29-1 gas fields have a proved reserve >100 × 109 m3 each, and the PY30-1 gas field has proved reserve of 30 × 109 m3 and started production in early 2009. The produced gas has been transported to Zhuhai City through underwater pipelines. A disadvantage for CO2 storage is that these gas fields reside in deepwater areas, where the cost of drilling and infrastructure are likely to be much higher. These fields have the potential to be used as storage sites for CO2 only in a very long term.
7. Conclusions For the saline formations deeper than 800 m below seafloor in the Pearl River Mouth Basin, the estimated effective capacity for CO2 storage is 308 Gt in average, with P15 and P85 probability level of 118 Gt and 473 Gt. If only the formations shallower than 2500 m below the seafloor are considered, the estimated effective capacity is reduced by 27%, 210 Gt in average, with P15 and P85 probability level of 81 Gt and 324 Gt. About 73% of the effective capacity resides at depth <2500 m, and 88% of the effective capacity resides in Lower-Middle Miocene formations. The abovementioned effective capacity includes that in oil and gas fields, which is very small (0.06 Gt). But this is a conservative estimate as newly proved and unproved fields are not included. According to this assessment, the deep saline formations in the PRMB are able to storing 190 years of total CO2 emission from major point sources in Guangdong, if 10% of the effective storage capacity may be used and if the total emission keeps the 2006 level of 160 Mt/a (Bai et al., 2006). These estimates are of high uncertainty because they were obtained based on published incomplete data, and with the assumptions that all the formations are saline and all the pore space may be filled with injected CO2 . Compared with the estimates for other areas in the world, the estimated capacities for the saline formations in the PRMB are larger than those for the California state
(84–311 Gt) (USDOE, 2008c), but the estimated effective capacity for oil and gas fields in the PRMB is less than 1/100 of that for California (7.7 Gt) (USDOE, 2008c). The advantages common to all offshore storage of CO2 are applicable to the PRMB, such as no interference with population, agriculture, and industry, no damage to groundwater, and in technical issues such as the potential to manage pressure within the geological formation (Schrag, 2009). The disadvantages of the PRMB for CO2 storage are also common to all offshore storage sites, mainly the higher cost of the infrastructures and engineering operations compared with the onshore storage. But overall, storing CO2 in geological formations offshore may be easier, safer, and less expensive (Schrag, 2009). In addition, the advantages of the Pearl River Mouth Basin for CO2 storage are: (1) The mudstones in the Late Miocene Hanjiang Formation and the upper Middle Miocene Zhujiang Formation form excellent regional seals. Frequent sealevel fluctuation in Neogene resulted in multi-layers of local seals. Sandstones and limestones are wide spread in the Neogene and upper Paleogene formations, forming promising reservoirs. Multiple seal-reservoir assemblages have been proved by hydrocarbon exploration. (2) Extensive data and infrastructure (wells, pipelines, etc.) have been accumulated during a long period of exploration and may be used for CO2 storage. (3) Proximal to major CO2 point sources in the Pearl River Delta. As there is little capacity for CO2 storage in onshore Guangdong, the high potential for CO2 storage in the Pearl River Mouth Basin is even more important to the Guangdong Province. As the hydrocarbon exploration is still going on in the PRMB, the initial stage of CO2 storage should be concentrated on known dry traps in areas where the hydrocarbon source rocks are less developed. In consideration of the distribution of reservoirs and seals, the distance from major emission sources in the Pearl River Delta, and the depth and size of possible reservoirs, the promising areas for CO2 storage should be considered first are the Zhuhai and Zhujiang formations in the northern Lufeng and Hanjiang sags of the Zhu-1 depression. A detailed study on the dry traps in these areas should be conducted to identify target traps and their capacity. Additional data such as seal maps, reservoir maps, pressure, temperature, CO2 density, irreducible water saturation, etc. should be collected to make more accurate estimation for the CO2 storage capacity in these traps. Acknowledgements The study is funded by the Tactical Fund for Low Carbon and High Growth and administered by the UK Foreign & Commonwealth Office. The authors are indebted to Wayne Ives, Bill Senior, Jonathan Pearce, as well as Stefan Bachu and anonymous reviewers for their valuable suggestions on improving the manuscript. References Bachu, S., 2003. Screening and ranking of sedimentary basins for sequestration of CO2 in geological media. Environmental Geology 44 (3), 277–289. Bachu, S., 2008. Comparison between Methodologies Recommended for Estimation of CO2 Storage Capacity in Geological Media – Phase 3 CSLF Task Force on CO2 Storage Capacity Estimation and the USDOE Capacity and Fairways Subgroup of the Regional Carbon Sequestration Partnerships Program, p. 21. Bachu, S., Shaw, J.C., 2005. CO2 storage in oil and gas reservoirs in western Canada: effect of aquifers, potential for CO2 -flood enhanced oil recovery and practical capacity. In: Proceedings of the 7th International Conference on Greenhouse Gas Control Technologies (GHGT-7), September 5–9, 2004, Vancouver, Canada, pp. 361–370.
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