A comprehensive evaluation index for shale ... - Science Direct

PETROLEUM EXPLORATION AND DEVELOPMENT Volume 44, Issue 4, August 2017 Online English edition of the Chinese language journal Cite this article as: PETROL. EXPLOR. DEVELOP., 2017, 44(4): 686–695.

RESEARCH PAPER

A comprehensive evaluation index for shale reservoirs and its application: A case study of the Ordovician Wufeng Formation to Silurian Longmaxi Formation in southeastern margin of Sichuan Basin, SW China SHEN Cheng1, REN Lan1, ZHAO Jinzhou1,*, TAN Xiucheng1, WU Leize2 1. State Key Laboratory of Oil and Gas Reservoir Geology and Exploration, Southwest Petroleum University, Chengdu 610500, China; 2. Research Institute of Petroleum Engineering of Jianghan Oilfield Branch of Sinopec Corp., Wuhan 430035, China

Abstract: Aiming at the disadvantages of existing shale reservoir evaluation methods, a new comprehensive index was proposed to accurately predict the distribution of high quality shale reservoirs and favorable fracturing intervals. The comprehensive index can be calculated using the physical properties index and fracturing index by the equivalent method. Computed by logging rock-electric parameters and mineral bulk physical model, the physical properties index characterizes reservoir property and gas-bearing property; the fracturing index characterizes reservoir fracability and is acquired by equivalent porous medium model considering mineral components. According to the comprehensive index, combined with the macro-micro characteristics of cores and logging data, the shale reservoirs in the Ordovician Wufeng Formation to Silurian Longmaxi Formation of Jiaoshiba area in the southeastern margin of Sichuan Basin are subdivided into four types, the high terrigenous siliceous and high authigenic siliceous types are the best in reservoir property and fracability, followed by the middle siliceous and then low siliceous. The comprehensive index can be used to interpret the logging data of horizontal well to figure out the proportion of reservoirs of different types, identify the spatial distribution of reservoirs with good physical properties and good fracability. The predicted results match well with actual production after fracturing. Key words: comprehensive evaluation index; physical properties index; fracturing index; shale reservoir; gas-bearing property; fracability; siliceous shale; Jiaoshiba shale gas; Sichuan Basin

Introduction Efficient evaluation of shale reservoir has become a key link in shale gas development research[12]. Good reservoir quality and large stimulated reservoir volume (SRV) are the premises for economic productivity. But evaluation methods are taken for different shale areas due to different geological settings and different data collected. For example, attribute contour method[3], seismic inversion method[46], lithological standardization method[79] and cycle comparison method[10] can be used in reservoir storage capacity evaluation; while mineral constituent method[1112], elastic parameter method[1314] and their combination[1517], and numerical analysis method with micro-seismic monitoring[1819] can be used in brittleness and fracability evaluation. Therefore, sweet spots with high reservoir quality or potential artificial high permeability zone with high fracturing degree can be picked out[20]. However,

the geological and engineering factors have not been considered simultaneously in the present evaluation methods mentioned above[21], which may lead to uncertainties in horizontal well clustering and staged fracturing program, and thus low or unstable production. Also, the connection between reservoir physical properties and fracability has not been fully considered (whether the horizontal well (section) with large SRV also has high reservoir quality or high gas content), so the deployment of production well and selection of fracture section are still not so pertinent. Thanks to the “Two element enrichment theory”, and “High productivity and enrichment mode” proposed by Guo Xusheng[22] and Guo Tonglou et al[23], the development of shale gas reservoir in Upper Ordovician Wufeng Formation to Lower Silurian Longmaxi Formation in the southeastern margin of Sichuan Basin has achieved substantial effect, and reservoir evaluation has obtained periodical result[2425]. Aiming at

Received date: 11 Dec. 2016; Revised date: 12 May 2017. * Corresponding author. E-mail: [email protected] Foundation item: Supported by the China National Science and Technology Major Project (2016ZX05060); National Natural Science Foundation of China (51404204). Copyright © 2017, Research Institute of Petroleum Exploration and Development, PetroChina. Published by Elsevier BV. All rights reserved.

SHEN Cheng et al. / Petroleum Exploration and Development, 2017, 44(4): 686–695

the imperfection in current shale reservoir evaluation methods, with the above-mentioned block as the study object, considering the effect of gas content and stimulated reservoir volume, a comprehensive index considering physical properties and fracability is introduced to classify the shale reservoir, and the distribution of shale reservoir with high quality and good fracability is identified on the basis of logging data. This study also can be used to evaluate the refracturing section later.

1. Establishment of comprehensive shale reservoir evaluation index Both geological features and fracturing conditions should be considered in the process of shale gas development. Through core and numerical analysis, some researchers found that there was a negative correlation between brittle mineral content and porosity of shale reservoir[15,26]. Analysis of shale samples from Wufeng Formation to Longmaxi Formation in Jiaoshiba gas field, the southeastern margin of Sichuan Basin showed the same rule (Fig. 1). Therefore, the reservoir zone with high physical quality is not necessarily the fracturing sweet spot, and the zone with larger SRV doesn’t necessarily have good physical properties. Hence it is necessary to evaluate the shale gas reservoir by considering geological and engineering indexes jointly, so a comprehensive index considering the reservoir physical properties and fracability has been advanced. 1.1.

Physical properties index

Physical characteristics of reservoir can directly affect oil

Fig. 1. Relationship between porosity and brittle mineral content of shale samples from Wufeng Formation to Longmaxi Formation in Jiaoshiba shale gas field, southeastern margin of Sichuan Basin. Table 1.

and gas content. Generally, reservoir physical properties are assessed by experiment, i.e. evaluating physical properties of shale reservoir by obtaining reservoir space features from capillary pressure curve, but the capillary pressure curve cannot further distinguish shale reservoir type due to similar tightness of shale (Table 1); or of the reservoir physical properties can be assessed by storage coefficient which is the product of total organic carbon (TOC) and organic-rich (TOC >2%) reservoir thickness. But development effects of shale gas in different areas show the contribution of free gas content to productivity is significant and can’t be ignored (Fig. 2), TOC and porosity are key parameters to predict the absorbed and free gas content respectively[27] (Figs. 3 and 4), whereas the storage coefficient method doesn’t consider factors like porosity etc that measure the reservoir space and free gas content. Therefore, in this study, TOC and porosity are taken to establish the physical property index from the point of gas content, then the weight of each parameter is worked out by entropy weight method to evaluate the physical properties of shale gas reservoir. The weight coefficients a1 and b1 are introduced to respectively characterize the contribution of porosity (free gas) and TOC (absorbed gas) to productivity, the shale reservoir physical property index can therefore be established:

e1  a1   b1 TOC 

where   = e  min  max  min  TOC  = TOCo  TOCmin  TOCmax  TOCmin 

(1)

But not all TOC and porosity data can be obtained by lab analysis because of economic limitation, so, in this study, TOC was regressively calculated from logging-density data by the method introduced in reference [28]: TOC =  0.161 29 ρ  0.441 47 (2) Similarly, shale was divided into two parts, matrix (siliceous, carbonate and clay minerals, organic matter), and formation fluid and reservoir space (bound water, natural gas and pore-fracture system). The formula calculating porosity was established by mineral volume model:  TOClab  m    m  TOC   1  k   (3) e =  m   m  f  TOClab  f 1   k   Then weight coefficients of TOC and porosity were calculated by entropy weight method. Firstly, the TOC and porosity

Mercury injection experiment results of shale samples from Well JY-1 in Jiaoshiba shale gas field

Depth/m

Porosity/%

Permeability/103 μm2

Median radius/μm

Median pressure/MPa

Displacement pressure/MPa

Curve type

2 330.46

4.31

0.034 8

0.004 8

156.782 0

45.4

Fine skewness

2 340.82 2 355.60 2 369.63

4.19 2.77 3.86

0.749 6 9.417 7 1.240 8

0.005 1 0.004 7 0.005 1

146.524 0 160.560 0 146.395 9

50.5 47.2 41.0

Fine skewness Fine skewness Fine skewness

2 379.78

4.13

109.721 0 (Fracture)

0.007 6

98.323 9

27.5

Fine skewness

2 393.63

4.00

0.005 6

0.007 2

131.246 0

37.6

Fine skewness

2 412.61

4.79

0.009 7

0.005 9

126.356 8

48.2

Fine skewness

 687 

SHEN Cheng et al. / Petroleum Exploration and Development, 2017, 44(4): 686–695

Fig. 5. Relationship between free gas content and absorbed gas content of shale samples from Well JY-1. Fig. 2. Comparison of free gas and absorbed gas contents of different shale gas reservoirs in north America.

where

a Wj   1 b1

j  j  TOC

When higher than 4.5% in porosity, the shale reservoir in the research area has higher free gas content (Fig. 4), which has been proved by porosity test of core samples (Fig. 5). Therefore, a1 and b1 at the porosity of more than 4.5% and less than 4.5% were calculated respectively to characterize the contribution of free gas and absorbed gas in different conditions. The results show that a1 and b1 equal 0.65 and 0.35 when the porosity is higher than 4.5%, and a1 and b1 equal 0.55 and 0.45 when the porosity is less than 4.5%. Fig. 3. Relationship between TOC and absorbed gas content of shale samples.

Fig. 4. Relationship between porosity and free gas content of shale samples.

data were normalized: xij  min x j Yij  (i=1, 2, …, k; j=, TOC) max x j  min x j

(4)

Secondly, the entropy model was established: k

E j   ln k 1  pij ln pij

(5)

i 1

where

pij  Yij

1.2.

Fracability of shale can also affect the shale gas productivity, and is usually characterized by mineral brittleness and rock mechanics brittleness[1317, 29]. The method in Reference [13] estimates fracability by equivalently processing each mineral component, therefore it cannot evaluate the brittleness accurately; the method in Reference [15] doesn’t consider the weight of poisson’s ratio and elastic modulus, and elastic parameters of shales in different work areas are different in variation amplitude, and thus have different influences on fracturing; the method in Reference [29], although taking factors such as fracture toughness and fracture extension criterion etc into consideration, is complex, and needs to set natural fracture occurrence, giving it too strong manual adjustability. In general, the less the Poisson’s ratio and the larger the elastic modulus, the larger the SRV will be (Fig. 6), thus, the gas-producing area will be larger, too. Based on the theory above, a fracturing index was derived from the new brittle index[15]: e2=E / υ (7) where

E =  Ei  Emin   Emax  Emin  υ=  υi  υmin   υmax  υmin 

k

Y i 1

Fracturing index

ij

At last, the weight coefficients were worked out from the weight model below: 1 Ej Wj  (6) k  Ej

Longitudinal and transverse wave offset time from logging data were used to calculate the Poisson’s ratio and elastic modulus of each logging data point: 2 2  3ts  4tp Ei = 2 (8) ts ts 2  tp 2

 688 

SHEN Cheng et al. / Petroleum Exploration and Development, 2017, 44(4): 686–695

Finally, with the formula (10) to formula (14), longitudinal and transverse wave offset time were calculated, and then Poisson’s ratio and elastic modulus of all logging points were calculated with formula (8) and formula (9). In the last step, the fracturing index was calculated by the formula (7). 1.3.

Fig. 6. Relationship between SRV and elastic parameters of Well Y.

0.5  Δts Δt p   1 2

υi 

 Δt

Δt p   1 2

s

(9)

However, not all wells have multipole array acoustic logging data, so the transverse wave data is often not available. Therefore, the compressional wave and transverse wave data were obtained by using Voigt-Reuss-Hill model[3032] and BiotGassmann model[33] in order to quickly calculate the fracturing index, establish correlation between mineral components and elastic parameters, and simplify the calculation process. Firstly, the equivalent elastic parameters of rock matrix (bulk modulus and shear modulus) were calculated by establishing the Voigt-Reuss-Hill model of different mineral components: Km   KV  KR  2 (10) where

K V   K n fn

1 1 fn  KR Kn

μm   μV  μR  2

where

μV   μn f n

(11)

1 1 fn  μR μn

Secondly, the pore and fluid were put into the shale matrix at the same time according to the equivalence relation between stress and strain in two phase medium deduced by Mavko from Biot theory[34]:  μ  μm 1  α  (12)  2  K  K m 1  α   α p 1   e e where =  p Km Kf

New comprehensive index

Assuming that reservoir physical properties and fracability have equal contribution to productivity after fracturing of high-quality reservoir, then the comprehensive index can also be calculated by equivalent conversion: 2 1 1 =  (15) E0 E1 E2 where

E1   e1  e1min   e1max  e1min 

E2   e2  e2 min   e2 max  e2 min 

2. Classification of reservoir rock based on the new comprehensive index The rock type of reservoirs from Wufeng Formation to the 1st Member of Longmaxi Formation changes little, but as the depositional environment changed from deep-water anaerobic environment to deep-water continental shelf, the limited sedimentary water body was broken and water energy increased during their deposition, they have quite different proportions and origins of mineral components, in which the rapid change of biogenic silica minerals in Wufeng Formation to terrigenous silica in Longmaxi Formation is particularly obvious[35]. Based on previous research[36] and triaxial rock mechanics experiment, the gas bearing shale, in Wufeng Formation-1st Member of Longmaxi Formation (excluding the tuff in Guanyinqiao Member of the Upper Wufeng Formation), is divided into four kinds of reservoir rocks: low terrigenous siliceous shale (S1), middle terrigenous siliceous shale (S2), high terrigenous siliceous shale (S3) and high authigenic siliceous shale (S4)(Fig. 7). 2.1.

Low terrigenous siliceous shale

The cores of this kind of rock, dark grey-greyish black and tight, have many horizontally-laminated beds (Fig. 8a, 8b),

The bound water and natural gas were taken as fluid in this study, so the fluid bulk modulus can be equivalent converted by using water and gas saturation data: 1 Sw 1  Sw =  (13) Kf K w Kg Thirdly, the relation between elastic parameters can be established by Biot-Gassmann model: 4  ρ  Δt 2 =K  3 μ  p (14)   ρ =μ  Δts 2

Fig. 7. Plate of physical property index and fracturing index of Wufeng Formation to Longmaxi Formation in Jiaoshiba area, southeastern margin of Sichuan Basin.

 689 

SHEN Cheng et al. / Petroleum Exploration and Development, 2017, 44(4): 686–695

Fig. 8.

Macro and micro features of low terrigenous siliceous shale in Jiaoshiba area.

silty bands along beds about 0.31.0 mm wide, a few unfilled horizontal fractures (about 100 mm long and about 12 mm wide), calcite veins (Fig. 8a) and massive silty blocks (6 mm×6 mm10 mm×35 mm) (Fig. 8b). Microscopic observation shows this kind of rock has a clay mineral content of more than 50% (up to 76%), silica mineral content of less than 35%, carbonate mineral content of less than 8%, and bedparallel quartz particles with certain directionality (Fig. 8c). With physical property index and fracturing index of 0.20.4 and 0.40.6, respectively, this kind of rock has poor reservoir physical properties and fairly good fracability. Few bedding fissures and nanoscale organic matter pores are the main factors leading to poor physical properties of this kind of rock. Although low in total brittle mineral content, including silica and carbonate minerals, the silty bands and massive silty blocks enhance the fracability of this kind of rock. This kind of rock has a comprehensive index range of 0.10.4, low gas resources due to shortfall of reservoir space, and minor development degree of fractures makes it difficult to generate large SRV by volume fracturing, so this kind of rock would have poor development result from comprehensive evaluation. 2.2.

Middle terrigenous siliceous shale

Dark grey-greyish black, tight and brittle, on core samples, this kind of rock has many horizontally-laminated beds, frequent stacking of grey black argillaceous and pale grey silty bands (Fig. 9a), and quite some horizontal fractures semifilled by calcite (70120 mm long and 12 mm wide). Microscopic observation shows this kind of rock has a clay mineral content of less than 35%, silica mineral contents between 35% and 50%, carbonate mineral content between 8% and 10%, dolomite in bands with unclear boundary with clay (Fig. 9b),

Fig. 9.

quartz even distributed in clay or in lamina (Fig. 9c), and graptolite fragment content of 5%10%, higher than low terrigenous siliceous shale. This kind of rock has physical property indexes and fracturing indexes of mainly 0.30.5 and 0.40.6, respectively. Poorer pore abundance and semi-filled natural fractures make it limited in reservoir space and not very good in physical properties. But high content of brittle minerals gives this kind of reservoir fairly good fracability. With comprehensive indexes of 0.400.45, this kind of rock has poorer physical properties, but abundant natural fractures, frequent superposition of argillaceous and silty bands, and inter-contact of quartz, dolomite and clay generate weak stress planes, making this kind of rock easy to break when fracturing. If the overlying and underlying layers are of good physical properties, this medium-terrigenous siliceous shale can be fractured to connect the upper and lower layers to obtain high yield. 2.3.

High terrigenous siliceous shale

Mostly greyish black, this kind of rock has many horizontally-laminated beds, few discontinuous silty bands of millimeter width (Fig. 10a), abundant fractures, mostly horizontal, turning denser, and from semi-filled, unfilled to fully-filled upward (Fig. 10b), occasional vertical fractures, and more graptolite fragments than the former two types of shale (Fig. 10c). Microscopic observation shows this kind of rock has a clay mineral content of less than 20%, silica mineral content of more than 50%, carbonate mineral content of more than 10%, and unsharp boundary between mineral bands of quartz and dolomite (0.2000.275 mm wide) and clay bands (Fig. 10d). Different from the middle terrigenous siliceous shale, in this kind of shale, dolomites can be in star-like even distribu-

Macro and micro features of middle terrigenous siliceous shale in Jiaoshiba shale gas field.

 690 

SHEN Cheng et al. / Petroleum Exploration and Development, 2017, 44(4): 686–695

Fig. 10.

Macro and micro features of high terrigenous siliceous shale in Jiaoshiba area.

tion (Fig. 10e), and there are a few radiolaria and siliceous spicules (Fig. 10f) replaced by calcite. This kind of rock has a physical property index range of 0.400.75 and a fracturing index range of 0.350.60. Its relative high content of organic matter means abundant nanoscale pores, and the high conversion of organic matter enlarges reservoir space, which are conducive to the storage of adsorbed and free gas. Meanwhile, its high brittle mineral content also makes hydraulic fracturing feasible. The comprehensive indexes of this kind of rock range between 0.450.50, indicating good storage capacity and fracability. Besides, abundant fractures semi- and fully-filled by calcite create more macro weak stress planes, and increase of carbonate minerals generates more micro weak stress planes between different miner-

Fig. 11.

als[16,37], both conducive to fracture expanding and connecting more gas-bearing areas. Therefore, this type of shale should be given high priority in development. 2.4.

High authigenic siliceous shale

Greyish black-black on cores, this kind of rock occurs mostly in Wufeng Formation, and have abundant lamellations and many horizontal and vertical fractures filled by calcite (Fig. 11a, 11b), intersecting in U-shape or cross-shape (Fig. 11c, 11d). Microscopic observation shows this kind of rock has clay mineral content of less than 20%, silica mineral content of more than 60% (maximum up to 75%), carbonate mineral content ranging from 8% to 10%, many dark clay laminae interbedding with light mixed quartze and dolomite laminae

Macro and micro features of high authigenic siliceous shale in Jiaoshiba area.

 691 

SHEN Cheng et al. / Petroleum Exploration and Development, 2017, 44(4): 686–695

(Fig. 11e), or silty quartz bands (Fig. 11f), and enriched graptolite fragments without directionality, mostly replaced by silica. Physical property indexes of this kind of rock, ranging from 0.5 to 0.9, indicate good reservoir storage capacity, and fracturing indexes of this kind of rock, between 0.40 and 0.55, indicate good fracability. High TOC is the premise for oil and gas enrichment, while with almost all fractures filled, rich organic matter pores are critical for forming high quality reservoir[36]. The abundant authigenic quartz and U-shaped and cross-shaped fractures create weak stress planes, giving the rock good fracability. With comprehensive index of more than 0.50, this kind of rock has good storage capacity and fracability, so it is currently the main production layer. The four kinds of shales in Wufeng Formation-1st Member of Longmaxi Formation of Sichuan Basin, have different physical properties and fracability. It is concluded from comprehensive analysis that the high authigenic and high terrigenous siliceous shales have better storage capacity and fracability, followed by middle terrigenous siliceous shale, and then low terrigenous siliceous shale.

3. Identification of high-quality reservoirs and evaluation of productivity after fracturing 3.1.

Identification of high-quality reservoirs

Different from the vertical well exploitation mode in conventional reservoirs, shale gas production needs to be realized through horizontal well fracturing, and the conventional storage coefficient may no longer be suitable for evaluating the horizontal wells in shale reservoir. The proportions of four types of rock in 92 horizontal wells of Jiaoshiba area were calculated by the comprehensive index on the basis of logging data. It is found that wells obtained higher test productivity generally when encountering higher proportion of high terrigenous siliceous and high authigenic siliceous shale (Table 2). That is to say, the shale reservoirs with a comprehensive index

of higher than 0.45 have better storage capacity and fracability, which proves the applicability of the comprehensive index, and also indicates that shale reservoir evaluation shouldn’t only consider storage capacity or fracability. 3.2.

Productivity evaluation after fracturing

Shale reservoirs are stage fractured, and the fractured stages have different contributions to the well productivity. The production data of shale gas reservoirs in North America shows that fractured stages which make substantial contribution to well yield are less than 50%. Therefore, the Well Y with 17 fractured stages (Fig. 12a), and SRV monitored by micro-seismic (Fig. 6), was taken as an example to evaluate the horizontal section by the physical property index, fracturing index and new comprehensive index (Fig. 13). On the whole, the 13th to 17th stages, with comprehensive indexes ranging from 0.45 to 0.5, have good storage capacity and fracability, and thus higher yield contribution between (1.02.0)104 m3/d; the 1st, 4th, 9th, 11th and 12th stages, with comprehensive indexes of over 0.5, show good storage capacity but poorer fracability, and moderate contribution to yield, mostly between (0.51)104 m3/d; the 2nd, 3rd, 5th to 8th and 10th stages, with comprehensive indexes below 0.45 and a few ranging from 0.45 to 0.5, have widely variable physical property indexes and fracturing indexes, low or no contribution to yield, mostly below 0.5104 m3/d. Thus, it can be seen that the physical properties and fracability affect productivity jointly: (1) For the study area in this paper, the reservoir with a comprehensive index of more than 0.50 has inherent advantages, was usually selected for fracturing before, but the fracturing fluid lost seriously because of the mass development of natural fractures, in addition, fracturing fluid and power had no contribution to yield when transferred to the nodular limestone with no gas-bearing capacity in Jiancaogou Formation below (Fig. 12b), this reservoir has a SRV from micro-seismic monitoring from (1.53.0)106 m3, reservoir near the wellbore

Table 2.

Statistics on storage capacity, fracability and tested productivity of shales encountered in horizontal wells of Jiaoshiba area

Well

Proportions of different shales in horizontal section/% S1 S2 S3 S4

Physical Fracturing Comprehensive Fracturing property index index stages index

Tested productivity/ Average productivity of (104 m3·d1) each stage/(104 m3·d1)

JY8-2

2.2

5.5

16.5

75.8

0.617

0.485

0.557

21

155.8

7.42

JY48-2

9.6

8.9

29.1

52.4

0.513

0.480

0.500

17

64.5

3.79

JY2-2

0.9

2.4

31.2

65.5

0.586

0.464

0.530

21

67.5

3.21

JY47-1

17.5

45.7

23.5

13.3

0.319

0.417

0.352

15

3.5

0.23

JY8-3

2.2

7.1

38.2

52.5

0.617

0.435

0.529

19

58.2

3.06

JY24-1

6.8

26.8

26.2

40.2

0.461

0.444

0.454

15

21.5

1.43

JY11-1

2.8

18.8

33.3

45.1

0.508

0.454

0.485

17

61.1

3.59

JY11-2

3.4

13.8

20.2

62.6

0.664

0.405

0.529

14

61.9

4.42

JY47-5

5.5

43.8

30.2

20.5

0.459

0.429

0.446

18

6.0

0.33

JY14-3

3.7

9.2

21.7

65.4

0.600

0.464

0.537

18

103.2

5.73

JY6-3

0.7

6.7

28.7

64.2

0.703

0.452

0.575

15

70.4

4.69

JY15-2

2.8

31.1

22.5

43.6

0.481

0.484

0.482

19

37.2

1.96

 692 

SHEN Cheng et al. / Petroleum Exploration and Development, 2017, 44(4): 686–695

Fig. 12.

Fig. 13.

Penetrated layers of the horizontal section and fracturing mode of Well Y in Jiaoshiba area.

Reservoir physical properties, fracability and comprehensive evaluation of horizontal section in Well Y of Jiaoshiba area.

fully stimulated, and moderate yield. (2) The reservoir has both better storage capacity and fracability when ranging from 0.45 to 0.5 in comprehensive index. Under this situation, the horizontal well track is not located in Wufeng Formation with the highest gas content, but located in the layer with the best fracability, fractures from this layer connect overlying and underlying shale layers with higher gas content (Fig. 12c), thus, its SRV, mostly over 3.0106 m3, is larger than the hori-

zontal well section penetrating reservoir with comprehensive index of higher than 0.5, and the reservoir has the most development advantages. (3) With a comprehensive index of less than 0.45, the layer though has higher fracability, poor storage capacity, and low development degree of natural fractures, making it hard to connect adjacent favorable layers and form a larger SRV (less than 1.5106 m3), so, this kind of reservoir has poor development effect in general.

 693 

SHEN Cheng et al. / Petroleum Exploration and Development, 2017, 44(4): 686–695

4.

Conclusions

xij—porosity or TOC corresponding to the ith logging point, %;

The comprehensive index, which reflects the storage capacity and fracability of shale reservoir, has been established based on reservoir geological features from petrophysics experiment and previous research achievements. The shale in Wufeng Formation to Longmaxi Formation in southeastern margin of Sichuan Basin is divided into four types according to the comprehensive index, namely, low terrigenous siliceous, middle terrigenous siliceous, high terrigenous siliceous and high authigenic siliceous shales. Thereinto, high terrigenous siliceous and high authigenic siliceous shales, have better storage capacity and fracability, and are the better shale types for development. According to the reservoir geological features obtained from well logging interpretation, it has been found after field application that the comprehensive index, fully considering the geological and engineering features, has good match with the production result after fracturing. It has also been also found when applied in horizontal intervals evaluation, the moderate and stable comprehensive index indicate the reservoir has better storage capacity and fracability, and thus high productivity. Also, this confirms that the storage capacity and fracability both influence the shale gas reservoir yield.

Yij—normalized porosity or TOC corresponding to the ith logging point; α—Biot coefficient; Δtp, Δts—longitudinal and transverse wave offset time, μs/ft; ρ—density from logging or core, g/cm3; ρf—fluid density, g/cm3; ρm—matrix density, g/cm3; ρk—organic matter (kerogen) density, g/cm3; υmax, υmin—the maximum and minimum Poission’s ratio of single well; υi —Poission’s ratio corresponding to the ith logging point;

e—effective porosity, %; max, min—the maximum and minimum porosity of each well, %; TOClab—average total organic content tested in lab, %; TOCmax,TOCmin—the maximum and minimum TOC of single well, %.

References [1]

CHEN Xinjun, BAO Shujing, HOU Dujie, et al. Methods and key parameters of shale gas resources evaluation. Petroleum Exploration and Development, 2012, 39(5): 566–571.

[2]

CHEN Gengsheng, DONG Dazhong, WANG Shiqian, et al. A preliminary study on accumulation mechanism and enrich-

Nomenclature

ment pattern of shale gas. Natural Gas Industry, 2009, 29(5): 17–21.

a1, b1—weight coefficients;

[3]

e1, e2—original physical property index and fracturing index; e1max, e1min— the maximum and minimum physical property index of a well; e2max, e2min—the maximum and minimum fracturing index of a

LI Yuxi, QIAO Dewu, JIANG Wenli, et al. Gas content of gas-bearing shale and its geological evaluation summary. Geological Bulletin of China, 2011, 30(2): 308–317.

[4]

ALZATE J H, DEEPAK D. Integration of surface seismic, microseismic, and production logs for shale gas characteriza-

well;

tion: Methodology and field application. Interpretation, 2013,

E0—comprehensive index;

1(2): 37–49.

Ej—entropy of porosity or TOC; Emax, Emin—the maximum and minimum elastic modulus of well

[5]

HU R, VERNIK L, NAYVELT L, et al. Seismic inversion for organic richness and fracture gradient in unconventional res-

logging points, MPa;

ervoirs: Eagle Ford Shale, Texas. Leading Edge, 2015, 34(1):

Ei—the elastic modulus corresponded to the ith logging point,

80–84.

MPa; [6]

fn—the nth mineral content, %;

GUO Xusheng, YIN Zhengwu, LI Jinlei. Quantitative seismic

k—the numbers of logging points;

prediction of marine shale gas content, a case study in

Kf— fluid bulk modulus, MPa;

Jiaoshiba area, Sichuan Basin. Oil Geophysical Prospecting,

Km, μm—matrix bulk modulus and shear modulus, MPa;

2015, 50(1): 144–149. [7]

Kn, μn—the nth mineral’s bulk modulus and shear modulus, MPa;

ABOUELRESH M O, SLATT R M. Lithofacies and sequence

KR, μR—Reuss average bulk modulus and shear modulus, MPa;

stratigraphy of the Barnett Shale in east-central Fort Worth

KV, μV—Voigt average bulk modulus and shear modulus, MPa;

Basin, Texas. AAPG Bulletin, 2012, 96(1): 34–43. [8]

Kw, Kg—liquid and gas phase bulk modulus, MPa;

HAN C, JIANG Z, HAN M, et al. The lithofacies and reservoir characteristics of the Upper Ordovician and Lower Silu-

K, μ—shale bulk modulus and shear modulus in saturated fluid

rian black shale in the Southern Sichuan Basin and its periph-

state, MPa;

ery, China. Marine & Petroleum Geology, 2016, 75: 181–191.

max xj, min xj—the maximum and minimum porosity or TOC [9]

in the study area, %;

OU C, RUI R, LI C, et al. Multi-index and two-level evaluation of shale gas reserve quality. Journal of Natural Gas Sci-

p—pressure varied by volumetric strain and flow quantity, MPa;

ence & Engineering, 2016, 35: 1139–1145.

Sw—water saturation of rock, %;

[10] SHI Qiang, CHEN Peng, WANG Xiuqin, et al. A method for

TOC —total organic content, %;

identifying high-productivity intervals in a horizontal shale

Wj—the weight of porosity or TOC;

 694 

SHEN Cheng et al. / Petroleum Exploration and Development, 2017, 44(4): 686–695

gas well and its application: A case study of the Lower Silurian Longmaxi Fm in Weiyuan Shale gas demonstration area,

tion of Jiaoshiba area. Geology of China, 2014, 41(3): 893–901. [25] PENG Yongmin, LONG Shengxiang, HU Zongquan, et al.

Sichuan basin. Natural Gas Industry, 2017, 37(1): 60–65. [11] GUO Z, CHAPMAN M, LI X. A shale rock physics model

Calibration method of shale petrological facies and its appli-

and its application in the prediction of brittleness index, min-

cation in Fuling area, the Sichuan Basin. Oil and Gas Geology,

eralogy, and porosity of the Barnett Shale//2012 SEG Annual

2016, 37(6): 964–970. [26] ZHANG Teng, ZHANG Liehui, TANG Hongming, et al. An

Meeting. Las Vegas, Nevada: SEG, 2012. [12] SHI X, LIU G, JIANG S, et al. Brittleness index prediction

integrated shale pore characteristics method: A case study of

from conventional well logs in unconventional reservoirs us-

the Lower Silurian Longmaxi Formation in the Sichuan Basin. Natural Gas Industry, 2015, 35(12): 19–26.

ing artificial intelligence. IPTC 18776-MS, 2016. [13] PAPANASTASIOU P, ATKINSON C. The brittleness index in

[27] HUANG Renchun, WANG Yan, CHENG Sijie, et al. Optimal selection of logging-based TOC calculation methods of shale

hydraulic fracturing. ARMA 15-489, 2015. [14] GENG Z, CHEN M, JIN T, et al. Brittleness determination of rock using rock physics techniques calibrated with macro

reservoirs: A case study of the Jiaoshiba shale gas field, Sichuan Basin. Natural Gas Industry, 2014, 34(12): 25–32. [28] ZHAO Jinzhou, SHEN Cheng, REN Lan, et al. Quantitative

damage. ARMA 15-268, 2015. [15] LIU Zhishui, SUN Zandong. New brittleness indexes and their

prediction of gas contents in different occurrence states of

application in shale/clay gas reservoir prediction. Petroleum

shale reservoirs: A case study of Jiaoshiba shale gasfield in the Sichuan Basin. Natural Gas Industry, 2017, 37(4): 27–33.

Exploration and Development, 2015, 42(1): 117–124. [16] MATHIA E, RATCLIFFE K. Brittleness index: A parameter to

[29] ZHAO Jinzhou, XU Wenjun, LI Yongming, et al. A new method for fracability evaluation of shale-gas reservoirs.

embrace or avoid?. URTeC 2448745, 2016. [17] ROJAS L F, PEÑA Y Q, CARRILLO Z H C. Brittleness

Natural Gas Geoscience, 2015, 26(6): 1165–1172.

analysis: A methodology to identify sweet spots in shale gas

[30] VOIGT W. Crystal physics. Leipzig: Teubner, 1928: 1–20.

reservoirs. SPE 180955-MS, 2016.

[31] REUSS A. Stresses constant in composite, rule of mixtures for

[18] MITTAL R, ORUGANTI Y, MCBURNEY C. Re-fracturing simulations: Pressure-dependent SRV and shear dilation of

compliance components. Journal of Applied Mathematics and Mechanics, 1929, 9(1): 49–58. [32] HILL R. The elastic behavior of crystalline aggregate. Journal

natural fractures. SPE 178631-MS, 2015. [19] ANDERSON D M, THOMPSON J M, CADWALLADER S

of Process Physical Society, 1952, 65(5): 349–354.

D, et al. Maximizing productive stimulated reservoir volume

[33] BIOT M. Theory of propagation of elastic waves in a fluid

in the Eagle Ford: An infill case study. URTeC 2430961, 2016.

saturated porous solid. The Journal of the Acoustical Society

[20] ZOU Caineng, DING Yunhong, LU Yongjun, et al. Concept,

of America, 1956, 28(2): 168–191.

technology and practice of “man-made reservoir” develop-

[34] MAVKO G, MUKERJI T, DVORKIN J. The rock physics

ment. Petroleum Exploration and Development, 2017, 44(1):

handbook: Tools for seismic analysis of porous media. Cambridge: Cambridge University Press, 2003.

144–154. [21] OTTMANN J, BOHACS K. Conventional reservoirs hold

[35] WANG Shufang, ZOU Caineng, DONG Dazhong, et al. Biogenic silica of organic-rich shale in Sichuan Basin and its sig-

keys to the ‘Un’s. AAPG Explorer, 2014, 35(2): 26. [22] GUO Xusheng. Rules of Two-Factor enrichment for marine shale gas in southern China: Understanding from the Longmaxi Formation shale gas in Sichuan Basin and its surround-

nificance for shale gas. Acta Scientiarum Naturalium Univesitatis Pekinensis, 2014, 50(3): 476–486. [36] WU Lanyu, HU Dongfeng, LU Yongchao, et al. Advantageous shale lithofacies of Wufeng Formation-Longmaxi Formation

ing areas. Acta Geologica Sinica, 2014, 88(7): 1209–1218. [23] GUO Tonglou, ZHANG Hanrong. Formation and enrichment mode of Jiaoshiba shale gas field, Sichuan Basin. Petroleum

in Fuling gas field of Sichuan Basin, SW China. Petroleum Exploration and Development, 2016, 43(2): 1–9. [37] FU Xiaodong, QIN Jianzhong, TENGER, et al. Mineral com-

Exploration and Development, 2014, 41(1): 28–36. [24] GUO Xusheng, HU Dongfeng, WEN Zhidong, et al. Major

ponents of source rocks and their petroleum significance: A

factors controlling the accumulation and high productivity in

case from Paleozoic marine source rocks in the Mid-

marine shale gas in the Lower Paleozoic of Sichuan Basin and

dle-Upper Yangtze region. Petroleum Exploration and De-

its periphery: A case study of the Wufeng-Longmaxi Forma-

velopment, 2011, 38(6): 671–684.

 695 