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Fractured reservoir modeling by discrete fracture network and seismic modeling in the Tarim Basin, China

Fractured reservoir modeling by discrete fracture network and seismic modeling in the Tarim... Pet.Sci.(2011)8:433-445 433 DOI 10.1007/s12182-011-0161-x Fractured reservoir modeling by discrete fracture network and seismic modeling in the Tarim Basin, China 1 2 2 1 Sam Zandong Sun , Zhou Xinyuan , Yang Haijun , Wang Yueying , Wang 1 1 Di and Liu Zhishui Laboratory for Integration of Geology & Geophysics, China University of Petroleum, Beijing 102249, China Research Institute of Exploration & Development, PetroChina Tarim Oilfi eld Company, Korla 841000, China © China University of Petroleum (Beijing) and Springer-Verlag Berlin Heidelberg 2011 Abstract: Fractured reservoirs are an important target for oil and gas exploration in the Tarim Basin and the prediction of this type of reservoir is challenging. Due to the complicated fracture system in the Tarim Basin, the conventional AVO inversion method based on HTI theory to predict fracture development will result in some errors. Thus, an integrated research concept for fractured reservoir prediction is put forward in this paper. Seismic modeling plays a bridging role in this concept, and the establishment of an anisotropic fracture model by Discrete Fracture Network (DFN) is the key part. Because the fracture system in the Tarim Basin shows complex anisotropic characteristics, it is vital to build an effective anisotropic model. Based on geological, well logging and seismic data, an effective anisotropic model of complex fracture systems can be set up with the DFN method. The effective elastic coeffi cients, and the input data for seismic modeling can be calculated. Then seismic modeling based on this model is performed, and the seismic response characteristics are analyzed. The modeling results can be used in the following AVO inversion for fracture detection. Key words: Fractured reservoir, Discrete Fracture Network (DFN), equivalent medium, seismic modeling, azimuth-angle gathers we should investigate the seismic wave field based on the 1 Introduction assumption of anisotropy. When we carry out the seismic The Tarim Basin is a large-scale superimposed basin. For wave forward modeling, fi rst, the fracture models should be example, the Tazhong area has undergone multi-stage tectonic built according to geological statistics based on the geologic movements and crust uplifting. The strata have suffered data, seismic data and well logging data. Secondly, through strong weathering, denudation and corrosion (Wei et al, 2000; the analysis of the fracture models, the fractured reservoir Luo et al, 2005). Therefore, many unconformities are formed. can be equaled to a specifi c anisotropic model and the elastic Moreover, the bedrock of the Tazhong carbonate reservoirs coefficients can be computed. Finally, we can model the is characterized by low porosity and low permeability, and seismic wave field. The modeling result can not only help secondary storage space such as fractures, pores and caves are us to study the seismic wave characteristics and provide the well developed (Yang et al, 2000). As a result, the reservoirs guidance to fi eld acquisition, but also can be utilized for AVO have strong heterogeneity. Carbonate reservoir prediction is inversion to extract fracture information. So the seismic wave a difficult problem, throughout the whole world. However, modeling is an important part. the Tarim Basin is the energy base in China and exploration is of great importance to the national economy and people’s 2 A research concept for fractured reservoir livelihood. So reservoir prediction in the carbonate rock of prediction the Tarim Basin is more signifi cant than ever. Seismic exploration makes use of the relationship between Fractured reservoirs are an important type of oil and the propagation characteristics of the seismic wave and the gas reservoir in the Tarim Basin and they show strong physical properties of the strata. Reservoirs usually show anisotropy. When AVO inversion is carried out to predict anisotropic characteristics when fractures exist. Therefore, fracture development, fractures are often viewed as the Horizontal Transverse Isotropy (HTI) medium. However, the real fracture system is rather complicated. So the theoretical * Corresponding author. email: samzdsun@yahoo.com inversion results are very likely to contain some errors. In Received March 18, 2011 Pet.Sci.(2011)8:433-445 435 45 90 135 180 225 270 315 360 0 200[ 315 45 315 Density log 45 270 90 270 90 01 23 0 0.2 0.4 0.6 0.8 1 Density log 225 135 135 NN Liang1 fracture Liang2 fracture dip directions dip directions 315 45 315 45 With Bias Without Bias With Bias Without Bias 270 90 270 90 04 1 23 0 0.2 0.4 0.6 0.8 1 1:1 1:1 Fault set definition Statistic cabibration Fault set definition Statistic cabibration (a) Fracture analysis of well TZ45 (b) Integrated fracture analysis Liang3 fracture Liang2 fracture (TZ45, TZ86, TZ88) dip directions dip directions Fig. 4 Frac ture analysis in the TZ45 area (a) Statistics of the TZ45 FMI (b) Statistics of the TZ86 FMI 3.3 Fault analysis Fig. 3 St atistics of the FMI in the TZ45 area According to the seismic interpretation results, two groups of faults are developed in TZ45 area: NE-SW (D1) and NW- 3.2 Fracture analysis SE (D2), as shown in Fig. 5. For fault D1, its strike is 204 After the geological model is set up, the cores, FMI and degrees, and the grid dimension is 1.06. The average length fault information from seismic data are needed. According of the fault is 1020 m, and the dip Fischer coeffi cient is 2.6. to the geological statistics, the information such as fracture For fault D2, its strike is 85 degrees, and the grid dimension orientation and dip angle are analyzed. The fracture analysis is 1.23. The average length of the fault is 1193 m, and the dip method includes single-well analysis and multi-well Fischer coeffi cient is 2.9. If D1 and D2 can be assumed to be integrated analysis. vertical faults, D2 is cut by D1. The fracture analysis result of well TZ45 is shown in Fig. 3.4 Discrete fracture network (DFN) modeling 4(a), and the dip direction is recognized to be mainly NE- SW. Both high angle and low angle fracture exist in well Through analyzing the FMI data of the three wells and the TZ45. The high angle ranges from 65 degrees to 85 degrees, fault information, the spatial distribution characteristics can while the low angle ranges from 5 degrees to 20 degrees. be predicted and the DFN model can be built up. The DFN An integrated fracture analysis from wells TZ45, TZ86 and model of the block fractures around well TZ45 is shown in TZ88 is shown in Fig. 4(b). Two groups of fractures can be Fig. 6. The fractures with dip direction of NW-SE are well observed in the TZ45 area. One dip direction is NE-SW, with developed, which are consistent with the FMI interpretation the dip angle ranging from 45 degrees to 85 degrees, and the results. other is NW-SE, with the dip angle ranging from 10 degrees Based on the DFN model established, the fracture to 75 degrees. parameters such as fracture azimuth, strike, orientation and Select orientation: Select orientation: Fault’s orientation 0 200 400 600 800 Fault’s orientation 0 200 400 600 800 Select all Invert selection Select all Invert selection fault set definition Throw profiles Box counting length (a) D1 Fault (b) D2 Fault Fig. 5 Fault analysis in the TZ45 area Pet.Sci.(2011)8:433-445 437 4.2 Acquisition s ystem 22 22 ª º F G G (4ED G G ) ( G G ED )(1 P ) (15 ) rskl rk sl rl sk rs kl ¬ ¼ During the process of wavefi eld modeling, the acquisition (4) system is shown in Fig. 9. The circle point in the center represents the reflection point, and shots and receivers are where, α, β and μ respectively represents the v , v and shear p s located on the intersections between circles and radial lines. modulus of the background medium. δ is the Kronecker ij Concentric circles with equal distances represent different 1 2 symbol. During the calculation process of C and C , fracture offsets, while the circle point represents shot and receiver. parameters such as fracture density derived through DFN will be used. In this way, elastic parameters can be worked out eventually. 4 Seismic modeling of a fractured reservoir in the Tarim Basin 4.1 Calculation of elastic coeffi cients By using the real geological, well logging and seismic data in the Tarim Basin, the DFN model is built. The fracture parameters are then derived from the DFN and are listed in Table 1. These parameters will be used to calculate the equivalent elastic coeffi cients. Fig. 9 Acquisition system Table 1 Fracture parameters obtained from DFN model Fracture Aspect Fracture Density N N N x y z radius ratio group 4.3 Wavefi eld characteristics 65.19 0.001 0.083 0.017912 -0.07679 0.996886 1 Using the parameters given in 4.1, staggered-grid high- 63.83 0.001 0.35 -0.08912 -0.9779 0.189109 2 order finite difference forward modeling is conducted. The characteristics of the azimuthal gathers in different offsets are 60.22 0.001 0.067 -0.67422 -0.5059 -0.53805 3 analyzed, the wavefi eld features are provided in Fig. 10 and 62.91 0.001 0.09 -0.17247 -0.15133 0.973321 4 Fig. 11. From Fig. 10 and Fig. 11, we can get the following 61.16 0.001 0.28 -0.92245 -0.26419 0.281571 5 conclusions. The wavefield features are rather complex for 63.97 0.001 0.08 -0.23245 -0.12499 -0.96454 6 this quasi TTI anisotropic medium. For data with the same offset, the traveling time of reflection wave changes versus Based on the fracture parameters obtained from the DFN azimuth. The time difference between the minimum and the model analysis, equivalent elastic coeffi cients are calculated maximum traveling time of the P-P wave increases as the according to the Hudson theory. The elastic coeffi cients are offset rises. Shear wave splitting exists when the shear wave shown in Eq. (5). From the elastic coefficient matrix we propagates through the quasi TTI medium (as shown by the can get the following conclusion: the fractures in this study reflected shear wave PS , PS and the direct shear wave S , 1 2 1 area are complex and is not the standard HTI or TTI (Tilted S ). From what we have mentioned above, we fi nd that when Transverse Isotropy) model, and here we defi ne it as a quasi the data processing is conducted, as the velocity in different TTI model. On the basis of this elastic coefficient matrix, azimuths varies, data processing toward different azimuths we conduct the wave fi eld forward modeling using the fi nite is necessary. The wavefield obtained through the forward difference method. The model which contains two horizontal modeling provides the input data for the following AVO layers is designed. The fi rst layer is the quasi TTI medium, inversion method, which acts as an important bridge in the and the second layer is isotropic, where the P-wave velocity fracture prediction fl ow shown in Fig. 1. is 3,000.0 m/s, S-wave velocity is 1,500.0 m/s and the density is 2,000.0 kg/m . 5 Seismic modeling of a theoretical fracture model 25.2269 ª º In order to further analyze the seismic responses of the « » 10.5544 25.5865 fractured reservoir, a theoretical fracture model is designed, « » « » 10.6918 10.2232 25.5492 which contains two layers. The first layer is an isotropic « » medium, and the second layer is a monoclinic anisotropic 0.1725 0.4684 0.7059 5.0638 « » medium. The model parameters and fracture parameters are « » 0.6108 0.1236 0.7766 0.2024 5.7258 « » shown in Table 2 and Table 3. Based on this model, seismic 0.0737  0.6231 0.4449 0.1602 0.1930 5.2015 « » ¬ ¼ modeling is performed using the staggered-grid high-order fi nite difference method (Cerjan et al, 1985; Wang et al, 2005; (5) 438 Pet.Sci.(2011)8:433-445 Azimuth angle, ° Azimuth angle, ° 0 25 50 75 100 125 150 175 0 25 50 75 100 125 150 175 0.0 0.0 0.2 0.2 P P 0.4 0.4 t, s t, s PP PP 0.6 0.6 S S 1 1 S S 2 0.8 2 PS PS 0.8 1 1 PS PS 2 2 1.0 1.0 Fig. 10 Az imuthal gathers of x and z components at the offset of 1000 m Azimuth angle, ° Azimuth angle, ° 0 25 50 75 100 125 150 175 0 25 50 75 100 125 150 175 0.0 0.0 0.2 0.2 0.4 0.4 P P t, s t, s 0.6 0.6 PP PP 0.8 0.8 S S 1 1 1.0 1.0 Fig. 11 Azim uthal gathers of x and z components at the offset of 1800 m Dong et al, 2000). The acquisition system is the same as 5.1 Wavefi eld of a monoclinic medium shown in Fig. 9. We select the parameters in model 1 (Table 2). Fig. 12 shows the angle gathers with different offsets of the model. Table 2 Model 1 parameters From 0º to 180º, the reflection travel-time curves show Model Layer V , m/s V , m/s ρ, kg/m negative sine characteristics. The longest travel-time of the p s PP wave appears at about 55º and the shortest appears at Layer 1 isotropy 2800.0 1800.0 2300.0 Model 1 about 145º. With the offset increasing, the difference between Layer 2 (clastic rock) the shortest and the longest increases. At about 55º, the PS anisotropy 3500.0 2000.0 2300.0 (base-rock) wave travels at the slow S wave velocity and there is only PS whose energy is very strong. At about 145º, the PS wave Table 3 Fracture parameters travels at the fast S wave velocity and there is only PS whose energy is also very strong. And at other azimuth angles, PS Normal direction, º Radius, m Aspect ratio Density and PS exist at the same time, but their energies are weak. So 1 0 1.0 0.001 0.01 converted waves are sensitive to fractures and it is feasible to use the converted waves to detect the fractures. Moreover, the 2 60 1.0 0.001 0.1 azimuth must be considered during processing the azimuth- Pet.Sci.(2011)8:433-445 439 angle gathers. different fl uids in fractures. Comparing with Fig. 12(b), Fig. 13 and Fig. 14, we fi nd that when the fractures are fi lled with 5.2 Infl uence of fl uids the same fl uid, but the base rock is different, the difference between the shortest and the longest reflection travel-time We still select the parameters in model 1 (Table 2). For decreases from clastic base-rock to carbonate base-rock. analyzing the fluid influence, we respectively use oil and Therefore it is easier to distinguish gas from oil and water in water to fi ll the fractures. Fig. 12(b) and Fig. 13 show that: clastic rock than in carbonate rock. from 0º to 180º, when fractures are filled with oil or water, the PP reflection travel-time curves also have negative sine Table 4 Model 2 parameters characteristics. Regardless of whether the fractures are filled with oil or water, the PP, PS and PS show similar 1 2 Model Layer V , m/s V , m/s ρ, kg/m p s characteristics. When fractures are filled with oil or water, the difference between the longest and shortest travel time Layer 1 isotropy 4800.0 3200.0 2600.0 Model 2 is smaller than that when fractures are filled with gas. In Layer 2 (carbonate rock) anisotropy 6000.0 3800.0 2700.0 summary, when the fractures are filled with gas, the model (base-rock) displays obvious azimuth-anisotropy, while when fi lled with oil or water, the azimuth-anisotropy is weak. 6 The reflection coefficients characteristics 5.3 Infl uence of base-rock of a fractured reservoir For studying the base-rock influence, the model is changed from model 1 to model 2 (Table 4). The base-rock Spherical divergence exists when performing seismic of the fractured reservoir is changed from clastic rock to modeling, so it is not suitable for amplitude analysis. To do carbonate rock, and the fracture parameters are kept the same this more easily, the Zoeppritz equation is applied in this (Table 3). Fig. 14 shows the modeling results of model 2 with paper to analyze the refl ection coeffi cient characteristics of a Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 P P 0.5 0.5 t, s t, s PP PP 1.0 1.0 PS PS 1 1 PS 2 PS 1.5 1.5 (a) Angle gathers of x and z components at offset 1200m Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 0.5 0.5 P P t, s t, s PP PP 1.0 1.0 PS PS PS PS 2 1.5 1.5 (b) Angle gathers of x and z components at offset 1980m Fig. 12 Angle gathers of x, z components at different offsets in clastic rock 440 Pet.Sci.(2011)8:433-445 Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 0.5 P 0.5 P t, s t, s PP PP 1.0 1.0 PS PS PS PS 2 1.5 1.5 (a) Azimuth-angle gathers x and z components with fractures filled with oil Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 0.5 P P 0.5 t, s t, s PP PP 1.0 1.0 PS PS 1 1 PS PS 2 2 1.5 1.5 (b) Azimuth-angle gathers x and z components with fractures filled with water Azimuth-angle gathers with 1980m offset in clastic rock Fig. 13 fractured reservoir. Refl ection and transmission are produced represent the transmission coefficients of the P-wave and when a seismic wave arrives at the elastic interface. The converted S-wave. seismic wave is considered as a plane wave. According to 6.1 Characteristics of reflection coefficients with Huygen’s principle, the incidence, refl ection, and transmission incident angles waves should satisfy Snell’s Law as well as the displacement continuity and the stress continuity on the boundary (Wu, We select the model 1 (Table 2) and calculate the refl ection 2006). Then, the Zoeppritz equation which describes the coeffi cients (Fig. 15). From Fig. 15, the following conclusions reflection coefficient and transmission coefficient under can be derived. For a certain azimuth, the reflection anisotropic condition can be obtained. For example, the coefficient changes with the incident angle (denoted by the Zoeppritz equation of a compression wave under anisotropic slowness), and if the azimuth angle changes, the reflection conditions is shown as follows: coefficient also changes. The lines on the 30º and 120º are respectively perpendicular and parallel to the bisecting line sinT cosT  sinTT cos R  sinT ª ºª º ªº PR SR PT ST PP PR of the included angle between the two groups of fractures, « »« » «» cosT  sinT cos TT sin R cosT and the P-wave velocity is smallest on 30º and is biggest on PR SR PT ST PS PR « »« » « » 120º, so the refl ection coeffi cient is different obviously from « »« » « » A A A AT B 1 2 3 4 PP 1 « »« » «» the slowness of 0.25 s/m to the slowness of 0.35 s/m. The A A A AT B ¬ 5 6 7 8 ¼¬ PS¼ ¬¼ 2 lines on the 90º and the 150º are respectively parallel to the (6) fracture strikes, and the corresponding refl ection coeffi cients where, A and B are function of elastic parameters, incidence are different because the fracture intensities are not the same i i angle and transmission angle on both sides of the interface. for fractures in these two directions. Fig. 15(e) displays R and R respectively represent the refl ection coeffi cients the differences of the PP reflection coefficients on different PP PS of the P-wave and converted S-wave. T and T respectively azimuth angles and the differences on middle offsets are more PP PS Pet.Sci.(2011)8:433-445 441 Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 0.5 S 0.5 t, s PP t, s PP 1.0 PS 1.0 PS PS PS 2 2 1.5 1.5 (a) Azimuth-angle gathers x and z components with fractures filled with gas Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 P P 0.5 0.5 PP t, s PP t, s 1.0 1.0 PS PS PS PS 1.5 1.5 (b) Azimuth-angle gathers x and z components with fractures filled with oil Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 P P 0.5 0.5 t, s PP t, s PP 1.0 1.0 PS PS 1 1 PS PS 1.5 1.5 (c) Azimuth-angle gathers x and z components with fractures filled with water Fig. 14 Azimuth-angle gathers with 1980m offset in carbonate rock obvious than those on near offsets. incident angle. Slowness of 0.198 s/m, 0.286 s/m, 0.358 s/m and 0.418 s/m are selected as examples, the PP reflection 6.2 Characteristics of reflection coefficients with coeffi cient changes gently at 0.198 s/m, 0.358 s/m and 0.418 azimuth angles s/m, while the PP refl ection coeffi cient changes dramatically at 0.286 s/m. The azimuth AVO characteristics exist on the Fig. 16 shows the reflection coefficients changing with top interface of the fractured reservoirs, and we might be able the azimuth angles for the model 1 (Table 2). The refl ection to use this characteristic to invert fracture development. coeffi cient changes with the azimuth angle for a certain fi xed 442 Pet.Sci.(2011)8:433-445 1.0 1.0 0.9 0.9 PP 0.8 0.8 PSV PP 0.7 PSH 0.7 PSV SVP 0.6 0.6 PSH SVSV 0.5 0.5 SVP SVSH 0.4 SVSV 0.4 SHP SVSH 0.3 SHSV 0.3 SHP SHSH 0.2 0.2 SHSV 0.1 SHSH 0.1 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 Slowness, s/m Slowness, s/m (E $]LPXWKDQJOHRIÛ (D $]LPXWKDQJOHRIÛ 1.0 1.0 0.9 0.9 PP PP 0.8 0.8 PSV PSV 0.7 0.7 PSH PSH SVP SVP 0.6 0.6 SVSV SVSV 0.5 0.5 SVSH SVSH 0.4 0.4 SHP SHP 0.3 0.3 SHSV SHSV SHSH SHSH 0.2 0.2 0.1 0.1 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 Slowness, s/m Slowness, s/m (G $]LPXWKDQJOHRIÛ (F $]LPXWKDQJOHRIÛ 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 Slowness, s/m (e) PP reflection coefficients Fig. 15 Diagrams showing the refl ection coeffi cients changing with incident angles in clastic reservoi r reflection coefficient is 0.2 at 0.28 s/m when filled with oil 6.3 Infl uence of fl uid properties or water. From Fig. 17(a) and Fig. 17(b), we fi nd that when For analyzing the influence of fluid properties on the azimuth is 30º or 120º, the PP refl ection coeffi cient when refl ection coeffi cients, the fractures of the model 1 (Table 2) filled with oil is similar with that when filled with water. are fi lled respectively with oil and water. At the 30º azimuth, Therefore, it is very difficult to distinguish oil from water selecting the slowness area from 0.05 s/m to 0.25 s/m, from the refl ection coeffi cient. when the fractures are filled with gas (Fig. 15(b)), the PP reflection coefficient decreases apparently almost to 0.06. 6.4 Infl uence of base-rocks However, when the fractures are fi lled with oil or water (Fig. For analyzing the influence of the base-rocks, we select 17(a) and Fig. 17(b)), the PP refl ection coeffi cient decreases the model 2 (Table 4) with carbonate rock as base-rock. As apparently almost to 0.09. At the slowness from 0.20 s/m to shown in Fig. 18, the curves are different when fi lled with gas 0.30 s/m, the PP reflection coefficient when filled with gas compared to fi lled with oil or water at 30º and 120º. So we is smaller than that when fi lled with oil or water. The law is can distinguish gas from oil and water, but oil and water are the same at the 120º azimuth. For example, the PP refl ection coeffi cient is 0.2 at 0.3 s/m when fi lled with gas, while the PP almost indistinguishable from the PP refl ection coeffi cient. Amplitude Amplitude Amplitude Amplitude Amplitude Pet.Sci.(2011)8:433-445 443 0.7 0.7 PP 0.6 0.6 PP PSV PSV 0.5 PSH 0.5 PSH SVP SVP 0.4 SVSV 0.4 SVSV SVSH 0.3 SVSH 0.3 SHP SHP SHSV 0.2 SHSV 0.2 SHSH SHSH 0.1 0.1 0.0 0.0 0 40 80 120 160 200 240 280 320 360 0 40 80 120 160 200 240 280 320 360 Angle, º Angle, º (a) Slowness 0.198 s/m (b) Slowness 0.286 s/m 1.0 0.7 0.9 0.6 PP PP 0.8 PSV PSV 0.7 0.5 PSH PSH 0.6 SVP SVP 0.4 0.5 SVSV SVSV SVSH 0.3 0.4 SVSH SHP SHP 0.3 SHSV 0.2 SHSV 0.2 SHSH SHSH 0.1 0.1 0.0 0.0 0 40 80 120 160 200 240 280 320 360 0 40 80 120 160 200 240 280 320 360 Angle, º Angle, º (c) Slowness 0.358 s/m (d) Slowness 0.418 s/m Fig. 16 Diagrams showing the refl ection coeffi cients changing with azimuth angles in clastic reservoir 1.0 1.0 0.9 0.9 0.8 0.8 PP PP 0.7 0.7 PSV PSV 0.6 0.6 PSH PSH SVP SVP 0.5 0.5 SVSV SVSV 0.4 0.4 SVSH SVSH 0.3 0.3 SHP SHP SHSV 0.2 SHSV 0.2 SHSH SHSH 0.1 0.1 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 Slowness, s/m Slowness, s/m (a) Refl ection coeffi cients at 30º and 120 º azimuth with fractures fi lled with oil 1.0 1.0 0.9 0.9 0.8 0.8 PP PP 0.7 0.7 PSV PSV 0.6 0.6 PSH PSH SVP 0.5 0.5 SVP SVSV 0.4 0.4 SVSV SVSH SVSH 0.3 0.3 SHP SHP 0.2 SHSV 0.2 SHSV SHSH 0.1 0.1 SHSH 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 Slowness, s/m Slowness, s/m (b) Refl ection coeffi cients at 30˚and 120˚azimuth with fractures fi lled with water Diagrams showing the refl ection coeffi cients changing with slowness with fractures fi lled with different fl uids in clastic reservoir Fig. 17 Amplitude Amplitude Amplitude Amplitude Amplitude Amplitude Amplitude Amplitude 444 Pet.Sci.(2011)8:433-445 1.0 1.0 0.9 0.9 PP PP 0.8 0.8 PSV PSV 0.7 0.7 PSH PSH 0.6 0.6 SVP SVP 0.5 0.5 SVSV SVSV SVSH SVSH 0.4 0.4 SHP SHP 0.3 0.3 SHSV SHSV 0.2 0.2 SHSH SHSH 0.1 0.1 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.00 0.05 0.10 0.15 0.20 0.25 0.30 Slowness, s/m Slowness, s/m (a) Refl ection coeffi cients at 30˚and 120˚azimuth with fractures fi lled with gas 1.0 1.0 0.9 0.9 0.8 0.8 PP PP 0.7 0.7 PSV PSV 0.6 0.6 PSH PSH 0.5 0.5 SVP SVP 0.4 SVSV SVSV 0.4 0.3 SVSH SVSH 0.3 SHP SHP 0.2 0.2 SHSV SHSV 0.1 0.1 SHSH SHSH 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.00 0.05 0.10 0.15 0.20 0.25 0.30 Slowness, s/m Slowness, s/m (b) Refl ection coeffi cients at 30˚and 120˚azimuth with fractures fi lled with oil 1.0 1.0 0.9 0.9 PP 0.8 0.8 PSV 0.7 0.7 PP PSH PSV 0.6 SVP 0.6 PSH 0.5 SVSV 0.5 SVP SVSH 0.4 0.4 SVSV SHP 0.3 SVSH SHSV 0.3 0.2 SHP SHSH 0.2 SHSV 0.1 0.1 SHSH 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.00 0.05 0.10 0.15 0.20 0.25 0.30 Slowness, s/m Slowness, s/m (c) Refl ection coeffi cients at 30˚and 120˚azimuth with fractures fi lled with water Diagrams showing refl ection coeffi cients changing with slowness with fractures fi lled with different fl uids in carbonate reservoir Fig. 18 The modeling result shows that for data with the same 7 Conclusions offset, the traveling time of the refl ection wave changes with 1) The geological, seismic and well log data respectively the azimuth. Additionally, the time difference between the describe the fractures at different scales, and an integration of minimum and the maximum traveling time of the P-P wave the three can be used to build up the fracture models by the increases as the offset rises. Shear wave splitting exists when DFN method and the fracture parameters can be calculated. a shear wave propagates through the quasi TTI medium. The The equivalent medium theory uses the fracture parameters wavefi eld through the forward modeling not only helps us to to compute the elastic coeffi cients of the anisotropic medium, understand the seismic response of the fractured reservoirs, which is an important bridge to connect the microscopic but also provides the input data for the study of the fracture fractures and macroscopic reservoir modeling. inversion method. 2) Using the real geological, seismic and well longing 3) From an analysis of the monoclinic anisotropy, we data, the DFN model is built to calculate the equivalent elastic learn some characteristics of the reflection coefficients, coefficient. The wavefield forward modeling is conducted the slowness and the azimuth angles. The PP reflection using the staggered-grid high-order fi nite difference method. coeffi cients in middle offsets are sensitive to the fractures, so Amplitude Amplitude Amplitude Amplitude Amplitude Amplitude Pet.Sci.(2011)8:433-445 445 Luo J H, Zhou X Y, Qiu B, et al. Mesozoic-Cenozoic fi ve tectonic events the middle offsets are better than the others when inverting and their petroleum geologic signifi cances in the West Tarim Basin. the fractures. The seismic data are more sensitive to gas than Petroleum Exploration and Development. 2005. 32(1): 18-22 (in oil or water, so gas can be distinguished from oil and water, Chinese) while oil can not be distinguished from water. When the base- Tsv ankin I. Seismic Signatures and Analysis of Reflection Data in rocks are different, it is much easier to distinguish the fl uids Anisotropic Media. Amsterdam: Elsevier Science. 2005. 14-252 in the clastic rock than in carbonate rock. Azimuth anisotropy Wan g D L, He Q D and Han L G. Multi-azimuth three-component can be used in detecting fractured reservoirs. Theoretically, surface seismic modeling for cracked monoclinic media. Chinese the acquisition system for anisotropy detection should be full- Journal of Geophysics. 2005. 48(2): 386-393 (in Chinese) azimuth and have equal fold. Data processing toward different Wan g S M, Jin Z J and Xie Q L. Transforming effect of deep fl uids on azimuth is necessary as the velocities in different azimuth are carbonate reservoirs in the well TZ45 region. Geological Review. not the same. 2004. 50(5): 543-547 (in Chinese) Wan g Z Y, Li Y P, Chen J S, et al. Characters of atmospheric diagenetic lens along middle-late Ordovician carbonate shelf margin in central Acknowledgements Tarim area. Chinese Journal of Geology. 2002. 37(S1): 152-160 (in The work is co-supported by the National Basic Research Chinese) Program of China (Grant No.2011CB201103) and the Wan g Z Y, Yan W, Zhang Y F, et al. Diagenesis and porosity evolution of National Science and Technology Major Project (Grant upper Ordovician platform margin reefs and grain banks reservoirs in the Tazhong area. Xinjiang Geology. 2007. 25(3): 288-290 (in No.2011ZX05004003). The authors would like to thank the Chinese) Laboratory for Integration of Geology and Geophysics (LIGG) Wei G Q, Jia C Z, Song H Z, et al. Ordovician structural-depositional at China University of Petroleum for the permission to model and prediction for profitable crack reservoirs of carbonate publish this work and the Tarim Oilfi eld Co., PetroChina for rock in the Tazhong area, Tarim Basin. Acta Sedimentologica Sinica. their help in providing fi eld data. Also, Shell Co. is thanked 2000. 18(3): 408-413 (in Chinese) for the fi nancial assistant to the fi rst author. Wu G C. Seismic Wave Propagation and Imaging in an Anisotropic Medium. Dongying: China University of Petroleum Press. 2006. 43- References 156 (in Chinese) Yan g H J, Liu S, Li Y P, et al. Analysis of the middle-upper Ordovician Cer jan C, Kosloff D, Kosloff R, et al. A nonrefl ecting boundary condition carbonate reservoirs in the Tazhong area. Marine Origin Petroleum for discrete acoustic and elastic wave equations. Geophysics. 1985. Geology. 2000. 5(1-2): 73-83 (in Chinese) 50(4): 705-708 Zha o Z J, Wang Z M, Wu X N, et al. Genetic types and distribution Cra mpin S. Effective anisotropic elastic constants for wave propagation forecast of available carbonate reservoirs in Ordovician in the central through cracked solids. Geophysical Journal of the Royal area of Tarim Basin. Petroleum Geology and Experiment. 2007. Astronomical Society. 1984. 76(1): 135-145 29(1): 40-46 (in Chinese) Don g L G, Ma Z T, Cao J Z, et al. A staggered-grid high-order difference Zhu D Y, Hu W X, Song Y C, et al. Fluoritization in Tazhong 45 method of one-order elastic wave equation. Chinese Journal of reservoir: characteristics and its effect on the reservoir bed. Acta Geophysics. 2000. 43(3): 411-419 (in Chinese) Petrologica et Mineralogica. 2005. 24(3): 205-215 (in Chinese) Hud son J A. A higher order approximation to the wave propagation constants for a cracked solid. Geophysical Journal of the Royal (Edited by Hao Jie) Astronomical Society. 1986. 87(1): 265-274 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Petroleum Science Springer Journals

Fractured reservoir modeling by discrete fracture network and seismic modeling in the Tarim Basin, China

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Springer Journals
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Copyright © 2011 by China University of Petroleum (Beijing) and Springer-Verlag Berlin Heidelberg
Subject
Earth Sciences; Mineral Resources; Industrial Chemistry/Chemical Engineering; Industrial and Production Engineering; Energy Economics
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1672-5107
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1995-8226
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10.1007/s12182-011-0161-x
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Abstract

Pet.Sci.(2011)8:433-445 433 DOI 10.1007/s12182-011-0161-x Fractured reservoir modeling by discrete fracture network and seismic modeling in the Tarim Basin, China 1 2 2 1 Sam Zandong Sun , Zhou Xinyuan , Yang Haijun , Wang Yueying , Wang 1 1 Di and Liu Zhishui Laboratory for Integration of Geology & Geophysics, China University of Petroleum, Beijing 102249, China Research Institute of Exploration & Development, PetroChina Tarim Oilfi eld Company, Korla 841000, China © China University of Petroleum (Beijing) and Springer-Verlag Berlin Heidelberg 2011 Abstract: Fractured reservoirs are an important target for oil and gas exploration in the Tarim Basin and the prediction of this type of reservoir is challenging. Due to the complicated fracture system in the Tarim Basin, the conventional AVO inversion method based on HTI theory to predict fracture development will result in some errors. Thus, an integrated research concept for fractured reservoir prediction is put forward in this paper. Seismic modeling plays a bridging role in this concept, and the establishment of an anisotropic fracture model by Discrete Fracture Network (DFN) is the key part. Because the fracture system in the Tarim Basin shows complex anisotropic characteristics, it is vital to build an effective anisotropic model. Based on geological, well logging and seismic data, an effective anisotropic model of complex fracture systems can be set up with the DFN method. The effective elastic coeffi cients, and the input data for seismic modeling can be calculated. Then seismic modeling based on this model is performed, and the seismic response characteristics are analyzed. The modeling results can be used in the following AVO inversion for fracture detection. Key words: Fractured reservoir, Discrete Fracture Network (DFN), equivalent medium, seismic modeling, azimuth-angle gathers we should investigate the seismic wave field based on the 1 Introduction assumption of anisotropy. When we carry out the seismic The Tarim Basin is a large-scale superimposed basin. For wave forward modeling, fi rst, the fracture models should be example, the Tazhong area has undergone multi-stage tectonic built according to geological statistics based on the geologic movements and crust uplifting. The strata have suffered data, seismic data and well logging data. Secondly, through strong weathering, denudation and corrosion (Wei et al, 2000; the analysis of the fracture models, the fractured reservoir Luo et al, 2005). Therefore, many unconformities are formed. can be equaled to a specifi c anisotropic model and the elastic Moreover, the bedrock of the Tazhong carbonate reservoirs coefficients can be computed. Finally, we can model the is characterized by low porosity and low permeability, and seismic wave field. The modeling result can not only help secondary storage space such as fractures, pores and caves are us to study the seismic wave characteristics and provide the well developed (Yang et al, 2000). As a result, the reservoirs guidance to fi eld acquisition, but also can be utilized for AVO have strong heterogeneity. Carbonate reservoir prediction is inversion to extract fracture information. So the seismic wave a difficult problem, throughout the whole world. However, modeling is an important part. the Tarim Basin is the energy base in China and exploration is of great importance to the national economy and people’s 2 A research concept for fractured reservoir livelihood. So reservoir prediction in the carbonate rock of prediction the Tarim Basin is more signifi cant than ever. Seismic exploration makes use of the relationship between Fractured reservoirs are an important type of oil and the propagation characteristics of the seismic wave and the gas reservoir in the Tarim Basin and they show strong physical properties of the strata. Reservoirs usually show anisotropy. When AVO inversion is carried out to predict anisotropic characteristics when fractures exist. Therefore, fracture development, fractures are often viewed as the Horizontal Transverse Isotropy (HTI) medium. However, the real fracture system is rather complicated. So the theoretical * Corresponding author. email: samzdsun@yahoo.com inversion results are very likely to contain some errors. In Received March 18, 2011 Pet.Sci.(2011)8:433-445 435 45 90 135 180 225 270 315 360 0 200[ 315 45 315 Density log 45 270 90 270 90 01 23 0 0.2 0.4 0.6 0.8 1 Density log 225 135 135 NN Liang1 fracture Liang2 fracture dip directions dip directions 315 45 315 45 With Bias Without Bias With Bias Without Bias 270 90 270 90 04 1 23 0 0.2 0.4 0.6 0.8 1 1:1 1:1 Fault set definition Statistic cabibration Fault set definition Statistic cabibration (a) Fracture analysis of well TZ45 (b) Integrated fracture analysis Liang3 fracture Liang2 fracture (TZ45, TZ86, TZ88) dip directions dip directions Fig. 4 Frac ture analysis in the TZ45 area (a) Statistics of the TZ45 FMI (b) Statistics of the TZ86 FMI 3.3 Fault analysis Fig. 3 St atistics of the FMI in the TZ45 area According to the seismic interpretation results, two groups of faults are developed in TZ45 area: NE-SW (D1) and NW- 3.2 Fracture analysis SE (D2), as shown in Fig. 5. For fault D1, its strike is 204 After the geological model is set up, the cores, FMI and degrees, and the grid dimension is 1.06. The average length fault information from seismic data are needed. According of the fault is 1020 m, and the dip Fischer coeffi cient is 2.6. to the geological statistics, the information such as fracture For fault D2, its strike is 85 degrees, and the grid dimension orientation and dip angle are analyzed. The fracture analysis is 1.23. The average length of the fault is 1193 m, and the dip method includes single-well analysis and multi-well Fischer coeffi cient is 2.9. If D1 and D2 can be assumed to be integrated analysis. vertical faults, D2 is cut by D1. The fracture analysis result of well TZ45 is shown in Fig. 3.4 Discrete fracture network (DFN) modeling 4(a), and the dip direction is recognized to be mainly NE- SW. Both high angle and low angle fracture exist in well Through analyzing the FMI data of the three wells and the TZ45. The high angle ranges from 65 degrees to 85 degrees, fault information, the spatial distribution characteristics can while the low angle ranges from 5 degrees to 20 degrees. be predicted and the DFN model can be built up. The DFN An integrated fracture analysis from wells TZ45, TZ86 and model of the block fractures around well TZ45 is shown in TZ88 is shown in Fig. 4(b). Two groups of fractures can be Fig. 6. The fractures with dip direction of NW-SE are well observed in the TZ45 area. One dip direction is NE-SW, with developed, which are consistent with the FMI interpretation the dip angle ranging from 45 degrees to 85 degrees, and the results. other is NW-SE, with the dip angle ranging from 10 degrees Based on the DFN model established, the fracture to 75 degrees. parameters such as fracture azimuth, strike, orientation and Select orientation: Select orientation: Fault’s orientation 0 200 400 600 800 Fault’s orientation 0 200 400 600 800 Select all Invert selection Select all Invert selection fault set definition Throw profiles Box counting length (a) D1 Fault (b) D2 Fault Fig. 5 Fault analysis in the TZ45 area Pet.Sci.(2011)8:433-445 437 4.2 Acquisition s ystem 22 22 ª º F G G (4ED G G ) ( G G ED )(1 P ) (15 ) rskl rk sl rl sk rs kl ¬ ¼ During the process of wavefi eld modeling, the acquisition (4) system is shown in Fig. 9. The circle point in the center represents the reflection point, and shots and receivers are where, α, β and μ respectively represents the v , v and shear p s located on the intersections between circles and radial lines. modulus of the background medium. δ is the Kronecker ij Concentric circles with equal distances represent different 1 2 symbol. During the calculation process of C and C , fracture offsets, while the circle point represents shot and receiver. parameters such as fracture density derived through DFN will be used. In this way, elastic parameters can be worked out eventually. 4 Seismic modeling of a fractured reservoir in the Tarim Basin 4.1 Calculation of elastic coeffi cients By using the real geological, well logging and seismic data in the Tarim Basin, the DFN model is built. The fracture parameters are then derived from the DFN and are listed in Table 1. These parameters will be used to calculate the equivalent elastic coeffi cients. Fig. 9 Acquisition system Table 1 Fracture parameters obtained from DFN model Fracture Aspect Fracture Density N N N x y z radius ratio group 4.3 Wavefi eld characteristics 65.19 0.001 0.083 0.017912 -0.07679 0.996886 1 Using the parameters given in 4.1, staggered-grid high- 63.83 0.001 0.35 -0.08912 -0.9779 0.189109 2 order finite difference forward modeling is conducted. The characteristics of the azimuthal gathers in different offsets are 60.22 0.001 0.067 -0.67422 -0.5059 -0.53805 3 analyzed, the wavefi eld features are provided in Fig. 10 and 62.91 0.001 0.09 -0.17247 -0.15133 0.973321 4 Fig. 11. From Fig. 10 and Fig. 11, we can get the following 61.16 0.001 0.28 -0.92245 -0.26419 0.281571 5 conclusions. The wavefield features are rather complex for 63.97 0.001 0.08 -0.23245 -0.12499 -0.96454 6 this quasi TTI anisotropic medium. For data with the same offset, the traveling time of reflection wave changes versus Based on the fracture parameters obtained from the DFN azimuth. The time difference between the minimum and the model analysis, equivalent elastic coeffi cients are calculated maximum traveling time of the P-P wave increases as the according to the Hudson theory. The elastic coeffi cients are offset rises. Shear wave splitting exists when the shear wave shown in Eq. (5). From the elastic coefficient matrix we propagates through the quasi TTI medium (as shown by the can get the following conclusion: the fractures in this study reflected shear wave PS , PS and the direct shear wave S , 1 2 1 area are complex and is not the standard HTI or TTI (Tilted S ). From what we have mentioned above, we fi nd that when Transverse Isotropy) model, and here we defi ne it as a quasi the data processing is conducted, as the velocity in different TTI model. On the basis of this elastic coefficient matrix, azimuths varies, data processing toward different azimuths we conduct the wave fi eld forward modeling using the fi nite is necessary. The wavefield obtained through the forward difference method. The model which contains two horizontal modeling provides the input data for the following AVO layers is designed. The fi rst layer is the quasi TTI medium, inversion method, which acts as an important bridge in the and the second layer is isotropic, where the P-wave velocity fracture prediction fl ow shown in Fig. 1. is 3,000.0 m/s, S-wave velocity is 1,500.0 m/s and the density is 2,000.0 kg/m . 5 Seismic modeling of a theoretical fracture model 25.2269 ª º In order to further analyze the seismic responses of the « » 10.5544 25.5865 fractured reservoir, a theoretical fracture model is designed, « » « » 10.6918 10.2232 25.5492 which contains two layers. The first layer is an isotropic « » medium, and the second layer is a monoclinic anisotropic 0.1725 0.4684 0.7059 5.0638 « » medium. The model parameters and fracture parameters are « » 0.6108 0.1236 0.7766 0.2024 5.7258 « » shown in Table 2 and Table 3. Based on this model, seismic 0.0737  0.6231 0.4449 0.1602 0.1930 5.2015 « » ¬ ¼ modeling is performed using the staggered-grid high-order fi nite difference method (Cerjan et al, 1985; Wang et al, 2005; (5) 438 Pet.Sci.(2011)8:433-445 Azimuth angle, ° Azimuth angle, ° 0 25 50 75 100 125 150 175 0 25 50 75 100 125 150 175 0.0 0.0 0.2 0.2 P P 0.4 0.4 t, s t, s PP PP 0.6 0.6 S S 1 1 S S 2 0.8 2 PS PS 0.8 1 1 PS PS 2 2 1.0 1.0 Fig. 10 Az imuthal gathers of x and z components at the offset of 1000 m Azimuth angle, ° Azimuth angle, ° 0 25 50 75 100 125 150 175 0 25 50 75 100 125 150 175 0.0 0.0 0.2 0.2 0.4 0.4 P P t, s t, s 0.6 0.6 PP PP 0.8 0.8 S S 1 1 1.0 1.0 Fig. 11 Azim uthal gathers of x and z components at the offset of 1800 m Dong et al, 2000). The acquisition system is the same as 5.1 Wavefi eld of a monoclinic medium shown in Fig. 9. We select the parameters in model 1 (Table 2). Fig. 12 shows the angle gathers with different offsets of the model. Table 2 Model 1 parameters From 0º to 180º, the reflection travel-time curves show Model Layer V , m/s V , m/s ρ, kg/m negative sine characteristics. The longest travel-time of the p s PP wave appears at about 55º and the shortest appears at Layer 1 isotropy 2800.0 1800.0 2300.0 Model 1 about 145º. With the offset increasing, the difference between Layer 2 (clastic rock) the shortest and the longest increases. At about 55º, the PS anisotropy 3500.0 2000.0 2300.0 (base-rock) wave travels at the slow S wave velocity and there is only PS whose energy is very strong. At about 145º, the PS wave Table 3 Fracture parameters travels at the fast S wave velocity and there is only PS whose energy is also very strong. And at other azimuth angles, PS Normal direction, º Radius, m Aspect ratio Density and PS exist at the same time, but their energies are weak. So 1 0 1.0 0.001 0.01 converted waves are sensitive to fractures and it is feasible to use the converted waves to detect the fractures. Moreover, the 2 60 1.0 0.001 0.1 azimuth must be considered during processing the azimuth- Pet.Sci.(2011)8:433-445 439 angle gathers. different fl uids in fractures. Comparing with Fig. 12(b), Fig. 13 and Fig. 14, we fi nd that when the fractures are fi lled with 5.2 Infl uence of fl uids the same fl uid, but the base rock is different, the difference between the shortest and the longest reflection travel-time We still select the parameters in model 1 (Table 2). For decreases from clastic base-rock to carbonate base-rock. analyzing the fluid influence, we respectively use oil and Therefore it is easier to distinguish gas from oil and water in water to fi ll the fractures. Fig. 12(b) and Fig. 13 show that: clastic rock than in carbonate rock. from 0º to 180º, when fractures are filled with oil or water, the PP reflection travel-time curves also have negative sine Table 4 Model 2 parameters characteristics. Regardless of whether the fractures are filled with oil or water, the PP, PS and PS show similar 1 2 Model Layer V , m/s V , m/s ρ, kg/m p s characteristics. When fractures are filled with oil or water, the difference between the longest and shortest travel time Layer 1 isotropy 4800.0 3200.0 2600.0 Model 2 is smaller than that when fractures are filled with gas. In Layer 2 (carbonate rock) anisotropy 6000.0 3800.0 2700.0 summary, when the fractures are filled with gas, the model (base-rock) displays obvious azimuth-anisotropy, while when fi lled with oil or water, the azimuth-anisotropy is weak. 6 The reflection coefficients characteristics 5.3 Infl uence of base-rock of a fractured reservoir For studying the base-rock influence, the model is changed from model 1 to model 2 (Table 4). The base-rock Spherical divergence exists when performing seismic of the fractured reservoir is changed from clastic rock to modeling, so it is not suitable for amplitude analysis. To do carbonate rock, and the fracture parameters are kept the same this more easily, the Zoeppritz equation is applied in this (Table 3). Fig. 14 shows the modeling results of model 2 with paper to analyze the refl ection coeffi cient characteristics of a Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 P P 0.5 0.5 t, s t, s PP PP 1.0 1.0 PS PS 1 1 PS 2 PS 1.5 1.5 (a) Angle gathers of x and z components at offset 1200m Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 0.5 0.5 P P t, s t, s PP PP 1.0 1.0 PS PS PS PS 2 1.5 1.5 (b) Angle gathers of x and z components at offset 1980m Fig. 12 Angle gathers of x, z components at different offsets in clastic rock 440 Pet.Sci.(2011)8:433-445 Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 0.5 P 0.5 P t, s t, s PP PP 1.0 1.0 PS PS PS PS 2 1.5 1.5 (a) Azimuth-angle gathers x and z components with fractures filled with oil Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 0.5 P P 0.5 t, s t, s PP PP 1.0 1.0 PS PS 1 1 PS PS 2 2 1.5 1.5 (b) Azimuth-angle gathers x and z components with fractures filled with water Azimuth-angle gathers with 1980m offset in clastic rock Fig. 13 fractured reservoir. Refl ection and transmission are produced represent the transmission coefficients of the P-wave and when a seismic wave arrives at the elastic interface. The converted S-wave. seismic wave is considered as a plane wave. According to 6.1 Characteristics of reflection coefficients with Huygen’s principle, the incidence, refl ection, and transmission incident angles waves should satisfy Snell’s Law as well as the displacement continuity and the stress continuity on the boundary (Wu, We select the model 1 (Table 2) and calculate the refl ection 2006). Then, the Zoeppritz equation which describes the coeffi cients (Fig. 15). From Fig. 15, the following conclusions reflection coefficient and transmission coefficient under can be derived. For a certain azimuth, the reflection anisotropic condition can be obtained. For example, the coefficient changes with the incident angle (denoted by the Zoeppritz equation of a compression wave under anisotropic slowness), and if the azimuth angle changes, the reflection conditions is shown as follows: coefficient also changes. The lines on the 30º and 120º are respectively perpendicular and parallel to the bisecting line sinT cosT  sinTT cos R  sinT ª ºª º ªº PR SR PT ST PP PR of the included angle between the two groups of fractures, « »« » «» cosT  sinT cos TT sin R cosT and the P-wave velocity is smallest on 30º and is biggest on PR SR PT ST PS PR « »« » « » 120º, so the refl ection coeffi cient is different obviously from « »« » « » A A A AT B 1 2 3 4 PP 1 « »« » «» the slowness of 0.25 s/m to the slowness of 0.35 s/m. The A A A AT B ¬ 5 6 7 8 ¼¬ PS¼ ¬¼ 2 lines on the 90º and the 150º are respectively parallel to the (6) fracture strikes, and the corresponding refl ection coeffi cients where, A and B are function of elastic parameters, incidence are different because the fracture intensities are not the same i i angle and transmission angle on both sides of the interface. for fractures in these two directions. Fig. 15(e) displays R and R respectively represent the refl ection coeffi cients the differences of the PP reflection coefficients on different PP PS of the P-wave and converted S-wave. T and T respectively azimuth angles and the differences on middle offsets are more PP PS Pet.Sci.(2011)8:433-445 441 Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 0.5 S 0.5 t, s PP t, s PP 1.0 PS 1.0 PS PS PS 2 2 1.5 1.5 (a) Azimuth-angle gathers x and z components with fractures filled with gas Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 P P 0.5 0.5 PP t, s PP t, s 1.0 1.0 PS PS PS PS 1.5 1.5 (b) Azimuth-angle gathers x and z components with fractures filled with oil Azimuth angle, ° Azimuth angle, ° 0 40 80 120 160 0 40 80 120 160 0.0 0.0 P P 0.5 0.5 t, s PP t, s PP 1.0 1.0 PS PS 1 1 PS PS 1.5 1.5 (c) Azimuth-angle gathers x and z components with fractures filled with water Fig. 14 Azimuth-angle gathers with 1980m offset in carbonate rock obvious than those on near offsets. incident angle. Slowness of 0.198 s/m, 0.286 s/m, 0.358 s/m and 0.418 s/m are selected as examples, the PP reflection 6.2 Characteristics of reflection coefficients with coeffi cient changes gently at 0.198 s/m, 0.358 s/m and 0.418 azimuth angles s/m, while the PP refl ection coeffi cient changes dramatically at 0.286 s/m. The azimuth AVO characteristics exist on the Fig. 16 shows the reflection coefficients changing with top interface of the fractured reservoirs, and we might be able the azimuth angles for the model 1 (Table 2). The refl ection to use this characteristic to invert fracture development. coeffi cient changes with the azimuth angle for a certain fi xed 442 Pet.Sci.(2011)8:433-445 1.0 1.0 0.9 0.9 PP 0.8 0.8 PSV PP 0.7 PSH 0.7 PSV SVP 0.6 0.6 PSH SVSV 0.5 0.5 SVP SVSH 0.4 SVSV 0.4 SHP SVSH 0.3 SHSV 0.3 SHP SHSH 0.2 0.2 SHSV 0.1 SHSH 0.1 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 Slowness, s/m Slowness, s/m (E $]LPXWKDQJOHRIÛ (D $]LPXWKDQJOHRIÛ 1.0 1.0 0.9 0.9 PP PP 0.8 0.8 PSV PSV 0.7 0.7 PSH PSH SVP SVP 0.6 0.6 SVSV SVSV 0.5 0.5 SVSH SVSH 0.4 0.4 SHP SHP 0.3 0.3 SHSV SHSV SHSH SHSH 0.2 0.2 0.1 0.1 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 Slowness, s/m Slowness, s/m (G $]LPXWKDQJOHRIÛ (F $]LPXWKDQJOHRIÛ 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 Slowness, s/m (e) PP reflection coefficients Fig. 15 Diagrams showing the refl ection coeffi cients changing with incident angles in clastic reservoi r reflection coefficient is 0.2 at 0.28 s/m when filled with oil 6.3 Infl uence of fl uid properties or water. From Fig. 17(a) and Fig. 17(b), we fi nd that when For analyzing the influence of fluid properties on the azimuth is 30º or 120º, the PP refl ection coeffi cient when refl ection coeffi cients, the fractures of the model 1 (Table 2) filled with oil is similar with that when filled with water. are fi lled respectively with oil and water. At the 30º azimuth, Therefore, it is very difficult to distinguish oil from water selecting the slowness area from 0.05 s/m to 0.25 s/m, from the refl ection coeffi cient. when the fractures are filled with gas (Fig. 15(b)), the PP reflection coefficient decreases apparently almost to 0.06. 6.4 Infl uence of base-rocks However, when the fractures are fi lled with oil or water (Fig. For analyzing the influence of the base-rocks, we select 17(a) and Fig. 17(b)), the PP refl ection coeffi cient decreases the model 2 (Table 4) with carbonate rock as base-rock. As apparently almost to 0.09. At the slowness from 0.20 s/m to shown in Fig. 18, the curves are different when fi lled with gas 0.30 s/m, the PP reflection coefficient when filled with gas compared to fi lled with oil or water at 30º and 120º. So we is smaller than that when fi lled with oil or water. The law is can distinguish gas from oil and water, but oil and water are the same at the 120º azimuth. For example, the PP refl ection coeffi cient is 0.2 at 0.3 s/m when fi lled with gas, while the PP almost indistinguishable from the PP refl ection coeffi cient. Amplitude Amplitude Amplitude Amplitude Amplitude Pet.Sci.(2011)8:433-445 443 0.7 0.7 PP 0.6 0.6 PP PSV PSV 0.5 PSH 0.5 PSH SVP SVP 0.4 SVSV 0.4 SVSV SVSH 0.3 SVSH 0.3 SHP SHP SHSV 0.2 SHSV 0.2 SHSH SHSH 0.1 0.1 0.0 0.0 0 40 80 120 160 200 240 280 320 360 0 40 80 120 160 200 240 280 320 360 Angle, º Angle, º (a) Slowness 0.198 s/m (b) Slowness 0.286 s/m 1.0 0.7 0.9 0.6 PP PP 0.8 PSV PSV 0.7 0.5 PSH PSH 0.6 SVP SVP 0.4 0.5 SVSV SVSV SVSH 0.3 0.4 SVSH SHP SHP 0.3 SHSV 0.2 SHSV 0.2 SHSH SHSH 0.1 0.1 0.0 0.0 0 40 80 120 160 200 240 280 320 360 0 40 80 120 160 200 240 280 320 360 Angle, º Angle, º (c) Slowness 0.358 s/m (d) Slowness 0.418 s/m Fig. 16 Diagrams showing the refl ection coeffi cients changing with azimuth angles in clastic reservoir 1.0 1.0 0.9 0.9 0.8 0.8 PP PP 0.7 0.7 PSV PSV 0.6 0.6 PSH PSH SVP SVP 0.5 0.5 SVSV SVSV 0.4 0.4 SVSH SVSH 0.3 0.3 SHP SHP SHSV 0.2 SHSV 0.2 SHSH SHSH 0.1 0.1 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 Slowness, s/m Slowness, s/m (a) Refl ection coeffi cients at 30º and 120 º azimuth with fractures fi lled with oil 1.0 1.0 0.9 0.9 0.8 0.8 PP PP 0.7 0.7 PSV PSV 0.6 0.6 PSH PSH SVP 0.5 0.5 SVP SVSV 0.4 0.4 SVSV SVSH SVSH 0.3 0.3 SHP SHP 0.2 SHSV 0.2 SHSV SHSH 0.1 0.1 SHSH 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 Slowness, s/m Slowness, s/m (b) Refl ection coeffi cients at 30˚and 120˚azimuth with fractures fi lled with water Diagrams showing the refl ection coeffi cients changing with slowness with fractures fi lled with different fl uids in clastic reservoir Fig. 17 Amplitude Amplitude Amplitude Amplitude Amplitude Amplitude Amplitude Amplitude 444 Pet.Sci.(2011)8:433-445 1.0 1.0 0.9 0.9 PP PP 0.8 0.8 PSV PSV 0.7 0.7 PSH PSH 0.6 0.6 SVP SVP 0.5 0.5 SVSV SVSV SVSH SVSH 0.4 0.4 SHP SHP 0.3 0.3 SHSV SHSV 0.2 0.2 SHSH SHSH 0.1 0.1 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.00 0.05 0.10 0.15 0.20 0.25 0.30 Slowness, s/m Slowness, s/m (a) Refl ection coeffi cients at 30˚and 120˚azimuth with fractures fi lled with gas 1.0 1.0 0.9 0.9 0.8 0.8 PP PP 0.7 0.7 PSV PSV 0.6 0.6 PSH PSH 0.5 0.5 SVP SVP 0.4 SVSV SVSV 0.4 0.3 SVSH SVSH 0.3 SHP SHP 0.2 0.2 SHSV SHSV 0.1 0.1 SHSH SHSH 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.00 0.05 0.10 0.15 0.20 0.25 0.30 Slowness, s/m Slowness, s/m (b) Refl ection coeffi cients at 30˚and 120˚azimuth with fractures fi lled with oil 1.0 1.0 0.9 0.9 PP 0.8 0.8 PSV 0.7 0.7 PP PSH PSV 0.6 SVP 0.6 PSH 0.5 SVSV 0.5 SVP SVSH 0.4 0.4 SVSV SHP 0.3 SVSH SHSV 0.3 0.2 SHP SHSH 0.2 SHSV 0.1 0.1 SHSH 0.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.00 0.05 0.10 0.15 0.20 0.25 0.30 Slowness, s/m Slowness, s/m (c) Refl ection coeffi cients at 30˚and 120˚azimuth with fractures fi lled with water Diagrams showing refl ection coeffi cients changing with slowness with fractures fi lled with different fl uids in carbonate reservoir Fig. 18 The modeling result shows that for data with the same 7 Conclusions offset, the traveling time of the refl ection wave changes with 1) The geological, seismic and well log data respectively the azimuth. Additionally, the time difference between the describe the fractures at different scales, and an integration of minimum and the maximum traveling time of the P-P wave the three can be used to build up the fracture models by the increases as the offset rises. Shear wave splitting exists when DFN method and the fracture parameters can be calculated. a shear wave propagates through the quasi TTI medium. The The equivalent medium theory uses the fracture parameters wavefi eld through the forward modeling not only helps us to to compute the elastic coeffi cients of the anisotropic medium, understand the seismic response of the fractured reservoirs, which is an important bridge to connect the microscopic but also provides the input data for the study of the fracture fractures and macroscopic reservoir modeling. inversion method. 2) Using the real geological, seismic and well longing 3) From an analysis of the monoclinic anisotropy, we data, the DFN model is built to calculate the equivalent elastic learn some characteristics of the reflection coefficients, coefficient. The wavefield forward modeling is conducted the slowness and the azimuth angles. The PP reflection using the staggered-grid high-order fi nite difference method. coeffi cients in middle offsets are sensitive to the fractures, so Amplitude Amplitude Amplitude Amplitude Amplitude Amplitude Pet.Sci.(2011)8:433-445 445 Luo J H, Zhou X Y, Qiu B, et al. Mesozoic-Cenozoic fi ve tectonic events the middle offsets are better than the others when inverting and their petroleum geologic signifi cances in the West Tarim Basin. the fractures. The seismic data are more sensitive to gas than Petroleum Exploration and Development. 2005. 32(1): 18-22 (in oil or water, so gas can be distinguished from oil and water, Chinese) while oil can not be distinguished from water. When the base- Tsv ankin I. Seismic Signatures and Analysis of Reflection Data in rocks are different, it is much easier to distinguish the fl uids Anisotropic Media. Amsterdam: Elsevier Science. 2005. 14-252 in the clastic rock than in carbonate rock. Azimuth anisotropy Wan g D L, He Q D and Han L G. Multi-azimuth three-component can be used in detecting fractured reservoirs. Theoretically, surface seismic modeling for cracked monoclinic media. Chinese the acquisition system for anisotropy detection should be full- Journal of Geophysics. 2005. 48(2): 386-393 (in Chinese) azimuth and have equal fold. Data processing toward different Wan g S M, Jin Z J and Xie Q L. Transforming effect of deep fl uids on azimuth is necessary as the velocities in different azimuth are carbonate reservoirs in the well TZ45 region. Geological Review. not the same. 2004. 50(5): 543-547 (in Chinese) Wan g Z Y, Li Y P, Chen J S, et al. Characters of atmospheric diagenetic lens along middle-late Ordovician carbonate shelf margin in central Acknowledgements Tarim area. Chinese Journal of Geology. 2002. 37(S1): 152-160 (in The work is co-supported by the National Basic Research Chinese) Program of China (Grant No.2011CB201103) and the Wan g Z Y, Yan W, Zhang Y F, et al. Diagenesis and porosity evolution of National Science and Technology Major Project (Grant upper Ordovician platform margin reefs and grain banks reservoirs in the Tazhong area. Xinjiang Geology. 2007. 25(3): 288-290 (in No.2011ZX05004003). The authors would like to thank the Chinese) Laboratory for Integration of Geology and Geophysics (LIGG) Wei G Q, Jia C Z, Song H Z, et al. Ordovician structural-depositional at China University of Petroleum for the permission to model and prediction for profitable crack reservoirs of carbonate publish this work and the Tarim Oilfi eld Co., PetroChina for rock in the Tazhong area, Tarim Basin. Acta Sedimentologica Sinica. their help in providing fi eld data. Also, Shell Co. is thanked 2000. 18(3): 408-413 (in Chinese) for the fi nancial assistant to the fi rst author. Wu G C. Seismic Wave Propagation and Imaging in an Anisotropic Medium. Dongying: China University of Petroleum Press. 2006. 43- References 156 (in Chinese) Yan g H J, Liu S, Li Y P, et al. Analysis of the middle-upper Ordovician Cer jan C, Kosloff D, Kosloff R, et al. A nonrefl ecting boundary condition carbonate reservoirs in the Tazhong area. Marine Origin Petroleum for discrete acoustic and elastic wave equations. Geophysics. 1985. Geology. 2000. 5(1-2): 73-83 (in Chinese) 50(4): 705-708 Zha o Z J, Wang Z M, Wu X N, et al. Genetic types and distribution Cra mpin S. Effective anisotropic elastic constants for wave propagation forecast of available carbonate reservoirs in Ordovician in the central through cracked solids. Geophysical Journal of the Royal area of Tarim Basin. Petroleum Geology and Experiment. 2007. Astronomical Society. 1984. 76(1): 135-145 29(1): 40-46 (in Chinese) Don g L G, Ma Z T, Cao J Z, et al. A staggered-grid high-order difference Zhu D Y, Hu W X, Song Y C, et al. Fluoritization in Tazhong 45 method of one-order elastic wave equation. Chinese Journal of reservoir: characteristics and its effect on the reservoir bed. Acta Geophysics. 2000. 43(3): 411-419 (in Chinese) Petrologica et Mineralogica. 2005. 24(3): 205-215 (in Chinese) Hud son J A. A higher order approximation to the wave propagation constants for a cracked solid. Geophysical Journal of the Royal (Edited by Hao Jie) Astronomical Society. 1986. 87(1): 265-274

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Published: Dec 8, 2011

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