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The predicted distribution of conventional hydrocarbon reservoirs saturated with different fluids in perspective target area (Taking Area I as example) .
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The storage spaces of carbonate reservoirs in Tarim are mostly secondary, and these reservoirs are characterized by strong heterogeneity and some degree of anisotropy. For caved reservoirs in Tarim, the precise rock physics and AVO forward analysis are performed, and the characteristics of two kinds of hydrocarbon reservoirs saturated with differen...
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... to deep-burying and compaction, the limestone in Tarim Basin is very dense and the seismic velocity of the Tarim carbonate reservoirs is high. Meanwhile, the reservoirs suffered a series of diagenesis, tectonic movements and strong dissolution, the pore shapes of the carbonate reservoirs are caved and dominated by secondary pores such as the dissolved holes, caves and cracks, which significantly influence the seismic velocity. As a result, it is often doubted of the avalidtity of fluid mapping of carbonate reservoirs based on elastic attributes. Through several field data examples, this paper provides an objective evaluation on whether the elastic information could be available for fluid mapping in the deep-buried caved carbonate reservoirs. It is of great significance to choose a reasonable rock physics model to conduct fluid mapping. Based on comparative analysis, Berryman’s (1992) differential effective medium (DEM) model and Gassmann’s equation (1951) are integrated to predict the elastic velocities of saturated reservoirs. Not only does this method consider the influence of pore shapes on P- and S-wave velocity, but also it meets the requirement of “dilute” pores by incrementally adding pores. Furthermore, it also avoids the effect of velocity dispersion, because it just uses DEM model to calculate dry rock elastic module. Meanwhile, Batzle-Wang’s ( 1992 ) model is also used in this paper to evaluate the influence of the change of temperature and pressure on the elastic characters of fluid. Thus it precisely simulates the elastic parameters of caved carbonate reservoir when saturated with oil, gas and water respectively. The optimized fluid factors are selected by the comparison of different elastic parameter combinations. Using the AVO inversion results, fluid distributions of conventional hydrocarbon reservoirs and condensed hydrocarbon reservoirs are predicted. Through the research and discussion in the paper, it is aimed at providing valuable references for fluid mapping in caved carbonate reservoirs based on elastic attributes. Fluid mapping of different hydrocarbon reservoirs is performed by Area I (conventional hydrocarbon reservoir) and Area II (condensate reservoir) in Tarim Basin for examples. Based on the method of velocity prediction discussed above, the reservoirs are respectively filled with oil, gas and water. And the corresponding P- and S-wave velocities are predicted (shown in Figure 1). those saturated with oil and gas. However, they are closed to each other for those saturated with oil and gas. Area I is mainly gas-producing. Oil testing results show that the bulk modulus of gas is low (about 0.15GPa), and that of oil is high (about 1.56GPa) at underground condition. Area II is a principle condensed gas-producing area, where the gas is easily separated out from the crude oil. That is, plenty of gas is dissolved in oil under the condition of high temperature and pressure. The 3 bulk modulus and density of the gas-dissolved oil are quite low (about 0.71Gpa and 0.79g/cm , respectively). This character decreases the differences of elastic properties of crude oil and gas, inducing the phenomenon of detachment between oil/gas and water saturated reservoirs, which also proves the applicability of this method to identify reservoir fluids. In order to simulate the AVO response in different fluid saturated reservoirs, Well LG34 and Well ZG16 are taken for examples (Figure 2). The synthetic AVO gathers are converted into seismic data. Single-CDP prestack inversion is implemented based on seismic data converted from synthetic AVO gathers. The inversion results are shown in Figure 3. Both AVO responses and the inverted tri-elastic parameters show that the characteristics of gas reservoir are very different to those of oil or water reservoirs for conventional reservoirs (e.g., Area I) while the characteristics of oil or gas reservoirs are very different to water reservoirs for condensed reservoirs (e.g., Area II). In order to better distinguish fluids, the fluid mapping capacity of different elastic parameters are tested here (shown in Figure 4). These elastic parameters include P-Impedance (PI), S-Impedance (SI), P-wave to S-wave velocity ratio (Vp/Vs), Possion’s ratio, product of lame constants and density 2 (LamRho and MuRho), LamRho*Vp/Vs and PI /SI. The figure shows that the cross-plot of Vp/Vs (or Possion’s ratio) and PI has the best mapping capacity. Fluid mapping of carbonate reservoir is processed by using the results of pre-stack AVO inversion. Then based on the cross-plot of Vp/Vs and PI using inversion results, the reservoir fluid types are identified. Figure 5 shows the comparison of fluid mapping results and oil testing results for Well ZG11 (water-production well) and Well ZG11C (gas well). The dark points in the upper part of Figure 5(right) reflect the prediction distribution of oil and gas, and the white points in the lower part of Figure 5(right) reflect the prediction distribution of water. Significantly, the fluid mapping results are consistent well with the actual oil-testing results. Figure 6 and Figure 7 show the corresponding fluid mapping distribution for conventional hydrocarbon reservoirs (Area I) and condensed hydrocarbon reservoirs (Area II). According to the cross-plots results, gas boundary against oil and water is designated for conventional hydrocarbon reservoirs while water boundary against oil and gas is designated for condensed hydrocarbon reservoirs. The fluid mapping results in the location of well are consistent well with oil-testing results. And the predicted perspective targets in Area I are located on the low structure zone at 800-1000m below the deepest bottom of dilled wells, which agree with the geology law in this area. Statistic analysis shows that the coherence of fluid mapping results and oil testing results can reach up to 87.5%, which is acceptable for deep-buried caved carbonate reservoirs. It has been proven that the method of fluid mapping is available for this kind of reservoirs. But it should be kept in mind that isotropic medium assumption for caved carbonate rocks and the low ratio of signal to noise of seismic data can limit the applicability of the proposed fluid mapping method. The integrated application of DEM model and Gassmann’s equation are proven to be most available for the calculation of elastic parameters of caved carbonate reservoirs. According to the fluid substitution, AVO analysis, and pre-stack inversion, several conclusions can be derived: 1) for conventional hydrocarbon reservoirs, gas can be distinguished from oil and water, yet oil and water is hard to be distinguished from each other; 2) for condensed hydrocarbon reservoirs, water can be distinguished from oil and gas, yet oil and gas is hard to be distinguished from each other; 3) Cross- plot of PI and Vp/Vs (or Poisson’s ratio) is proven to be the best fluid mapping for caved carbonate reservoirs in Tarim Basin. Batzle, M. and Wang, Z. [1991] Estimating grain-scale fluid effects on reservoir rock. SEG Geophysics , 56 (2): 1940-1949. Berryman, J.G. [1992] Single-scattering approximations for coefficients in Biot’s equations of poroelasticity. Journal of Acoustic Society of American , 91 : 551-571. Biot [1962] Generalized theory of acoustic propagation in porous dissipative media. The Journal of the Acoustic Society of America, 34 (9):1254-1264. Gassmann, F. [1951] Über die Elastizität poroser Medien. Vier.der Natur. Gessellschaft in Zürich, 96 :1-23. Kuster, G.T. and Toks ö z, M.N. [1974] Velocity and attenuation of seismic waves in two-phase media, Part 1: Theoretical formulations. Geophysics , 39 (3): 587-606. Wang, H.Y., Sun Z.D. and Yang, H.J. [2009] Velocity prediction models evaluation and permeability prediction for fractured and caved carbonate reservoir: from theory to case study. SEG Expanded Abstract , ...
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Citations
... Carbonate reservoir is widely developed in China Tarim basin, where a large number of oil fields are discovered in the paleo-karsts Ordovician limestone reservoir (Peng et al. 2008;Sun et al. 2011). The storage spaces for the carbonate reservoir in this area are mostly secondary dissolution caves and characterized by strong heterogeneity (Zhang et al. 2008;Zeng et al. 2011;Yang et al. 2012). ...
p class="zhengwen"> Seismic full waveform inversion seeks to make use of the full information based on full wave field modeling to extract quantitative information from seismograms. Its serious nonlinearity and high dependence on initial velocity model often results in unsatisfactory inversion results in paleo-karsts carbonate reservoir characterized by strong heterogeneity. The paper presents an improved strategy of multi-scale inversion to establish velocity field model of waveform tomography. the forward wave equation algorithm was derived in frequency domain, and then the Matrix formalism for the iterative inverse methods is derived by gradient methods to speed up calculation and to avoid convergence to local minimum value. After massive amount of frequencies tests, the appropriate bandwidth are extracted, and the velocity field calculated at low frequency is used as the input of the high frequency. After the iteration, the accurate velocity field is inverted. Finally, frequency domain wave equation full waveform inversion in mathematical and physical models is conducted in order to verify the inverse program. The method of selecting the inverse frequencies is proved to be effective. </p
... In the Tarim Basin in Western China, Karstified Ordovician limestone has been shown to be a highly productive oil and gas reservoir (Sun et al., 2011;Yang et al., 2012). The Ordovician carbonate reservoirs in this field are deeply buried (>5000m) and characterized by strong heterogeneity and some degree of anisotropy. ...
... Successful data processing in this area often focuses on preserving the true amplitudes in the whole processing workflow, e.g., amplitude compensation, noise attenuation, resolution enhancement and pre-stack migration. Significantly, the basic criterion for preserving amplitude is that the AVO characteristics between synthetic and obtained gathers should be similar (Sun et al., 2011;Zhang et al., 2011a;Zhang et al., 2011b;Feng et al., 2012). Meanwhile, the pre-stack seismic inversion should be carefully applied by seriously controlling the quality of four major approaches, including angle partial stack data preparation, wavelet estimation, low-frequency model building and inversion parameter control (Zhang et al., 2011a;Zhang et al., 2011b). ...
... The cross-plot between the measured acoustic impedance (logging) filtered to the seismic-frequency band (AI in x-axis) and the computed relative impedance (RI in y-axis) at well locations www.ccsenet.org/esr Earth Science Research Vol. 5, No. 2;2016 Figure 7. Low frequency models achieved by the traditional interpolation and extrapolation method (a) and the proposed amplitude-based method (b). The blue lines near well locations in Figure 7a indicate the measured acoustic impedances (insufficient for the well W1) Figure 7 demonstrates the difference between the Low frequency acoustic impedance models constructed by the traditional interpolation and extrapolation method and the proposed amplitude-based method, respectively. ...
p> For the modeling of complex reservoirs with strong heterogeneity, for instance the deeply buried paleokarst reservoirs in the Tarim Basin, the traditional method by lateral interpolation and extrapolation of measured logs between well locations with the guiding of interpreted seismic horizons is driven by distance and often leads to non-geologic solutions, while the past improvements via adding seismic velocities or attributes information are still not accurate due to the resolution limitation or AVO (amplitude versus offset) effects contamination. In this paper, we present an amplitude-based modeling method by utilizing the heterogeneous information from seismic data to guide the geological model construction, based on the inverted pure P-wave data which have removed the AVO effects. The proposed method is applied in the impedance inversion of the paleokarst carbonate reservoirs in the Tarim Basin, where the reservoirs are characterized by substantial heterogeneity. Both the constructed Low frequency model (LFM) and the inverted impedance results of proposed method are more correlative with drilling data than that of traditional method. This method is more beneficial for strong heterogeneous reservoirs description especially in well insufficient or absent areas, suggested by the comparisons with traditional methods in the ZG8 area. </p
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The present burial depth of the paleokarst reservoirs in the Tarim Basin is greater than 5000m, which premises rigorous demands for the data quality for accurate predictions. Although routinely used for reservoir prediction, the conventional full-stack data are often contaminated by the AVO (amplitude versus offset) effects no matter how much signal to noise ratio degree can be enhanced via stacking. This contamination usually changes with different geological deposits, and could reach an inappropriate and unacceptable level for the deeply buried carbonate reservoir in the Tarim Basin. In this paper, the pure P-wave data theoretically inverted through AVO effects removal are employed to improve reservoir prediction, which are illustrated by the comparisons with that of the conventional full-stack data for the classical four AVO models and the field data in the ZG8 area, Tazhong Uplift, central Tarim Basin. The dominant frequency has been improved for 8 Hz from 15 to 23 Hz in the target Yingshan formation, Ordovician through AVO effects removal, and the reflection events of the pure P-wave data are obviously more continuous comparing with that of the full-stack data. The fake potential reservoir caused by AVO effects in the northeast area has been removed, while the integral delineation of paleokarst reservoirs have been significantly improved with a higher fitness with the oil-testing results, which are more beneficial for later on exploration. The pure P-wave data inversion is in essence an important complement to current processing strategy.
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... In the process, two fluid identification polygons for gas and oil plus water (Fig. 8A) were set up by consulting Fig. 6A, and then, the corresponding fluid distributions were separately depicted by tracking qualified data (Fig. 8B,C). Because a great majority of research (Ping et al. 2007;Sun et al. 2011a;Zhang et al. 2011a,b) suggested that the karstic reservoir in this area typically shows a lower PI value compared to compacted carbonate matrix, the gas reservoir should exhibit lower PI and Sw (water saturation) values, opposite of water-saturated reservoirs. The predicted fluid is consistent with this character and verifies this fluid identification method. ...
Summary Ordovician paleokarst carbonate reservoirs are widely developed in the Tahe Oilfield, China. The storage space is complex, mainly including dissolved caves, pores and fractures, which significantly influence the seismic velocity. In order to accurately discriminate the saturated pore fluids, DEM-Gassmann rock physic model is employed to address this complex reservoir before pre-stack inversion. Based on the fluid substitution results from a field well, the feasibility of fluid identification at this area is discussed through systematically modeling and pre-stack inversion. In particular, the subsequent 2D/3D field fluid distribution results have a considerable coherence with oil testing results. This integral strategy and corresponding results are definitely beneficial for exploration/exploitation in that area.
Considering the fact that the fluid distribution in carbonate reservoir is very complicated and the existing fluid prediction methods are not able to produce ideal predicted results, this paper proposes a new fluid identification method in carbonate reservoir based on the modified Fuzzy C-Means (FCM) Clustering algorithm. Both initialization and globally optimum cluster center are produced by Chaotic Quantum Particle Swarm Optimization (CQPSO) algorithm, which can effectively avoid the disadvantage of sensitivity to initial values and easily falling into local convergence in the traditional FCM Clustering algorithm. Then, the modified algorithm is applied to fluid identification in the carbonate X area in Tarim Basin of China, and a mapping relation between fluid properties and pre-stack elastic parameters will be built in multi-dimensional space. It has been proven that this modified algorithm has a good ability of fuzzy cluster and its total coincidence rate of fluid prediction reaches 97.10%. Besides, the membership of different fluids can be accumulated to obtain respective probability, which can evaluate the uncertainty in fluid identification result.
The storage spaces within deeply buried Ordovician paleokarst reservoirs in the Tarim Basin are mostly secondary and characterized by strong heterogeneity and some degree of anisotropy. The types of fluids that fill the spaces within these reservoirs are of great importance for hydrocarbon exploration and exploitation. However, fluid identification from seismic data is often controversial in this area because the seismic velocity for this particular reservoir could be significantly influenced by many factors, including pore shapes, porosity, fluid types, and mineral contents. In this paper, we employ the DEM-Gassmann rock physics model to interpret and discuss the characteristics of conventional karstic carbonate reservoirs in the Tarim Basin that are filled with different fluids (oil, gas and water) by using logging data and thus objectively build corresponding fluid identification criteria. These criteria are subsequently evaluated by AVO forward analysis based on typical logging data and further applied to ascertain the reservoir fluid types in two different areas in the Tarim Basin based on pre-stack inversion results. For conventional carbonate reservoirs, gas can be distinguished from heavy oil and water, but heavy oil and water are broadly similar on seismic data. For condensate carbonate reservoirs, water can be differentiated from light oil (i.e., condensates) and gas, but light oil and gas demonstrate substantial similarities in terms of their seismic responses. The predicted fluid results are in good agreement with the results of drilling and oil testing. In particular, modeling the seismically resolvable reservoirs in the carbonate strata in the Tarim Basin, which have needle- and sphere-shaped storage spaces (pore aspect ratio > 0.3) and clay content that is lower than 5%, indicates that fluid properties could be properly evaluated if the porosity is larger than 5% for conventional carbonate reservoirs and >7% for condensate carbonate reservoirs.
CNPC), X. Zhou (Tarim Oilfield Co., CNPC), H. Yang (Tarim Oilfield Co., CNPC) & J. Han (Tarim Oilfield Co., CNPC) SUMMARY Carbonate reservoir in Western China, which shows tremendous exploration and development opportunity, has become the key area for oil and gas reserves addition and sustainable resources development for China. Compared to the conventional carbonate reservoir, prediction of this kind of reservoir predominated by secondary storage is much more difficult. Seismic detection of dissolved pore and fracture always sets pretty high demand for technology, which further puts serious challenges on exploration and many technological issues for field development plan. Based on a detailed analysis of exploration issues for such complex carbonate reservoir, the key geophysical problems are tackled. Subsequently, a set of techniques for complex carbonate reservoir prediction is established, including pre-stack amplitude-preserved processing, new technologies of rock physics, pre-stack AVO inversion , eismic multi-attributes optimization and integrated prediction, anisotropy detection using pre-stack data with limited azimuthal distribution, fluid identification based on prestack inversion. Additionally, to solve some special questions, diffraction wave field separation and imaging, nonstatorary deconvolution etc are also developed. Moreover, application of this set of technology to field data has proven this technology be effective and feasible. Besides, drilling results show pretty good agreement with our research. Nevertheless, the research has just got started.
Carbonate reservoirs of the Tarim Basin in China are buried deeply, with strong later diagenesis, and seldom are controlled by geologic facies. The effective storage spaces are mainly dissolution caves and fractures with few primary pores. Fluid distribution in the reservoir is extremely complicated. All these characteristics make it a world-class challenge for oil and gas exploration and production. Conventional poststack methods ignore the complexity of the reservoir medium with low accuracy of prediction results, by which the location of the dissolution cave is determined roughly. Only faults and fracture zones can be described to a certain degree instead of quantifying the fracture detection. Aiming at the key problems of the complex carbonate reservoirs in the Tarim Basin, a series of techniques has been developed to improve the successful rate of reservoir prediction, including the following aspects: the wide-azimuth and high-density data-acquisition technique to improve the quality of the original seismic data; a series of migration techniques including prestack reverse time migration; and amplitude-preserved Q migration to improve the quality of seismic gathers and the imaging precision with the matching precision of AVO gathers. The ta rget reser voir d ata dom inant f requenc y increased by more than 15% and by nearly 20 Hz. In addition, the effective DEM-Gassmann rock-physics model is proposed for velocity prediction, by which relative error of estimated shearwave velocity reaches to less than 5%. Furthermore, an advanced inversion algorithm is introduced to improve the accuracy of extracted elastic information. By using new prestack inversion and frequency-dependent AVO inversion, the tie rate of the dissolution-cave reservoir and fluid prediction increased by more than 15%. Furthermore, the fracture-prediction tie rate can be enhanced by 20% through limited-azimuth anisotropic inversion, on the basis of which the quantitative identification of fracture fluid for actual seismic data can be realized.
