Fast pre-stack multi-channel inversion constrained by seismic reflection features

Classical multi-channel technology can significantly reduce the pre-stack seismic inversion uncertainty, especially for complex geology such as high dipping structures. However, due to the consideration of complex structure or reflection features, the existing multi-channel inversion methods have to adopt the highly time-consuming strategy of arranging seismic data trace-by-trace, limiting its wide application in pre-stack inversion. A fast pre-stack multi-channel inversion constrained by seismic reflection features has been proposed to address this issue. The key to our method is to re-characterize the reflection features to directly constrain the pre-stack inversion through a Hadamard product operator without rearranging the seismic data. The seismic reflection features can reflect the distribution of the stratum reflection interface, and we obtained them from the post-stack profile by searching the shortest local Euclidean distance between adjacent seismic traces. Instead of directly constructing a large-size reflection features constraint operator advocated by the conventional methods, through decomposing the reflection features along the vertical and horizontal direction at a particular sampling point, we have constructed a computationally well-behaved constraint operator represented by the vertical and horizontal partial derivatives. Based on the Alternating Direction Method of Multipliers (ADMM) optimization, we have derived a fast algorithm for solving the objective function, including Hadamard product operators. Compared with the conventional reflection features constrained inversion, the proposed method is more efficient and accurate, proved on the Overthrust model and a field data set.

Pre-stack inversion for caved carbonate reservoir prediction:A case study from Tarim Basin,China

The major storage space types in the carbonate reservoir in the Ordovician in the TZ45 area are secondary dissolution caves.For the prediction of caved carbonate reservoir,post-stack methods are commonly used in the oilfield at present since pre-stack inversion is always limited by poor seismic data quality and insufficient logging data.In this paper,based on amplitude preserved seismic data processing and rock-physics analysis,pre-stack inversion is employed to predict the caved carbonate reservoir in TZ45 area by seriously controlling the quality of inversion procedures.These procedures mainly include angle-gather conversion,partial stack,wavelet estimation,low-frequency model building and inversion residual analysis.The amplitude-preserved data processing method can achieve high quality data based on the principle that they are very consistent with the synthetics.Besides,the foundation of pre-stack inversion and reservoir prediction criterion can be established by the connection between reservoir property and seismic reflection through rock-physics analysis.Finally,the inversion result is consistent with drilling wells in most cases.It is concluded that integrated with amplitude-preserved processing and rock-physics,pre-stack inversion can be effectively applied in the caved carbonate reservoir prediction.

Petrophysical parameters inversion for heavy oil reservoir based on a laboratory-calibrated frequency-variant rock-physics model

Heavy oil has high density and viscosity, and exhibits viscoelasticity. Gassmann's theory is not suitable for materials saturated with viscoelastic fluids. Directly applying such model leads to unreliable results for seismic inversion of heavy oil reservoir. To describe the viscoelastic behavior of heavy oil, we modeled the elastic properties of heavy oil with varying viscosity and frequency using the Cole-Cole-Maxwell (CCM) model. Then, we used a CCoherent Potential Approximation (CPA) instead of the Gassmann equations to account for the fluid effect, by extending the single-phase fluid condition to two-phase fluid (heavy oil and water) condition, so that partial saturation of heavy oil can be considered. This rock physics model establishes the relationship between the elastic modulus of reservoir rock and viscosity, frequency and saturation. The viscosity of the heavy oil and the elastic moduli and porosity of typical reservoir rock samples were measured in laboratory, which were used for calibration of the rock physics model. The well-calibrated frequency-variant CPA model was applied to the prediction of the P- and S-wave velocities in the seismic frequency range (1–100 Hz) and the inversion of petrophysical parameters for a heavy oil reservoir. The pre-stack inversion results of elastic parameters are improved compared with those results using the CPA model in the sonic logging frequency (∼10 kHz), or conventional rock physics model such as the Xu-Payne model. In addition, the inversion of the porosity of the reservoir was conducted with the simulated annealing method, and the result fits reasonably well with the logging curve and depicts the location of the heavy oil reservoir on the time slice. The application of the laboratory-calibrated CPA model provides better results with the velocity dispersion correction, suggesting the important role of accurate frequency dependent rock physics models in the seismic prediction of heavy oil reservoirs.

Pre-stack AVO inversion with adaptive edge preserving smooth filter regularization based on Aki-Richard approximation

With the development of exploration of oil and gas resources,the requirements for seismic inversion results are getting more accurate.In particular,it is hoped that the distribution patterns of oil and gas reservoirs can be finely characterized,and the seismic inversion results can clearly characterize the location of stratigraphic boundaries and meet the needs of accurate geological description.Specifically,for pre-stack AVO inversion,it is required to be able to distinguish smaller geological targets in the depth or time domain,and clearly depict the vertical boundaries of the geological objects.In response to the above requirements,we introduce the preprocessing regularization of the adaptive edge-preserving smooth filter into the pre-stack AVO elastic parameter inversion to clearly invert the position of layer boundary and improve the accuracy of the inversion results.

Fluid discrimination incorporating amplitude variation with angle inversion and squirt flow of the fluid

Pre-stack seismic inversion is an important method for fluid identification and reservoir characterization in exploration geophysics. In this study, an effective fluid factor is initially established based on Biot poroelastic theory, and a pre-stack seismic inversion method based on Bayesian framework is used to implement the fluid identification. Compared with conventional elastic parameters, fluid factors are more sensitive to oil and gas. However, the coupling effect between rock porosity and fluid content is not considered in conventional fluid factors, which may lead to fuzzy fluid identification results. In addition,existing fluid factors do not adequately consider the physical mechanisms of fluid content, such as squirt flow between cracks and pores. Therefore, we propose a squirt fluid factor(SFF) that minimizes the fluid and pore mixing effects and takes into account the squirt flow. On this basis, a novel P-wave reflection coefficient equation is derived, and the squirt fluid factor is estimated by amplitude variation with offset(AVO) inversion method. The new reflection coefficient equation has sufficient accuracy and can be utilized to estimate the parameters. The effectiveness and superiority of the proposed method in fluid identification are verified by the synthetic and field examples.

Sweet spot prediction in tight sandstone reservoir based on well-bore rock physical simulation

To establish the relationship among reservoir characteristics and rock physical parameters,we construct the well-bore rock physical models firstly,considering the influence factors,such as mineral composition,shale content,porosity,fluid type and saturation.Then with analyzing the change rules of elastic parameters along with the above influence factors and the cross-plots among elastic parameters,the sensitive elastic parameters of tight sandstone reservoir are determined,and the rock physics template of sweet spot is constructed to guide pre-stack seismic inversion.The results show that velocity ratio and Poisson impedance are the most sensitive elastic parameters to indicate the lithologic and gas-bearing properties of sweet spot in tight sandstone reservoir.The high-quality sweet spot is characterized by the lower velocity ratio and Poisson impedance.Finally,the actual seismic data are selected to predict the sweet spots in tight sandstone gas reservoirs,so as to verify the validity of the rock physical simulation results.The significant consistency between the relative logging curves and inversion results in different wells implies that the utilization of well-bore rock physical simulation can guide the prediction of sweet spot in tight sandstone gas reservoirs.

Prestack Multi-Gather Simultaneous Inversion of Elastic Parameters Using Multiple Regularization Constraints

Inversion of Young’s modulus,Poisson’s ratio and density from pre-stack seismic data has been proved to be feasible and effective.However,the existing methods do not take full advantage of the prior information.Without considering the lateral continuity of the inversion results,these methods need to invert the reflectivity first.In this paper,we propose multi-gather simultaneous inversion for pre-stack seismic data.Meanwhile,the total variation（TV）regularization,L1 norm regularization and initial model constraint are used.In order to solve the objective function contains L1norm,TV norm and L2 norm,we develop an algorithm based on split Bregman iteration.The main advantages of our method are as follows：（1）The elastic parameters are calculated directly from objective function rather than from their reflectivity,therefore the stability and accuracy of the inversion process can be ensured.（2）The inversion results are more in accordance with the prior geological information.（3）The lateral continuity of the inversion results are improved.The proposed method is illustrated by theoretical model data and experimented with a 2-D field data.

基于叠前PP-PS波联合广义线性反演的弹性模量提取方法（英文）

纵波和转换波联合反演方法作为有效的地震技术,比单纯纵波反演精度要高,能够提高地震储层识别的精度。纵波模量和横波模量是进行储层评价、流体判别的重要弹性参数,然而常规估算弹性模量方法的局限性制约了反演精度和稳定性的提升。本文从精确的Zoeppritz方程出发,建立了纵波模量、横波模量与纵波、转换波的精确关系,有效降低了通过近似公式或者间接计算引入的误差,从而提高了反演结果的精度。在反演过程中,考虑到反演过程的不适定性和正演算子的非线性,结合广义线性反演方法,在目标函数中引入了模型参数的先验约束和改进的低频约束,并在求解目标函数时借助迭代反演的思想,不断优化背景速度比值,增加了反演过程的稳定性。经多种模型试算结果表明,该方法有效地提高了纵波模量、横波模量提取的精度和稳定性,为储层、流体预测提供了高质量的数据支持。

Determination of gas reservoir(s) using AVO inversion within “XY” field offshore Niger Delta

The AVO inversion analysis of pre-stack seismic data of“XY”field located within the offshore,Niger Delta Basin has been considered in this research work with the aim of using AVO inversion to delineate gas reservoirs within the field.Three different inversion techniques are carried out in order to obtain accurate reservoir signature.The conventional AVO inversion analysis of the field do not identify the gas reservoirs clearly as there are other zones without gas with similar signatures,however,the cross-plots analysis of elastic parameters and the inverted volumes are used to delineate two gas reservoirs at 2000 and 2100 ms.Conclusively,the inversion techniques help to map the reservoir zone in a better way by increasing the vertical resolution.AVO inversion analysis as used in this research help for better understanding of the physical properties of the delineated reservoirs.

NVERSE CONDUCTIVITY PROBLEM WITH INTERNAL DATA

This paper concerns the reconstruction of a scalar coefficient of a second-order elliptic equation in divergence form posed on a bounded domain from internal data.This problem finds applications in multi-wave imaging,greedy methods to approximate parameter-dependent elliptic problems,and image treatment with partial differential equations.We first show that the inverse problem for smooth coefficients can be rewritten as a linear transport equation.Assuming that the coefficient is known near the boundary,we study the well-posedness of associated transport equation as well as its numerical resolution using discontinuous Galerkin method.We propose a regularized transport equation that allow us to derive rigorous convergence rates of the numerical method in terms of the order of the polynomial approximation as well as the regularization parameter.We finally provide numerical examples for the inversion assuming a lower regularity of the coefficient,and using synthetic data.