查看更多>>摘要：Seismic data is commonly acquired sparsely and irregularly,which necessitates the regularization of seismic data with anti-aliasing and anti-leakage methods during seismic data processing.We propose a novel method of 4D anti-aliasing and anti-leakage Fourier transform using a cube-removal strategy to address the combination of irregular sampling and aliasing in high-dimensional seismic data.We compute a weighting function by stacking the spectrum along the radial lines,apply this function to suppress the aliasing energy,and then iteratively pick the dominant amplitude cube to construct the Fourier spectrum.The proposed method is very efficient due to a cube removal strategy for accelerating the convergence of Fourier reconstruction and a well-designed parallel architecture using CPU/GPU collaborative computing.To better fill the acquisition holes from 5D seismic data and meanwhile considering the GPU memory limitation,we developed the anti-aliasing and anti-leakage Fourier transform method in 4D with the remaining spatial dimension looped.The entire workflow is composed of three steps:data splitting,4D regularization,and data merging.Numerical tests on both synthetic and field data examples demonstrate the high efficiency and effectiveness of our approach.
查看更多>>摘要：Quantitative prediction of reservoir properties(e.g.,gas saturation,porosity,and shale content)of tight reservoirs is of great significance for resource evaluation and well placements.However,the complex pore structures,poor pore connectivity,and uneven fluid distribution of tight sandstone reservoirs make the correlation between reservoir parameters and elastic properties more complicated and thus pose a major challenge in seismic reservoir characterization.We have developed a partially connected double porosity model to calculate elastic properties by considering the pore structure and connectivity,and to analyze these factors'influences on the elastic behaviors of tight sandstone reservoirs.The modeling results suggest that the bulk modulus is likely to be affected by the pore connectivity coefficient,while the shear modulus is sensitive to the volumetric fraction of stiff pores.By comparing the model pre-dictions with the acoustic measurements of the dry and saturated quartz sandstone samples,the volumetric fraction of stiff pores and the pore connectivity coefficient can be determined.Based on the calibrated model,we have constructed a 3D rock physics template that accounts for the reservoir properties'impacts on the P-wave impedance,S-wave impedance,and density.The template combined with Bayesian inverse theory is used to quantify gas saturation,porosity,clay content,and their corre-sponding uncertainties from elastic parameters.The application of well-log and seismic data demon-strates that our 3D rock physics template-based probabilistic inversion approach performs well in predicting the spatial distribution of high-quality tight sandstone reservoirs in southwestern China.
查看更多>>摘要：Full-waveform inversion(FWI)uses the full information of seismic data to obtain a quantitative esti-mation of subsurface physical parameters.Anisotropic FWI has the potential to recover high-resolution velocity and anisotropy parameter models,which are critical for imaging the long-offset and wide-azimuth data.We develop an acoustic anisotropic FWI method based on a simplified pure quasi P-wave(qP-wave)equation,which can be solved efficiently and is beneficial for the subsequent inversion.Using the inverse Hessian operator to precondition the functional gradients helps to reduce the parameter tradeoff in the multi-parameter inversion.To balance the accuracy and efficiency,we extend the truncated Gauss-Newton(TGN)method into FWI of pure qP-waves in vertical transverse isotropic(VTI)media.The inversion is performed in a nested way:a linear inner loop and a nonlinear outer loop.We derive the formulation of Hessian-vector products for pure qP-waves in VTI media based on the Lagrange multiplier method and compute the model update by solving a Gauss-Newton linear system via a matrix-free conjugate gradient method.A suitable preconditioner and the Eisenstat and Walker stopping criterion for the inner iterations are used to accelerate the convergence and avoid prohibitive computational cost.We test the proposed FWI method on several synthetic data sets.Inversion results reveal that the pure acoustic VTI FWI exhibits greater accuracy than the conventional pseudoacoustic VTI FWI.Additionally,the TGN method proves effective in mitigating the parameter crosstalk and increasing the accuracy of anisotropy parameters.
查看更多>>摘要：Seismic wave propagation in fluid-solid coupled media is currently a popular topic.However,traditional wave equation-based simulation methods have to consider complex boundary conditions at the fluid-solid interface.To address this challenge,we propose a novel numerical scheme that integrates the lattice Boltzmann method(LBM)and lattice spring model(LSM).In this scheme,LBM simulates vis-coacoustic wave propagation in the fluid area and LSM simulates elastic wave propagation in the solid area.We also introduce three different LBM-LSM coupling strategies,a standard bounce back scheme,a specular reflection scheme,and a hybrid scheme,to describe wave propagation across fluid-solid boundaries.To demonstrate the accuracy of these LBM-LSM coupling schemes,we simulate wave propagation in a two-layer model containing a fluid-solid interface.We place excitation sources in the fluid layer and the solid layer respectively,to observe the wave phenomena when seismic waves propagate to interface from different sides.The simulated results by LBM-LSM are compared with the reference wavefields obtained by the finite difference method(FDM)and the analytical solution(ANA).Our LBM-LSM coupling scheme was verified effective,as the relative errors between the LBM-LSM so-lutions and reference solutions were within an acceptable range,sometimes around 1.00％.The coupled LBM-LSM scheme is further used to model seismic wavefields across a more realistic rugged seabed,which reveals the potential applications of the coupled LBM-LSM scheme in marine seismic imaging techniques,such as reverse-time migration and full-waveform inversion.The method also has potential applications in simulating wave propagation in complex two-and multi-phase media.
查看更多>>摘要：Remote reflection waves,essential for acquiring high-resolution images of geological structures beyond boreholes,often suffer contamination from strong direct mode waves propagating along the borehole.Consequently,the extraction of weak reflected waves becomes pivotal for optimizing migration image quality.This paper introduces a novel approach to extracting reflected waves by sequentially operating in the spatial frequency and curvelet domains.Using variation mode decomposition(VMD),single-channel spatial domain signals within the common offset gather are iteratively decomposed into high-wavenumber and low-wavenumber intrinsic mode functions(IMFs).The low-wavenumber IMF is then subtracted from the overall waveform to attenuate direct mode waves.Subsequently,the curvelet transform is employed to segregate upgoing and downgoing reflected waves within the filtered curvelet domain.As a result,direct mode waves are substantially suppressed,while the integrity of reflected waves is fully preserved.The efficacy of this approach is validated through processing synthetic and field data,underscoring its potential as a robust extraction technique.
查看更多>>摘要：Seismic finite-difference(FD)modeling suffers from numerical dispersion including both the temporal and spatial dispersion,which can decrease the accuracy of the numerical modeling.To improve the accuracy and efficiency of the conventional numerical modeling,I develop a new seismic modeling method by combining the FD scheme with the numerical dispersion suppression neural network(NDSNN).This method involves the following steps.First,a training data set composed of a small number of wavefield snapshots is generated.The wavefield snapshots with the low-accuracy wavefield data and the high-accuracy wavefield data are paired,and the low-accuracy wavefield snapshots involve the obvious numerical dispersion including both the temporal and spatial dispersion.Second,the NDSNN is trained until the network converges to simultaneously suppress the temporal and spatial dispersion.Third,the entire set of low-accuracy wavefield data is computed quickly using FD modeling with the large time step and the coarse grid.Fourth,the NDSNN is applied to the entire set of low-accuracy wavefield data to suppress the numerical dispersion including the temporal and spatial dispersion.Numerical modeling examples verify the effectiveness of my proposed method in improving the computational accuracy and efficiency.
查看更多>>摘要：High resolution of post-stack seismic data assists in better interpretation of subsurface structures as well as high accuracy of impedance inversion.Therefore,geophysicists consistently strive to acquire higher resolution seismic images in petroleum exploration.Although there have been successful applications of conventional signal processing and machine learning for post-stack seismic resolution enhancement,there is limited reference to the seismic applications of the recent emergence and rapid development of generative artificial intelligence.Hence,we propose to apply diffusion models,among the most popular generative models,to enhance seismic resolution.Specifically,we apply the classic diffusion mod-el-denoising diffusion probabilistic model(DDPM),conditioned on the seismic data in low resolution,to reconstruct corresponding high-resolution images.Herein the entire scheme is referred to as SeisRe-soDiff.To provide a comprehensive and clear understanding of SeisResoDiff,we introduce the basic theories of diffusion models and detail the optimization objective's derivation with the aid of diagrams and algorithms.For implementation,we first propose a practical workflow to acquire abundant training data based on the generated pseudo-wells.Subsequently,we apply the trained model to both synthetic and field datasets,evaluating the results in three aspects:the appearance of seismic sections and slices in the time domain,frequency spectra,and comparisons with the synthetic data using real well-logging data at the well locations.The results demonstrate not only effective seismic resolution enhancement,but also additional denoising by the diffusion model.Experimental comparisons indicate that training the model on noisy data,which are more realistic,outperforms training on clean data.The proposed scheme demonstrates superiority over some conventional methods in high-resolution reconstruction and denoising ability,yielding more competitive results compared to our previous research.
查看更多>>摘要：The resistivity difference between oil and gas layers and the water layers in low contrast tight sandstone reservoirs is subtle.Fluid identification and saturation calculation based on conventional logging methods are facing challenges in such reservoirs.In this paper,a new method is proposed for fluid identification and saturation calculation in low contrast tight sandstone reservoirs.First,a model for calculating apparent formation water resistivity is constructed,which takes into account the influence of shale on the resistivity calculation and avoids apparent formation water resistivity abnormal values.Based on the distribution of the apparent formation water resistivity obtained by the new model,the water spectrum is determined for fluid identification in low contrast tight sandstone reservoirs.Following this,according to the average,standard deviation,and endpoints of the water spectrum,a new four-parameter model for calculating reservoir oil and gas saturation is built.The methods proposed in this paper are applied to the low contrast tight sandstone reservoirs in the Q4 formation of the X53 block and X70 block in the south of Songliao Basin,China.The results show that the water spectrum method can effectively distinguish oil-water layers and water layers in the study area.The standard deviation of the water spectrum in the oil-water layer is generally greater than that in the water layer.The new four-parameter model yields more accurate oil and gas saturation.These findings verify the effectiveness of the proposed methods.
查看更多>>摘要：The main objective is to optimize the development of shale gas-rich areas by predicting seismic sweet spot parameters in shale reservoirs.We systematically assessed the fracture development,fracture gas content,and rock brittleness in fractured gas-bearing shale reservoirs.To better characterize gas-bearing shale reservoirs with tilted fractures,we optimized the petrophysical modeling based on the equivalent medium theory.Based on the advantages of shale petrophysical modeling,we not only considered the brittle mineral fraction but also the combined effect of shale porosity,gas saturation,and total organic carbon(TOC)when optimizing the brittleness index.Due to fractures generally functioning as essential channels for fluid storage and movement,fracture density and fracture fluid identification factors are critical geophysical parameters for fractured reservoir prediction.We defined a new fracture gas indi-cation factor(GFI)to detect fracture-effective gas content.A new linear PP-wave reflection coefficient equation for a tilted transversely isotropic(TTI)medium was rederived,realizing the direct prediction of anisotropic fracture parameters and the isotropic elasticity parameters from offset vector tile(OVT)-domain seismic data.Synthetic seismic data experiments demonstrated that the inversion algorithm based on the LP quasinorm sparsity constraint and the split-component inversion strategy exhibits high stability and noise resistance.Finally,we applied our new prediction method to evaluate fractured gas-bearing shale reservoirs in the Sichuan Basin of China,demonstrating its effectiveness.
查看更多>>摘要：Fracture geometry is important when stimulating low-permeability reservoirs for natural gas or oil production.The geological layer(GL)properties and contrasts in in-situ stress are the two most important parameters for determination of the vertical fracture growth extent and containment in layered rocks.However,the method for assessing the cumulative impact on growth in height remains ambiguous.In this research,a 3D model based on the cohesive zone method is used to simulate the evolution of hydraulic fracture(HF)height in layered reservoirs.The model incorporates fluid flow and elastic deformation,considering the friction between the contacting fracture surfaces and the interaction between fracture components.First,an analytical solution that was readily available was used to validate the model.Afterwards,a quantitative analysis was performed on the combined impacts of the layer interface strength,coefficient of interlayer stress difference,and coefficient of vertical stress difference.The results indicate that the observed fracture height geometries can be categorized into three distinct regions within the parametric space:blunted fracture,crossed fracture,and T-shaped fracture.Furthermore,the results explained the formation mechanism of the low fracture height in the deep shale reservoir of the Sichuan Basin,China,as well as the distinction between fracture network patterns in mid-depth and deep shale reservoirs.
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