ABSTRACTS

Detectionofmicroseismiceventsbasedonresidualnetworkandseismicemissiontomography.WANGWeibo1,GUANQiang1,GAOMing1,andSHENGLi1.OilGeophysicalProspecting,2022,57(2):251-260.

Seismic emission tomography (SET) is a hypocentral location method suitable for surface microseismic monitoring. This method makes use of the monitoring signals from many stations on the ground to image a specific area of a reservoir layer by layer. The images are used to determine whether there are microseismic events and where the hypocenter coordinates are. In traditional processing methods, whether the SET images of a section of signal contain an effective microseismic event is usually judged by human experiences. It is difficult to process all the massive monitoring data manually, and thus it cannot make full use of the advantages of the SET method. To solve this problem, a residual network is proposed to process SET images of microseismic monitoring data, which can detect microseismic events automatically. Firstly, a large number of SET images are produced using synthetic data and actual surface microseismic monitoring data of an oil well with hydraulic fracturing, and these SET images are used to construct a sample data set for training and testing a residual network. In this way, a residual network model with the highest accuracy of event detection is obtained. Then, the trained residual network model is employed to detect and locate microseismic events from other SET images produced by synthe-tic signals with different signal-to-noise ratios and surface microseismic monitoring data of other oil & gas wells with hydraulic fracturing. The test results prove that the proposed method can detect microseismic events effectively and has good noise suppression and generalization abilities.

Keywords： microseismicity, event detection, hypocentral location, seismic emission tomography, residual network, model training

1. College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, Shandong 266580, China

Seismicfaciesclusteringtechnologybasedondeepembeddingnetwork.LIQixin1,LUOYaneng2,MAXiaoqiang1,CHENCheng1,andZHUYanhe1.OilGeophysicalProspecting,2022,57(2):261-267.

The early seismic facies clustering based on machine learning relies on the selection and combination of seismic attributes, leading to strong subjectivity of results. Nevertheless, this defect can be overcome by data-driven deep learning. Therefore,with deep learning technology, the autoencoder network is adopted to generate embedding code that can be used for abstract representation of seismic data. The clustering loss function and the reconstruction loss function are introduced to build a combined loss function, which is then optimized so that the seismic features learned can not only be used to reconstruct seismic data but also have favorable clustering ability. The proposed method is applied to a tight gas exploration area A in Ordos Basin. The following observations are drawn from the results: After 500 iterations, the embedding code has noticeable clustering features, and the original seismic signals can be well reconstructed with a relative error of less than 5%; compared with that in the case of the root-mean-square (RMS) amplitude attribute, the seismic facies map calculated by the seismic facies clustering technology based on deep embedding network delineates channels more accurately with richer detail; compared with the K-means clustering algorithm, the proposed technology delivers a prediction result that has a higher coincidence rate between seismic data and well logging data, which can reach 89.3%.

Keywords: seismic facies analysis, convolutional autoencoder network, deep learning, feature re-presentation

1. CNOOC Research Institute Co., Ltd., Beijing 100028, China

2. Geophysical Research & Development Center, BGP Inc., CNPC, Zhuozhou, Hebei 072751, China

ResearchonrandomnoiseattenuationmethodforseismicdatafromdesertsbasedonDBBCNN.ZHONGTie1,2,CHENYun2,DONGXintong3,LIYue4,andYANGBaojun5.OilGeophysicalProspecting,2022,57(2):268-278.

In the desert area of the Tarim Basin, the collected exploration data generally has a low signal-to-noise ratio (SNR) due to the harsh collection environment and complex surface geological conditions. In addition, spectrum aliasing exists between random noise and effective signals, and noise suppression is challenging, which have negative impacts on subsequent procedures such as inversion, imaging, and interpretations. In recent years, deep learning denoising methods, represented by feed-forward denoising convolutional neural networks (DnCNNs), have been employed to suppress complex random noise. However, traditional denoising networks generally extract data features on the basis of single-scale information, which results in the degeneration of denoising capability when confronting complex exploration data. To achieve effective attenuation of complex noise from deserts, this paper proposed a new denoising network, namely the diverse branch block convolutional neural network (DBBCNN). Unlike traditional networks, DBBCNN combines the branches in different scales and complexity to enrich the feature space. Then, the long-path operation fuses global and local features to improve the feature expression ability of the network for weak signals. Both simulations and field experimental results show that the proposed method can effectively suppress the complex random noise from deserts with a significant increment of SNR.

Keywords：desert seismic, convolutional neural network, DnCNN, denoising network, signal-to-noise ratio

1. Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technolo-gy, Ministry of Education, Jilin, Jilin 132012, China

2. Department of Communication Engineering, Northeast Electric Power University, Jilin, Jilin 132012, China

3. College of Instrumentation and Electrical Engineering, Jilin University, Changchun, Jilin 130026, China

4. College of Communication Engineering, Jilin University, Changchun, Jilin 130012, China

5. College of Geo-exploration Science and Technolo-gy, Jilin University, Changchun, Jilin 130026, China

Seismicimpedanceinversionmethodbasedontemporalconvolutionalneuralnetwork.WANGZefeng1,XUHuiqun1,YANGMengqiong1,andZHAOYasong1.OilGeophysicalProspecting,2022,57(2):279-286,296.

Seismic impedance inversion is an important method for reservoir prediction. The accuracy of linear seismic impedance inversion methods depends on the quality of the initial geological model. To get a high-accuracy solution, one can adopt a completely nonlinear method. In view of this, a temporal convolutional neural network (TCN) is first constructed by using a fully convolutional neural network, dilated convolution, causal convolution and a residual block. On this basis, a nonlinear mapping relationship is established between seismic data and wave impedance. Then, samples are trained by the network to yield an inverse mapping model. Further, seismic impedance is obtained by inputting seismic data into the model. According to the test results of forward data and actual data, the method realizes the mapping between seismic data and seismic impedance. It provides an intelligent method with parallel computing power and adaptive structure for seismic impedance inversion and has been applied in sandstone and mudstone reservoir prediction of Gang 2025 Block.

Keywords：seismic impedance inversion, temporal convolutional neural networks, inversion mapping model, reservoir prediction

1. College of Geophysics and Petroleum Resources, Yangtze University, Wuhan, Hubei 430100, China

Apredictionmethodoffractureaperturebasedonhierarchicalexpertcommitteemachinemodelfortightreservoirs.ZHOUYou1,2,ZHANGGuangzhi1,2,ZHANGShengze1,2,LIUJunzhou3,andHANLei3.OilGeophysicalProspecting,2022,57(2):287-296.

Fracture aperture is a key parameter for cha-racterizing the quality of tight reservoirs and evalua-ting oil and gas productivity. Tight reservoirs have strong heterogeneity due to the influences of sedimentation, diagenesis, and tectonism, resulting in complex and irregular logging response characteristics. Consequently, it is difficult to accurately predict reservoir fracture aperture by the conventional logging interpretation method or with a single machine learning model. To solve this problem, this paper proposes a prediction method of fracture aperture based on the hierarchical expert committee machine model for tight reservoirs. Firstly, the parameters of reservoir fracture aperture are obtained from core and imaging logging data, and sensitive logging data at same depth are selected as characteristic variables to construct a sample set. Secondly, the kernel ridge regression, support vector regression, and BP neural network are used as the basic expert network units to train and learn the sample set. Thirdly, the initial weight of each basic expert network unit is adaptively generated by hierarchical network modules built with the hierarchical structure model and the gated neural network model. Lastly, the prediction performance of each basic expert network unit is comprehensively considered. The contribution of each basic expert network to the final output is determined by alternating conditional expectation transform, and the fracture aperture of the reservoir is thereby accurately predicted. The practical application shows that this method can effectively quantitatively characterize the reservoir fracture aperture in a well and provide reliable geophysical information for the evaluation of tight reservoirs.

Keywords：tight oil and gas reservoir, fracture aper-ture, hier-archical expert committee machine, hier-archical structure, gated neural network model

1.Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao, Shandong 266580, China

2. School of Geosciences, China University of Petroleum (East China), Qingdao, Shandong 266580, China

3. SINOPEC Petroleum Exploration and Production Research Institute, Beijing 100083, China

Optimizationofbroadbandseismicwaveletsfromtheperspectiveofoctaves.ZHANGBaojin1,2,PENGKe1,CHENGGu3,BIANDonghui1,LIUYuping1,2,andLIFuyuan1,2.OilGeophysicalProspecting,2022,57(2):297-302.

Broadband seismic processing technology can effectively broaden the data frequency band and improve the resolution of seismic data. As one of the main means of marine broadband seismic data processing, the de-ghosting method is greatly sensitive to parameters such as water depth and the speed of sound, and the spectral morphology of data after de-ghosting is often significantly different, which makes it difficult to accurately interpret seismic data. Therefore, on the premise of fully considering the energy distribution of each frequency component of broadband data, a broadband seismic wavelet optimization method from the perspective of octaves was proposed. Firstly, the loga-rithm of each frequency value was taken, and a smooth amplitude spectrum curve was constructed in the octave coordinate system. Then, the curve was transformed into the ordinary coordinate system, and the broadband wavelet was reconstructed with the zero phase. Finally, a broadband seismic wavelet with clear physical meaning was obtained, which is referred to as an “octave wavelet”. The practical application results show that the wavelet proposed can be applied to the wavelet shaping of broadband seismic data after de-ghosting, and it can eliminate the spectral morphological difference caused by the change in parameters during de-ghosting and improve the quality of seismic profiles.

Keywords：wavelet, broadband seismic, octave, broadband processing, high resolution

1. Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, Guangdong 511458, China

2. Guangzhou Marine Geological Survey (Guangzhou), Guangzhou, Guangdong 510760, China

3. School of Earth Sciences and Engineering, Sun Yat-Sen University, Zhuhai, Guangdong 519082, China

InversionofRayleighwavedispersioncurvesbasedonparticleswarmandantcolonyhybridoptimization.WANGYiming1,SONGXianhai1,2,andZHANGXueqiang1.OilGeophysicalProspecting,2022,57(2):303-310,356.

Inversion of the Rayleigh surface-wave dispersion curve to obtain the shear-wave (S-wave) velocity profile of an underground medium is one of the important steps in surface-wave exploration. The traditional linear inversion method cannot meet the needs of geophysical exploration, and the nonlinear inversion method has instead become a research hotspot. In this paper, a nonlinear optimization algorithm based on the particle swarm optimization (PSO) algorithm and the ant colony optimization (ACO) algorithm is applied to the nonlinear inversion of the Rayleigh surface-wave dispersion curve to obtain the underground S-wave velocity profile. This algorithm uses the pheromone guidance mechanism to update the positions of particles in the early stage. It fully combines the guidance strategy of the PSO algorithm for the global optimal solution with the local search ability of the ACO algorithm. Meanwhile, it overcomes the shortcoming of the PSO algorithm that particle swarm update comes to a standstill when the population is in a state of equilibrium and the defect of the ACO algorithm that convergence is premature when it is applied to solve the multi-extremum function. The effectiveness and stability of the proposed algorithm are examined by the inversion of the dispersion curves of various theoretical mo-dels; the comparison of the inversion results of this algorithm with those of the ACO and PSO algorithms alone verifies its superiority; Inversion results of measured data further test the practicability of this algorithm.

Keywords：Rayleigh wave, dispersion curve, nonlinear inversion, particle swarm optimization algorithm, ant colony optimization algorithm

1. Institute of Geophysics & Geomatics, China University of Geosciences (Wuhan), Wuhan, Hubei 430074, China;

2. Hubei Subsurface Multiscale Image Key Laboratory, China University of Geosciences (Wuhan), Wuhan, Hubei 430074, China

AninversionmethodforarbitraryweakanisotropyparametersbasedonVSPdata.CHENZhanguo1,ZENGZhaohan1,andYANGXinchao1.OilGeophysicalProspecting，2022,57(2):311-319.

Vertical seismic profile (VSP) data boast a high signal-to-noise ratio and accurate depth information. Information such as traveltime in VSP data can be used to obtain vertical transversely isotropic (VTI) and tilted transversely isotropic (TTI) anisotropy parameters of the formation through inversion. However, it is difficult to determine arbitrary anisotropy parameters in this way. Polarization and slowness vectors are direct parameters that characterize the elastic matrix in the Christoffel equation and can be measured by VSP without being influenced by overlying strata. VSP also enjoys an advantage in accurate depth information. Therefore, it is available for obtaining arbitrary weak anisotropy parameters of a medium through inversion. To start with, we present a solution method for the Christoffel equation based on the perturbation theory and introduce forward and inversion formulas for slowness and polarization vectors of the qP wave. Then, we provide a high-precision acquisition method for slowness and polarization vectors based on Walkaway VSP mea-surement. Finally, a weighted iterative inversion algorithm for arbitrary weak anisotropy parameters is proposed. A maximum of 15 weak anisotropy parameters are worked out with model data, and the results are highly consistent with the theoretical values. Application on field data further shows that the proposed method, with high precision, applies to extraction of seismic anisotropy parameters.

Keywords：VSP, anisotropy parameter, slowness, polarization

1. Geophysical Research Institute, SINOPEC, Nanjing, Jiangsu 211103, China

AmplitudespectralintegraldifferencemethodforQestimationbasedonTaylorseriesexpansion.ZHANGJin1,ZHANGGuoshu2,WANGYanguo1,3,andLIHongxing1.OilGeophysicalProspecting，2022,57(2):320-330.

The quality factorQis a very important parameter for seismic data processing and interpretation, which can be used to improve the vertical resolution of seismic data and reflect reservoir characteristics. The lengths of time window and bandwidth are two key parameters forQestimation. In addition,Qestimation is easily susceptible to noise interference. To overcome these problems, this paper introduces a new method called the amplitude spectral integral difference (ASID) method based on Taylor series expansion forQestimation. In this method, the amplitude attenuation term is first subjected to the second-order Taylor series expansion. Then, an equation includingQvalue is established utilizing the difference between amplitude spectra of seismic wavelets at different moments. Finally, the equation is solved to estimate theQvalue. Model tests indicate that the ASID method is less influenced by noise interference and the lengths of time window and frequency bandwidth and is more suitable forQestimation of seismic data with thin layers, compared with the logarithmic spectral ratio (LSR) method, the centroid frequency shift (CFS) method and the logarithmic spectral area difference (LSAD) method. The ASID method is also applied to a CMP gather of marine seismic data. The results ofQestimation by the new method are close to those of the LASD method.

Keywords：Qestimation, Taylor series expansion, amplitude spectrum, thin layer

1. School of Geophysics and Measurement-control Technology, East China University of Technology, Nanchang, Jiangxi 330013, China

2. School of Nuclear Science and Engineering, East China University of Technology, Nanchang, Jiangxi 330013, China

3. State Key Laboratory of Nuclear Resources and Environment, East China University of Technology, Nanchang, Jiangxi 330013, China

Asimplifiedpurevisco-acousticwaveequationfor3DTTImediaanditsnumericalsimulation.XUShigang1,BAOQianzong1,andRENZhiming1.OilGeo-physicalProspecting,2022,57(2):331-341.

As earth media are generally characterized by inelasticity and anisotropy, both anisotropy and viscosity should be considered in research on seismic wave propagation in underground spaces. At present, pseudo-acoustic wave equations are the ones mainly applied in wavefield simulation, migration imaging, and waveform inversion regarding anisotropic media. As these equations are deve-loped on the basis of a shear-wave (S-wave) velocity directly set to zero, numerical pseudo-S wave artifacts and simulation instability are prone to occur when medium parameters do not satisfy the assumed conditions. Given the problem faced with pseudo-acoustic wave equations, this paper solves the high-precision pure acoustic wave equation for 3D tilted transversely isotropic (TTI) media by combining the Poisson operator with finite diffe-rence. Moreover, considering the influence of attenuating media on the amplitude and phase of seismic waves, this paper derives a simplified pure visco-acoustic wave equation for 3D TTI media on the basis of the isotropic visco-acoustic wave equation. This equation can be used to simulate the phase distortion and amplitude attenuation of pure acoustic waves. The effectiveness and applicability of the proposed method are verified with a 3D la-yered model, a TTI wedge model, and a modified Marmousi model.

Keywords：anisotropy, attenuating medium, wave equation, pure acoustic wave, numerical simulation

1. Department of Geophysics, School of Geological Engineering and Geomatics, Chang’an University, Xi’an, Shaanxi 710054, China

Afinite-differenceschemeinfrequency-spacedomaintosolveheterogeneousacousticwaveequation.WUYou1,2,WUGuochen1,2,LIQingyang1,2,YANGLingyun1,2,andJIAZongfeng1,2.OilGeophysicalProspecting,2022,57(2):342-356.

To accurately and efficiently simulate the propagation of acoustic wave in heterogeneous media, this paper constructed a general framework of finite-difference simulation of heterogeneous acoustic wave equations in frequency-space domain using a staggered grid and a hybrid grid. The finite-difference schemes of the staggered grid and the hybrid grid were respectively derived and extended to higher-order forms. The weighted avera-ge method was employed to approximate the mass acceleration term, and the perfectly matched layer (PML) absorbing boundary condition was used to effectively suppress the artificial boundary reflection. The accuracy of the method was verified by a layered model, and its stability was examined by the Marmousi model. Numerical experiments show that under the same space subdivision precision, the simulation accuracy of the hybrid grid and the fourth-order staggered grid is much higher than that of the second-order staggered grid. Although the simulation accuracy of the hybrid grid is slightly lower than that of the fourth-order staggered grid, it has higher computational efficiency. Thus, the hybrid grid method can be the first choice for the forward modeling of acoustic wave in heterogeneous media in a frequency domain.

Keywords：heterogeneous acoustic wave equation, frequency-space domain, finite difference, numerical simulation, staggered grid

1. School of Geosciences, China University of Petroleum (East China), Qingdao, Shandong 266580, China

2. Laboratory for Marine Mineral Resources, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266071, China

Seismicrockphysicsmodelingandshearwavevelocitypredictionmethodofcoalmeasurestrata.ZHOUQi1,2,YINXingyao1,2,andLIKun1,2.OilGeophysicalProspecting,2022,57(2):357-366.

The development potential of oil and gas resources in coal measure strata is great. However, existing seismic rock physics modeling methods lack systematic research on petrophysical properties of reservoirs containing coal. In response, a self-consistent approximation (SCA) model was used to couple the influence of coal and added it to the background medium in the form of inclusion. In this way, a seismic rock physics model was constructed which was suitable for coal-bearing reservoirs. The sensitive elastic parameters characterizing physical properties of reservoirs were selected according to the analysis of how the rock elastic modulus was influenced by microphysical parameters, such as the proportion of coal seam, shale content, water saturation, and porosity. The objective function of petrophysical inversion was derived with P-wave velocity as constraint, and S-wave velocity was predicted by using simulated annealing global optimization algorithm. The method was applied to actual logging data, and the predicted shear wave velocity was in good agreement with the measured data, which proved the applicability of the model to coal measure strata.

Keywords：coal measure strata, rock physics model, shear wave velocity prediction, sensitivity analysis

1. School of Geosciences, China University of Petroleum (East China), Qingdao, Shandong 266580, China

2. Laboratory for Marine Mineral Resources, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266071, China

Predictionforformationpressurecoefficientsbasedonanequivalentpetrophysicalmodelofshale.CHENChao1,2,YINXingyao1,CHENZuqing2,LIUXiaojing2,andXIEJiatong2.OilGeophysicalProspecting，2022,57(2):367-376,394.

In recent years, shale gas exploration and development have shown a positive correlation between shale gas production and pressure coefficients, but the accurate seismic prediction is difficult. Shale gas reservoirs contain rich organic matter and pores, and the mineral composition and microstructure are more complex than those of conventional reservoirs. Therefore, this paper built a petrophysical model suitable for marine shale and proposed a coefficient prediction technology for shale formation pressure. Firstly, in combination with the microstructure characteristics of shale re-servoirs and the difference in supporting minerals, the background medium was simulated by SCA and DEM models separately, and an equivalent petrophysical model was constructed given the characteristics of pores and fluids. Secondly, the bulk modulus of the background medium and the equi-valent rock bulk modulus of saturated fluids were calculated, and it was found that the difference between the two moduli positively correlated with the actual drilling pressure coefficient. On this basis, a seismic prediction model was built. Finally, a direct inversion method for the bulk modulus of Gray approximation-based elastic impedance was derived and developed, which realizes the quantitative prediction of the bulk modulus and pressure coefficients of shale formation. The predicted results are in good agreement with actual drilling and poste-rior wells.

Keywords：marine shale, petrophysics, background medium, saturated fluid, pressure coefficient, elastic impedance

1. School of Geosciences, China University of Petroleum (East China), Qingdao, Shandong 266580, China

2. SINOPEC Exploration Branch Co., Chengdu, Sichuan 610041, China

Methodofconnectedporosityevaluationandquantitativepermeabilitycalculationforcomplexreservoirs.LIXiongyan1,QINRuibao1,CAOJingji1,WANGPeng1,LIUXiaomei1,andPINGHaitao1.OilGeophysicalProspecting,2022,57(2):377-385.

Complex reservoirs of similar porosity gene-rally have largely different permeability. To reveal the reason for this phenomenon, we conduct experiments such as those with casting thin sections, nuclear magnetic resonance (NMR), and computed tomography (CT) scan imaging to evaluate the connectivity of pores. Connected porosity is a main contributing parameter to permeability. For this reason, approaching from the conductive mechanism of rock pore spaces, we build a calculation model for connected porosity with conductive porosity as a bridge. Then, the functional relationship between connected porosity and total porosity is analyzed for 12 types of rocks. A universal NMR T2 model is built on the basis of the calculation model for connected porosity. With limestone re-servoirs as an example, a porosity index model is derived and developed from the perspective of the permeability difference among different types of rocks under the condition of similar porosity. The distribution range of the porosity index is thereby determined. With the universal NMR T2 model, the average absolute error in permeability prediction for limestone reservoirs is reduced from 20.41mD to 0.83mD. The proposed method holds great theore-tical and practical significance.

Keywords： complex reservoir, connected porosity, conductive porosity, porosity index, permeability, limestone

1. CNOOC Research Institute Co., Ltd., Beijing 100028, China

Fastleast-squaresreverse-timemigrationwithadaptivemomentestimation.WUDan1,2,WUHaili1,2,LIQun1,2,ZHANGXiangyang1,2,andLIUShuren1,2.OilGeophysicalProspecting,2022,57(2):386-394.

Least-squares reverse-time migration (LSRTM) is a seismic imaging method with high resolution and favorable amplitude fidelity. However, its computational burden is heavy since it often needs to run iterations nearly ten times and takes approximately the computational cost of two full-dataset RTMs for each iteration. Here, we introduce the adaptive moment estimation (Adam) method from the field of deep learning to improve the computational efficiency of LSRTM: At each iteration, only part of the common shot gathers are required to calculate the gradient and the resulting gradient is corrected by the momentum (AdaGrad) method; considering the nonstationary property of the gradient, the root mean square propagation (RMSProp) algorithm is used to eliminate the influence of inadequate illumination. The Adam method, combining the advantages of the AdaGrad method and the RMSProp method, not only reduces the computational burden of each iteration but also improves the convergence speed of the iterations. In addition, this method is straightforward to implement and computationally efficient with a low memory requirement, and thus it is a fast and effective gradient preconditioning method. The A-dam method not only can be applied to LSRTM directly but also is applicable to shot encoding LSRTM. Numerical tests on the SEG/EAGE salt model show that this method can provide a high-precision and high-resolution image at merely the same cost as that of two RTMs. The substantial increase in computational efficiency paves the way for the application of LSRTM in practical seismic data processing.

Keywords：least-squares reverse-time migration, adaptive moment estimation, high resolution, amplitude fidelity, shot encoding

1. Northwest Branch, Research Institute of Petroleum Exploration & Development, PetroChina, Lanzhou, Gansu 730030, China

2. Key Laboratory of Internet of Things, CNPC, Lanzhou, Gansu 730030, China

Determinationofinter-wellconnectivityoffracturedfracturesinglutenitereservoirsbymicroseismicmonitoringresults:acasestudyofMahuOilfieldintheJunggarBasin.LIUWeidong1,LIUTengjiao2,JIYongjun1,ZHANGLifeng1,CHUFangdong2,andZHANGLong1.OilGeophysicalProspecting，2022,57(2):395-404.

At present, the fracture morphology characterized by discrete microseismic event locations only represents the envelope range of fractured fracture networks, and thus it is difficult to accurately characterize the actual artificial fracture morphology in the envelope of fracture networks. Moreover, due to the influence of factors such as the velocity model and first break picking, there is a certain error in the location results of microseismic events, and thus the inter-well connectivity of fractures cannot be determined only by the locations of discrete microseismic events. Therefore, the tracer detection results of the demonstration area Ma 131 in Mahu Oilfield of the Junggar Basin were taken as the basis to determine whether the artificially stimulated fractures between wells were connected. In addition, this paper summarized the rule of the minimum distance between microseismic event locations and adjacent well event locations without the influence of natural fractures and forms a new method to quantitatively evaluate the inter-well connectivity of fractured fractures in glutenite reservoirs. In the Mahu glutenite reservoir, without the influence of natural fractures, microseismic events of adjacent wells cross, and the minimum distance between a microseismic event and an adjacent well event is less than 10 m, which indicates that the fracturing fractures between two wells are connected; otherwise, the minimum distance between a microseismic event and an adjacent well event is more than 10 m, which shows that the fractured fractures between two wells are not connected. The proposed method can evaluate the rationality of well spacing and construction scale and can also be extended to other areas.

Keywords：microseismic, glutenite reservoir, tracer, inter-well connectivity, well spacing

1. Development Company, Xinjiang Oilfield Company, CNPC, Karamay, Xinjiang 834000, China

2. New Resources Geophysical Exploration Division, BGP Inc., CNPC, Zhuozhou, Hebei 072751, China

AstrongshieldingremovalmethodofreflectioncoefficientdomainbasedoncompressedsensingwithL2normconstraintalonglayer.ZHANGJunhua1,WANGJing2,WANGYanguang3,LIULibin3,LIHongmei3,andWANGXi’an1.OilGeophysicalProspecting,2022,57(2):405-413.

Conventional compressed sensing methods are based on the sparse inversion of reflection coefficients to improve the resolution of seismic data. However, if the strong shielding layer information and the weak reservoir information are superimposed, the reservoir cannot be effectively predicted, because the information of the weak reflection layer will be lost when the strong shielding layer is removed. For this reason, taking advantage of the strong sparse representation ability of compressed sensing and the high resolution of the reflection coefficient domain without wavelet overlap, this paper proposes a strong shielding removal method of reflection coefficient domain based on compressed sensing with L2norm constraint along the layer. This method is based on the theory of compressed sensing. First, according to the sparse characteristics of the reflection coefficient in the time domain, the strong shielding layer and the reservoir are separated using the information along the layer. Then the sparse inversion is performed, and finally the reflection coefficient after strong shielding removal is convolved with the original wavelet to obtain the high-resolution results in the absence of a strong shielding layer. The advantage of the method is that the high-resolution reflection coefficient can separate the information of the strong shielding layer and the reservoir, which is beneficial to extract and remove the strong shielding layer. The model tests and actual seismic data application show that the proposed method can accurately separate the reflection information of the strong shielding layer from the weak reflection information of the reservoir and thus improve the accuracy of reservoir identification. On the time-frequency slices after strong shielding layer removal, the weak energy of the reservoir can be seen, and low-frequency accompanying phenomena appear. On the energy half-time attribute slices along the layer after strong shielding removal, the attribute has a good correlation with the beach-bar sand reservoir, which can effectively identify favorable reservoir areas.

Keywords：compressed sensing, information along layer, L2norm constraint, strong shielding, remove, sparse inversion

1. School of Geosciences, China University of Petroleum (East China), Qingdao, Shandong 266580, China

2. Key labortory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao, Shandong 266580, China

3.Exploration and Development Research Institute, Shengli Oilfield Branch Company, SINOPEC, Dongying, Shandong 257015, China

4. Geophysical Research Institute, Shengli Oilfield Branch Company, SINOPEC, Dongying, Shandong 257022, China

Identificationtechnologyforinternalstructuresofcarbonatefault-karstanditsapplication.CHANGShaoying1,2,ZENGJianhui1,XUXuhui3,CAOPeng2,CUIYuyao1,andLITao4.OilGeophysicalProspecting，2022,57(2):414-422.

Carbonate fault-karst is an important new type of carbonate trap discovered in recent years. The difficulty in identifying the internal structures of fault-karst, however, has been restricting the full exploration of reserve potential, the efficient development of oil reservoirs, and the improvement of the success rate of new wells put into production. Conventional methods for fracture detection such as coherence, curvature, and ant tracking mainly characterize the distribution characteristics of fractures, which cannot well describe the external outline and internal structural characteristics of fault-karst traps. In addition, seismic reflection characteristic analysis is an important technical means to identify the internal structural characteri-stics of fault-karst. Firstly, by the actural seismic data, a fault-karst geological model was built based on the pattern of ‘adjacent rock/fractured zone/main fractured zone of oil sources/fractured zone/adjacent rock’, and the seismic response characteristics of each zone were analyzed. The consistency in the seismic reflection phase at the top of fault-karst was utilized to remove the reflection waveform influence from overlying formation and highlight the reservoir characteristics of weak reflection amplitude energy of fault-karst. Then, the external outline of the fault-karst system was identified by using the gradient attributes of the orthogonal composite tensor. Finally, the data free from the influence of overlying formation waveforms was employed for waveform indication inversion, and with the tensor gradient attribute as a constraint, the inversion data volume that can characterize the external contour and internal structural characteristics of fault-karst could obtain. The practical application of the research provide important technical support for suggestions including the selection of efficient wells, the exploration of fault-karst with remaining oil potential, enhanced oil recovery, and the implementation of measure wells. Therefore, the research has a great value of applicability.

Keywords：fault-karst reservoir, fracture-cavity structure, tensor gradient, wareform indication inversion, small-throw fault identification

1. College of Geosciences, China University of Petroleum, Beijing 102200, China

2. Hangzhou Research Institute of Geology, Pe-troChina, Hangzhou, Zhejiang 310023, China

3. Geophysical Research Institute, SINOPEC, Nanjing, Jiangsu 211103, China

4. BGP Intl., CNPC, Zhuozhou, Hebei 072751, China

FracturepredictionmethodbasedonFourierseriesofazimuthalelasticimpedance.LIUXiaojing1,CHENZuqing1,CHENChao1,andXIAOQiu-hong1.OilGeophysicalProspecting,2022,57(2):423-433.

At present, there are mainly two categories of fracture prediction methods. The first type is based on the amplitude or attributes (such as frequency and attenuation) derived from the amplitude of azimuth seismic data. It can only provide the comprehensive response information of the strata on both sides of the interface and fails to determine the fracture information of the overlying or underlying strata. The second type obtains the elastic parameters with the help of azimuthal AVO prestack seismic inversion, which can directly achieve the fracture information of target strata. However, the dimension of the parameters to be inverted is high, and the anisotropic parameter is much smaller than the elastic parameter, with the inversion stability needing to be improved. In response, this paper proposes a fracture prediction method based on the Fourier series of azimuthal elastic impedance. Firstly, the azimuthal elastic impedance equation is derived on the basis of the Rüger’s approximation of the azimuthal AVO reflection coefficient. The interface information of a fractured medium is transformed into the elastic information of the formation. The difference in azimuthal elastic impedance reflects the anisotropy of the formation. Secondly, the azimuthal elastic impedance equation is expanded by Fourier series to obtain the second-order Fourier coefficient . Finally, the normal direction of fracture is obtained through the cross-correlation between azimuthal elastic impedance and cosine function. The model test shows that the fracture prediction method based on the Fourier series expansion of azimuthal elastic impedance can well predict the development and normal direction of fracture with high accuracy and strong noise resistance. The performance on actual data indicates that the fracture prediction results are consistent with the imaging logging results, which proves that the method has high accuracy.

Keywords：azimuthal elastic impedance, Fourier series expansion, fracture prediction, normal direction of fracture, anisotropy

1. Geophysical Research Institute, Exploration Branch Co., SINOPEC, Chengdu, Sichuan 610041, China

Characteristics,genesisandquantitativecharacterizationofhigh-velocityanomalyzoneinstrike-slipandextensionalstresszone:acasefromLowerMemberofMinghuazhenFormationofLaibeiLowUpliftintheBohaiBayBasin.SUNXijia1,ZHANGZhongqiao1,XIEXiang1,andGONGMin1.OilGeo-physicalProspecting,2022,57(2):434-440.

Extensional stress and strike-slip shear stress jointly control the formation and evolution of the Laibei Low Uplift. It is found during drilling that the lateral velocity changes greatly, which seriously affects pre-drilling depth prediction and following progressive exploration. Therefore, logging data, 3D seismic data and seismic velocity data are used to study the high-velocity anomaly in the strike-slip and extensional stress zone of Laibei Low Uplift. After the analysis of the regional stress field mechanism and the compaction amount, this paper discusses the control effect of structure on the lateral variation of velocity and the cause of the high-velocity anomaly. The method of removing normal compaction is utilized to quantitatively describe the high-velocity anomaly zone. The results show the followings: ① In the strike-slip and extensional stress zone, the internal strata of the en echelon T fracture zone are affected by not only vertical normal compaction but also horizontal tectonic compression produced by the secondary compression component. The horizontal tectonic compression is the cause of the shallow NE-trending high-velocity anomaly zone in the Laibei Low Uplift. ② The high-velocity anomaly zone spreads along the en echelon T fracture, and its distribution is controlled by the range of fault activities. Besides, the amount of high-velocity anomaly and the fault activity intensity have a strong positive correlation, which is consistent with the development law of the high-velocity anomaly zone.

Keywords：high-velocity anomaly, horizontal tectonic compaction, strike-slip and extensional stress zone, en echelon T fracture, Laibei Low Uplift

1. Bohai Oilfield Research Institute, Tianjin Branch of CNOOC Ltd., Tianjin 300459, China

Analysisofinfluencingfactorsinreservoirdescriptionaccuracybyseismicinversion.FANZhonghai1,HUBo1,SONGJijie1,LIUHaojie2,SHENGuoqiang2,andWANGZhentao2.OilGeophysicalProspecting,2022,57(2):441-451.

In the process of efficient exploration and development of oilfields, it is urgent to improve the accuracy of reservoir description. Seismic inversion for reservoir description is a comprehensive oil and gas exploration technology, and its accuracy is affected by complex factors. Therefore, firstly, seismic inversion methods are introduced by classification, and their characteristics and advantages are clarified. Then, the inversion effect is analyzed by using field and synthetic data. Next, we explore the impact of technical links such as reservoir characteristic analysis, logging standardization, well seismic calibration, model construction, and seismic quality. The following conclusions are drawn: Reservoir characteristic recognition, inversion wavelet extraction, constraint model construction, and seismic data quality are the main factors affecting seismic inversion accuracy. In practical applications, it is necessary to carry out fine research on the main influencing factors, diminish the multi-solution property of reservoir identification, and improve the resolution of reservoir description, which is of great significance for the efficient and fine application of seismic inversion technology in oil and gas exploration and development.

Keywords：seismic driven inversion, model driven inversion, reservoir description, logging constraints, model construction, seismic data quality

1. Oilfield Exploration & Development Department, SINOPEC, Beijing 100728, China

2. Geophysical Research Institute, Shengli Oilfield Branch Co., SINOPEC, Dongying, Shandong 257022, China

Multi-componentjointinversionfortime-frequencyelectromagnetic(TFEM)method:AcasestudyofigneousrockprospectinginwesternSichuan.GUOHongxi1,CAOYang2,HEYulin1,WANGYi1,YANGJun2,andKUANGXihan2.OilGeophysicalProspecting,2022,57(2):452-458.

In recent years, non-seismic exploration has played a guiding role in the study of igneous rocks, deep-seated results, and fractures in western Sichuan, especially in the extraction and fine inversion of weak anomaly information by the time-frequency electromagnetic (TFEM) method, which has a good effect in searching for volcanic conduits and exploring the forming mechanism of volcanic rocks. However, the non-plane wave effect, sha-dow effect, and the additional effect of the artificial field source result in the multi-solutions to the data inversion, which leads to the low quality of inversion data imaging or even false anomalies. Multi-component electromagnetic data inversion is an effective method to overcome the difficulties mentioned above. On the basis of the principle of time-frequency electromagnetic exploration, the finite-difference forward modeling formula for the nine-point finite-difference structure of the two-dimensional model and three-dimensional source was derived. According to the principle of regularization inversion, a multi-component joint inversion objective function was constructed, and a multi-component joint inversion algorithm suitable for the time-frequency electromagnetic method was derived. To balance the difference in the order of magnitude between different components, we added the dynamic equilibrium coefficient to the inversion process. The theoretical model test results show that the multi-component joint inversion is more effective than single-component data inversion, and the noisy model test results indicate that the algorithm is correct and reliable and has great anti-noise performance. This method was applied to the observed time-frequency data from western Sichuan, and the inversion results were in good agreement with drilling information and other known information, which shows that the algorithm is practical and effective.

Keywords：time-frequency electromagnetic method(TFEM), multi-component joint inversion, igneous rock

1． Exploration Division, PetroChina Southwest Oil & Gasfield Company, Chengdu, Sichuan 610051, China

2． GME & Geochemical Surveys of BGP, CNPC, Zhuozhou, Hebei 072751, China

SimulationandanalysisofdynamicmonitoringofoilandgasreservoirbasedongroundedelectricsourceTEM.WANGXinyu1,2,YANLiangjun1,2,andMAOYurong1,2.OilGeophysicalProspecting,2022,57(2):459-466.

The change of acoustic impedance is small before and after the remaining oil and gas in a reservoir is displaced by fluid during oil and gas reservoir recovery, which can cause the failure of time-lapse seismic monitoring. However, the resistivity changes greatly before and after the displacement, and thus the time-lapse electromagnetic method has inherent advantages in the dynamic monitoring of oil and gas reservoirs. In light of this, we explore the capability of the grounded electric source TEM (transient electromagnetic) method for dynamic monitoring of remaining oil and gas reservoirs through three-dimensional (3D) numerical simulation. More importantly, to improve the numerical simulation accuracy, we use the difference scheme with variable step size from the second-order backward Eulerian method (BDF2) on the basis of the unstructured-grid vector finite element method. In this way, we realize the 3D forward modeling of grounded electric source TEM. In addition, the comparison between the analytical solution of a uniform half-space electromagnetic field and the numerical result of the 3D complex model verifies that the method meets the accuracy requirements of forward modeling. Utilizing this simulation method, we calculate and analyze the dynamic monitoring response characteristics of the relative anomalies of an oil and gas reservoir model under complex geological background. Subsequently, numerical modeling is performed for the actual geological data of Fuling shale gas, and the relative anomalies of electric field before and after fracturing are investigated. The results show that the grounded electric source TEM method has a good response for dynamic monitoring of oil and gas reservoirs and can meet the geological requirements of dynamic monitoring of complex 3D oil and gas reservoirs, which thus has broad application prospects.

Keywords：transient electromagnetic method(TEM) , time-lapse electromagnetic method, dynamic monitoring of oil and gas reservoir, vector finite element, difference scheme with variable step size

1. Key Laboratory of Exploration Technologies for Oil and Gas Resources, Ministry of Education, Yangtze University, Wuhan, Hubei 430100, China

2. Cooperative Innovation Center of Unconventional Oil and Gas, Wuhan, Hubei 430100, China

Studyonstep-by-stepregularizationinversionbasedonadaptiveunstructuredmesh.CHENGSan1，ZHANGZhiyong1，ZHOUFeng1,2，LIMan1，andZHAIBinjun1.OilGeophysicalProspecting,2022,57(2):467-477.

A step-by-step regularization inversion scheme based on adaptive mesh by taking two-dimensional magnetotelluric (MT) inversion as an example. In the initial stage of the inversion，coarse mesh is adopted for the inversion，and the ill-posedness of the inversion is decreased by reducing the number of inversion elements. During the iterative inversion process，mesh is adaptively refined according to mesh refinement strategies to get better imaging of abnormal bodies. The inversion results of the previous mesh are used as the reference model and the initial model in the inversion of the next mesh，so as to ensure the model improvements along the correct direction of the inversion，and then improve the inversion stability and inversion results. Four mesh refinement strategies were proposed，including model sensitivity，model variation，model gradient and “edge-angle” detection. The characteristics of the four mesh optimization schemes are analyzed by Hessian matrix eigenvalue distribution，and the adaptive inversion results of four mesh refinement schemes are compared. Finally，the practicability of the adaptive inversion algorithm is proved by the inversion of synthetic model and field data.

Keywords：adaptive inversion，magnetotelluric，two-dimensional inversion，unstructured mesh，eigenvalue

1.School of Geophysics and Measurement-Control Technology，East China University of Technology，Nanchang，Jiangxi 330013，China

2.Fundamental Science on Radioactive Geology and Exploration Technology Laboratory，East China University of Technology，Nanchang，Jiangxi 330013，China

StudyonfineGPRdetectiontechniqueoffan-deltasedimentarystructureinacomplexenvironment.LINGJianyu1,QIANRongyi1,LIUDongyi1,ZHANGJun1,WANGYuchen1,andZHANGShiqi1.OilGeophysicalProspecting,2022,57(2):478-486.

The coarse-grained sedimentary fans mainly composed of alluvial fans and fan deltas are large in scale and have diverse systems, good source-reservoir-cap rock configuration, and great exploration potential. In the past, the sedimentary structure and evolution laws of fan deltas were studied by methods including observation of outcrops, core analysis, well logging, and seismic exploration, but these methods faced problems of discontinuity as well as low efficiency and resolution in obtaining subsurface information. Ground-penetrating radar (GPR) can be used for rapid, high-resolution, and conti-nuous detection, which is helpful for fine dissection of shallow sedimentary characteristics of fan deltas. Therefore, this paper used GPR to detect the internal structure of the Xiligou Lake fan delta in Qinghai Province, and through field acquisition experiments and analysis of data characteristics and attributes, the influence of a complex environment on detection results was clarified. Then, the optimal field data acquisition scheme was put forward for the fine GPR detection of shallow sedimentary structure of the fan delta in a complex environment. Moreover, three key processing methods, i.e., distance normalization, migration, and static corrections, were proposed to solve the problems of inconsistent trace intervals, event crossing, and topographic relief. As a result, the scheme of high-resolution and fast detection technology for the internal structure of the fan delta is formed. The boundary positioning of channels and dams is realized in submeters, and the size information of channels and dams is provided quantitatively. The influence of floods on the structure and quality of fan delta reservoirs is clarified. The result provides the essential fine architecture combination laws and quantitative geological information for later studies of the modeling of ancient fan-delta reservoirs with a burial depth of several thousand meters.

Keywords：fine characterization of sedimentary structure, reservoir modeling, GPR, complex environment, fan delta, data acquisition and processing

1. School of Geophysics and Information Techno-logy, China University of Geosciences (Beijing), Beijing 100083, China

Reviewandprospectofresearchonlacustrinecarbonaterocks.LIUZhen1,2,ZHANGJunhua1,2,WANGJing1,2,YUZhengjun3,andSUChao-guang3.OilGeophysicalProspecting,2022,57(2):487-497.

Oil and gas exploration in lacustrine carbonate rocks has been paid increasing attention to. Nevertheless, related research methods and results are still in a preliminary stage and lack systematic review. In this paper, the main progress in geolo-gical, logging, and geophysical research on lacustrine carbonate rocks in recent years is extensively investigated and systematically summarized, with the focus placed on the Jiyang Depression as an example. Then, the characteristics of lacustrine and marine carbonate rocks are compared to assess the prospect of research techniques and methods for lacustrine carbonate rocks. The observations are as follows: ① Research on geological theories about lacustrine carbonate rocks is still in its infancy, and a unified and proven scheme of sedimentary facies division remains to be developed at present; the main controlling factors for lacustrine carbo-nate rocks are paleoclimate, paleostructure, paleo-water medium condition, paleogeomorphology, and paleosource; the reservoir space can be divided into primary pores, secondary pores, and fractures, and the influencing factors are sedimentary environment, diagenesis, and tectonics. ② Lacustrine carbonate rocks have the logging facies characteristics of finger shape, circular arc shape, tooth shape, and U shape. At present, sedimentary microfacies are mainly used to identify reservoirs and analyze fluid properties. ③ Seismic amplitude slices of lacustrine carbonate rocks often have typical beach core characteristics. The identification ability can be improved by frequency-division imaging and 90° phase shift. ④ Lacustrine carbonate rocks are different from marine ones in many aspects, such as development age, spatial distribution, sedimentary facies characteristics, reservoir types and characteristics, and source rocks. The former developed in the Mesozoic and Cenozoic and was greatly affected by paleoclimate, while the latter developed in the Jurassic, Permian, Triassic, Ordovician, and Cambrian and was mainly under the influence of tides. ⑤ Future prediction of lacustrine carbonate reservoirs should focus on faults and thin interbeds; sedimentary theories about lacustrine carbonate rocks are expected to undergo further development for a unified model of facies zone division to take shape; Deep learning methods based on big data analysis are an important future development direction.

Keywords：lacustrine carbonate rock, Jiyang Depression, sedimentary facies division, beach core, thin interbed, deep learning

1. School of Geosciences, China University of Petroleum (East China), Qingdao, Shandong 266580, China

2. Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao, Shandong 266580, China

3. Geophysical Research Institute, Shengli Oilfield Company, SINOPEC, Dongying, Shandong 257022, China