Geophysical Prospecting最新文献

{"title":"Automatic stack velocity picking using a semi-supervised ensemble learning method","authors":"Hongtao Wang,&nbsp;Jiangshe Zhang,&nbsp;Chunxia Zhang,&nbsp;Li Long,&nbsp;Weifeng Geng","doi":"10.1111/1365-2478.13492","DOIUrl":"10.1111/1365-2478.13492","url":null,"abstract":"<p>Picking stack velocity from seismic velocity spectra is a fundamental method in seismic stack velocity analysis. With the increase in the scale of seismic data acquisition, manual picking cannot achieve the required efficiency. Therefore, an automatic picking algorithm is urgently needed now. Despite some supervised deep learning–based picking approaches that have been proposed, they heavily rely on sufficient training samples and lack interpretability. In contrast, utilizing physical knowledge to develop semi-data-driven methods has the potential to efficiently solve this problem. Thus, we propose a semi-supervised ensemble learning method to reduce the reliance on manually labelled data and improve interpretability by incorporating the interval velocity constraint. Semi-supervised ensemble learning fuses the information of the estimated spectrum, nearby velocity spectra and few-shot manual picking to recognize the velocity picking. Test results of both the synthetic and field datasets indicate that semi-supervised ensemble learning achieves more reliable and precise picking than traditional clustering-based techniques and the currently popular convolutional neural network method.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"72 5","pages":"1816-1830"},"PeriodicalIF":2.6,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140156481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determination of the magnetization direction via correlation between reduced-to-the-pole magnetic anomalies and total gradient of the magnetic potential with vertical magnetization","authors":"Xiange Jian,&nbsp;Shuang Liu,&nbsp;Zuzhi Hu,&nbsp;Yunxiang Liu,&nbsp;Hongzhu Cai,&nbsp;Xiangyun Hu","doi":"10.1111/1365-2478.13499","DOIUrl":"10.1111/1365-2478.13499","url":null,"abstract":"<p>The total magnetization of an underground magnetic source is the vector sum of the induced magnetization and the natural remanent magnetization. The direction of the total magnetization serves as important a priori information in the inversion and processing of magnetic data. We demonstrated that the total gradient of the magnetic potential with vertical magnetization constitutes the envelope of the vertical component of the magnetic field for all directions of the Earth's field and source magnetization. The total gradient of the magnetic potential with vertical magnetization and the reduction-to-the-pole field simultaneously tend to achieve maximum symmetry near the correct total magnetization direction. As a result, the total magnetization direction can be estimated by computing the correlations between the reduction-to-the-pole and the total gradient of the magnetic potential with vertical magnetization. The proposed method yields accurate magnetization directions in synthetic model examples. The total gradient of the magnetic potential with vertical magnetization is less susceptible to data noise than transforms which are derived from the high-order magnetic field derivatives or tensors. The estimation results are slightly affected by changes in the source magnetization direction. In a field example in the Weilasito region (North China), the reduction-to-the-pole fields calculated using the estimated magnetization directions are well centred over the source. The proposed method obtained a more focused magnetization direction than that of a three-dimensional magnetization vector inversion. The total gradient of the magnetic potential with vertical magnetization therefore provides a novel and accurate approach to determine the total magnetization direction from the total field anomaly in a variety of situations.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"72 6","pages":"2377-2402"},"PeriodicalIF":2.6,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140107840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multidimensional Q-compensated reverse time migration using a high-efficient decoupled viscoacoustic wave equation","authors":"Zilong Ye,&nbsp;Jianping Huang,&nbsp;Xinru Mu,&nbsp;Qiang Mao","doi":"10.1111/1365-2478.13501","DOIUrl":"10.1111/1365-2478.13501","url":null,"abstract":"<p>Seismic waves propagating through attenuating media induce amplitude loss and phase dispersion. Neglecting the attenuation effects during seismic processing results in the imaging profiles with weakened energy, mispositioned interfaces and reduced resolution. To obtain high-quality imaging results, <i>Q</i>-compensated reverse time migration is developed. The kernel of the <i>Q</i>-compensated reverse time migration algorithm is a viscoacoustic wave equation with decoupled amplitude loss and phase dispersion terms. However, the majority of current decoupled viscoacoustic wave equations are solved using the computationally expensive pseudo-spectral method. To enhance computational efficiency, we initiate our approach from the dispersion relation of a single standard linear solid model. Subsequently, we derive a novel decoupled viscoacoustic wave equation by separating the amplitude loss and phase dispersion terms, previously coupled in the memory variable. The newly derived decoupled viscoacoustic wave equation can be efficiently solved using the finite-difference method. Then, we reverse the sign of the amplitude loss term of the newly derived viscoacoustic wave equation to implement high-efficient <i>Q</i>-compensated reverse time migration based on the finite-difference method. In addition, we design a regularization term to suppress the high-frequency noise for stabilizing the wavefield extrapolation. Forward modelling tests validate the decoupled amplitude loss and phase dispersion characteristics of the newly derived viscoacoustic wave equation. Numerical examples in both two-dimensional and three-dimensional confirm the effectiveness of the <i>Q</i>-compensated reverse time migration based on the finite-difference algorithm in mitigating the attenuation effects in subsurface media and providing high-quality imaging results.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"72 6","pages":"2109-2122"},"PeriodicalIF":2.6,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140125019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Building initial model for seismic inversion based on semi-supervised learning","authors":"Qianhao Sun,&nbsp;Zhaoyun Zong","doi":"10.1111/1365-2478.13491","DOIUrl":"10.1111/1365-2478.13491","url":null,"abstract":"<p>Seismic inversion is an important tool for reservoir characterization. The inversion results are significantly impacted by a reliable initial model. Conventional well interpolation methods are not able to meet the needs of seismic inversion for lateral heterogeneous reservoirs. Inspired by the sequence modelling network and seismic inversion in the Laplace–Fourier domain, we propose an initial model-building method using semi-supervised learning strategy. The proposed method considers spatial information to ensure the horizontal continuity of the initial model. Based on the fact that the low-frequency components of seismic signals in the Laplace–Fourier domain are easier to obtain, we use the forward model in the Laplace–Fourier domain to replace the time-domain forward model. The proposed workflow was validated using the Marmousi II model. Although the training was carried out on a small number of low-frequency impedance traces, the proposed workflow was able to build low-frequency model for the entire Marmousi II model with a correlation of 98%. Field data examples demonstrate the feasibility and effectiveness of the proposed method. For lateral heterogeneous reservoirs, the proposed method performs better than the well interpolation method. By utilizing the model obtained by the proposed method as the initial low-frequency model of the conventional inversion method, it is possible to estimate better inversion results. The results of different combinations of training sets demonstrate the stability of the proposed method. This method may still be a viable choice if there is lateral heterogeneity underground but not much well-logging label data.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"72 5","pages":"1800-1815"},"PeriodicalIF":2.6,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140044805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-geophysical methods for characterizing fractures in an open pit mine, western Bushveld Complex, South Africa","authors":"Moyagabo K. Rapetsoa,&nbsp;Sikelela Gomo,&nbsp;Musa S. D. Manzi,&nbsp;Ian James,&nbsp;Jureya Dildar,&nbsp;Mpofana Sihoyiya,&nbsp;Ndamulelo Mutshafa,&nbsp;Raymond J. Durrheim","doi":"10.1111/1365-2478.13489","DOIUrl":"10.1111/1365-2478.13489","url":null,"abstract":"<p>In the Bushveld Complex, South Africa, open pit mines are faced with a challenge of rock slope stability due to geological structures (fractures, faults and dykes) that compartmentalize the rock mass. Geophysical surveys (seismics, magnetics and electrical methods) were conducted in a 0.2 km² area at Tharisa mine, with the goal to delineate fractures that may be potential conduits for water migration into the pit. Special processing techniques were applied to the dataset to obtain good quality seismic, magnetic and resistivity models. The P-wave velocity models show distinct low velocities in the centre of the seismic profile, indicating the presence of weak zones associated with faulting or fracturing. Seismic reflection method was used to image the deeper discontinuities and mineralization contacts. Near surface reflections are observed throughout the profiles and are correlated with the contact between the chromitite and host rock. Ground magnetic surveys were conducted to delineate dykes and fractures. De-trending and de-culturing techniques were applied on the magnetic data for correcting regional and temporal variations. The low magnetic regions indicate the presence of fracture systems in the subsurface, whereas the high magnetic region is correlated with the dolerite dyke that crosscuts the pit. The electrical resistivity tomography exhibits linear low resistivity contrast zones that differentiate between the fractured and undisturbed hard rock at an estimated depth of 4–10 m. Resistivity shows discontinuities that suggests the presence of fracturing and dyke-host rock contacts. Correlation among magnetics, P-wave velocity models, resistivity section and seismic data is evident when overlaying the different datasets, implying that the low magnetic regions are highly weathered and prone to fracturing. The integration of geophysical data is encouraging, because it was able to image the depth to the bedrock, fractures within the host rock and dyke in a complex mining environment.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"72 5","pages":"1950-1970"},"PeriodicalIF":2.6,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1365-2478.13489","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140044807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization and analysis of attenuation anisotropy in viscoelastic vertical transverse isotropic media","authors":"Yijun Xi,&nbsp;Xingyao Yin","doi":"10.1111/1365-2478.13494","DOIUrl":"10.1111/1365-2478.13494","url":null,"abstract":"<p>Due to the intrinsic attenuation of the earth, the study of wave propagation characteristics, considering seismic attenuation plays an important role in high-precision reservoir prediction. Therefore, we investigate the propagation and reflection characteristics of seismic waves in viscoelastic vertical transverse isotropic media in the complex frequency domain. Specifically, we analyse the response characteristics of velocity, propagation vector and attenuation vector with respect to viscosity media with different attenuation intensities. Furthermore, based on the quasi-Zoeppritz equation, the variation of reflection coefficient amplitude with offset at different attenuation angles and different attenuation intensities is studied. We also compare the trends in the amplitude variation of reflection coefficients with offset in elastic isotropic, elastic anisotropic and viscoelastic anisotropic media. Due to the complexity of the exact reflection coefficient expression, we first propose the approximate expression of the attenuation–anisotropy parameters and then derive the approximate expression of the reflection coefficient. The numerical simulation results show that the approximate expression of the reflection coefficient is still accurate, even in media with strong anisotropy. Finally, the accuracy evaluations of the reflection coefficient formulas using four typical theory models demonstrate that the approximate reflection coefficient formulas are highly accurate in both weak and strong anisotropic media.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"72 5","pages":"1831-1851"},"PeriodicalIF":2.6,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140010270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stress-induced anisotropy in Gulf of Mexico sandstones and the prediction of in situ stress","authors":"Colin M. Sayers,&nbsp;W. Scott Leaney,&nbsp;Tom R. Bratton","doi":"10.1111/1365-2478.13497","DOIUrl":"10.1111/1365-2478.13497","url":null,"abstract":"<p>The strong sensitivity of velocity to stress observed in many sandstones originates from the response of stress-sensitive discontinuities such as grain contacts and microcracks to a change in effective stress. If the change in stress is anisotropic, then the change in elastic wave velocities will also be anisotropic. Characterization of stress-induced elastic anisotropy in sandstones may enable estimation of the in situ three dimensional stress tensor with important application in solving problems occurring during drilling, such as borehole instability, and during production, such as sanding and reservoir compaction. Other applications include designing hydraulic fracture stimulations and quantifying production-induced stresses which may lead to rock failure. Current methods for estimating stress anisotropy from acoustic anisotropy rely on third-order elasticity, which ignores rock microstructure and gives elastic moduli that vary linearly with strain. Elastic stiffnesses in sandstones vary non-linearly with stress. Using P- and S-wave velocities measured on Gulf of Mexico sandstones, this non-linearity is found to be consistent with a micromechanical model in which the discontinuities are represented by stress-dependent normal and shear compliances. Stress-induced anisotropy increases with increasing stress anisotropy at small stress but then decreases at larger stresses as the discontinuities close and their compliance decreases. When the ratio of normal-to-shear compliance of the discontinuities is unity, the stress-induced anisotropy is elliptical, but for values different from unity, the stress-induced anisotropy becomes anelliptic. Although vertical stress can be obtained by integrating the formation's bulk density from the surface to the depth of interest, and minimum horizontal stress can be estimated using leak-off tests or hydraulic fracture data, maximum horizontal stress is more difficult to estimate. Maximum horizontal stress is overpredicted based on third-order elasticity using measured shear moduli, with estimates of pore pressure, vertical stress and minimum horizontal stress as input. The non-linear response of grain contacts and microcracks to stress must be considered to improve such estimates.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"72 5","pages":"1852-1864"},"PeriodicalIF":2.6,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140017412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stationary-phase analysis of time-shift extended imaging in a constant-velocity model","authors":"W. A. Mulder","doi":"10.1111/1365-2478.13496","DOIUrl":"10.1111/1365-2478.13496","url":null,"abstract":"<p>To estimate the depth errors in a subsurface model obtained from the inversion of seismic data, the stationary-phase approximation in a two-dimensional constant-velocity model with a dipped reflector is applied to migration with a time-shift extension. This produces two asymptotic solutions: one is a straight line, and the other is a curve. If the velocity differs from the true one, a closed-form expression of the depth error follows from the depth and apparent dip of the reflector as well as the position of the amplitude peak at a non-zero time shift, where the two solutions meet and the extended migration image focuses. The results are compared to finite-frequency results from a finite-difference code. A two-dimensional synthetic example with a salt diapir illustrates how depth errors can be estimated in an inhomogeneous model after inverting the seismic data for the velocity model.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"72 5","pages":"1555-1563"},"PeriodicalIF":2.6,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1365-2478.13496","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139969712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A facies-constrained geostatistical seismic inversion method based on multi-scale sparse representation","authors":"Qin Su,&nbsp;Xingrong Xu,&nbsp;Ting Chen,&nbsp;Jingjing Zong,&nbsp;Hua Wang","doi":"10.1111/1365-2478.13476","DOIUrl":"10.1111/1365-2478.13476","url":null,"abstract":"<p>Geostatistical seismic inversion is an important method for establishing high-resolution reservoir parameter models. There is no accurate representation method for reservoir structural features, and prior information about structural features cannot be incorporated into geostatistical inversion. Based on the assumption of the sparsity of stratigraphic sedimentary features, the same type of structural feature is used to represent the sedimentary pattern of reservoirs within the same facies. Different sparse representation patterns are used to represent the differences in sedimentary patterns between facies. Although changes in depositional environment might result in the multi-scale characteristics of geological structures for varying sedimentary rhythms, this paper proposes a facies-constrained geostatistical inversion method based on multi-scale sparse representation to better accommodate such situation. Using the method of sparse representation combined with wavelet transform, the multi-scale sedimentary structural features of reservoirs are learned from well-logging data. Seismic facies and multi-scale features are used as prior information for geostatistical inversion. Further, the likelihood function is constructed using seismic data to obtain the posterior probability distribution of reservoir parameters. Finally, the accurate inversion result is obtained by using multi-scale sparse representation as a constraint in the posterior probability distribution of reservoir parameters. Compared with conventional geostatistical methods, this algorithm can better match the structural features of reservoir parameters with varying geological conditions. Field data tests have shown the effectiveness of this method in improving the accuracy and resolution of reservoir parameter structural features.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"72 5","pages":"1657-1671"},"PeriodicalIF":2.6,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139947007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-resolution reservoir prediction method based on data-driven and model-based approaches","authors":"Liu ZeYang,&nbsp;Song Wei,&nbsp;Chen XiaoHong,&nbsp;Li WenJin,&nbsp;Li Zhichao,&nbsp;Liu GuoChang","doi":"10.1111/1365-2478.13493","DOIUrl":"10.1111/1365-2478.13493","url":null,"abstract":"<p>The Jiyang depression in the southeastern part of the Bohai Bay Basin has a relatively large scale set of shale oil in the Paleogene Shahejie Formation, but the complex internal components lead to narrow frequency bands, low resolution and difficulty in reservoir information extraction. Impedance is important information for reservoir characterization, and how to predict high-resolution impedance using available information is particularly important. Deep learning, known for its effectiveness in addressing non-linear problems, has found extensive applications in various fields of oil and gas exploration. However, the challenges of overfitting and poor generalization persist due to the limited availability of training datasets. Besides, existing methods often use networks to solve a single problem in fact, deep learning can deal with a series of problems intelligently. In order to partially solve the above problems, an intelligent storage prediction network framework is proposed in this paper. Physical information is introduced to realize data-driven and model-based approaches, thus solving the problem of difficult construction of training datasets. The processing part accomplishes the high-resolution processing of seismic records, thus solving the problems of narrow bandwidth and low resolution. Initial model constraints are introduced so as to obtain more stable inversion results. Finally, the well data is compared and analysed to identify and predict the lithology and complete the intelligent prediction of unconventional reservoirs. The results are compared with the traditional model-driven inversion method, revealing that the approach presented in this paper exhibits higher resolution in predicting dolomite. This contributes to the establishment of a robust data foundation for reservoir evaluation.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"72 5","pages":"1971-1984"},"PeriodicalIF":2.6,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139947086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}