Geophysical Prospecting最新文献

{"title":"Random Noise Suppression of Prestack Seismic Data Using Non-Local Means via Patch Ordering in the Dual-Domain","authors":"Yawen Zhang,&nbsp;Shengchang Chen,&nbsp;Xinyue Gong,&nbsp;Ruxun Dou,&nbsp;Wenhao Luo","doi":"10.1111/1365-2478.70046","DOIUrl":"https://doi.org/10.1111/1365-2478.70046","url":null,"abstract":"<div>\u0000 \u0000 <p>Efficient noise removal in seismic data is crucial for accurately analysing subsurface structures because noise generated during field acquisition can considerably degrade data quality. Traditional single-domain denoising methods often struggle to preserve weak signals in prestack seismic data, potentially leading to the loss of critical information. To address this issue, we propose a novel dual-domain (DD) denoising approach called non-local means via patch ordering in DD (DD–PONLM). This method leverages the strengths of both time–space and transform domains to minimize the leakage of weak events. By employing non-local self-similarity and iterative processing in the time–space domain and discrete cosine transform domain, the proposed method effectively reduces noise while preserving weak signals. We validate the effectiveness of our method through extensive testing on both asynthetic and a field example. The results are compared with several traditional single-domain methods, demonstrating that DD–PONLM considerably improves the preservation of weak signals and reduces artefacts, such as the Gibbs phenomenon, associated with transform domain processing. This DD strategy not only enhances the signal-to-noise ratio but also preserves structural fidelity, making it a robust solution for seismic data denoising.</p>\u0000 </div>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"73 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144582284","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":"Bayesian Seismic–Petrophysical Inversion for Rock and Fluid Properties and Pore Aspect Ratio in Carbonate Reservoirs","authors":"Luiz E. S. Queiroz,&nbsp;Dario Grana","doi":"10.1111/1365-2478.70041","DOIUrl":"https://doi.org/10.1111/1365-2478.70041","url":null,"abstract":"<p>Seismic characterization of carbonate reservoirs is a challenging task due to the complex structure of carbonate rocks, where the seismic response is affected by multiple factors such as pore volume and shape as well as changes in mineralogy due to dolomitization and silicification. Hence, the prediction of petrophysical properties from seismic data is often uncertain. For this reason, we propose a statistical inversion method for the estimation of rock properties, where we combine Bayesian inverse theory with geophysical modelling. The geophysical model aims to compute the seismic response based on the rock and fluid properties and pore structure of the carbonate rocks, and it includes rock physics and the amplitude variation with offset models for the seismic response. The Bayesian formulation allows for the solution of the associated inverse problem by computing the posterior distribution of rock and fluid properties and pore structure of the rocks conditioned by the measured geophysical data. The novelty of the proposed method is that the rock physics model can be any petroelastic relation, without requiring any linearization. For the application to the carbonate reservoir, we adopt the self-consistent inclusion model with ellipsoidal pore shapes and Gassmann's equation for the fluid effect; however, the inversion can be applied to any rock physics model. The statistical model assumes that the prior probability distribution of the model variables is a Gaussian mixture model such that distinct petrophysical characteristics can be associated with geological or seismic facies. The result of the proposed inversion is the most likely reservoir model of rock and fluid and pore geometry parameters, for example, porosity, pore aspect ratio, and water saturation and the uncertainty of the model predictions. The method is demonstrated and validated on synthetic and real examples using well logs and two-dimensional seismic sections from a pre-salt dataset in Brazil.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"73 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1365-2478.70041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144589736","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":"Anisotropic Brittleness Characterization and Analysis of VTI Media","authors":"Qiyu Yang,&nbsp;Jingye Li,&nbsp;Jinming Cui,&nbsp;Yongping Wang,&nbsp;Lei Han,&nbsp;Yuning Zhang","doi":"10.1111/1365-2478.70049","DOIUrl":"https://doi.org/10.1111/1365-2478.70049","url":null,"abstract":"<div>\u0000 \u0000 <p>The brittleness index is a crucial parameter for evaluating the brittleness of subsurface reservoirs. Accurate brittleness determination optimizes fracture design and guides oil and gas extraction, especially in shale formations. Traditionally, the brittleness index assumes isotropy, which fails to capture the anisotropic nature of shale reservoirs and often leads to prediction errors. To mitigate this challenge, this study introduces a stiffness coefficient matrix specifically designed for anisotropic media and proposes a brittleness index equation tailored for transverse isotropic (VTI) media. Experimental results show that the proposed anisotropic brittleness index provides a more accurate assessment of shale reservoir brittleness than the conventional isotropic brittleness index. Ultimately, the anisotropic brittleness index is applied to field logging data, thereby validating the effectiveness of the method in distinguishing between reservoirs of high and low brittleness.</p>\u0000 </div>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"73 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581971","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":"Stochastic Joint Inversion of Seismic and Controlled-Source Electromagnetic Data","authors":"Pankaj K Mishra,&nbsp;Adrien Arnulf,&nbsp;Mrinal K Sen,&nbsp;Zeyu Zhao,&nbsp;Piyoosh Jaysaval","doi":"10.1111/1365-2478.70043","DOIUrl":"https://doi.org/10.1111/1365-2478.70043","url":null,"abstract":"<p>Stochastic inversion approaches provide a valuable framework for geophysical applications due to their ability to explore multiple plausible models rather than offering a single deterministic solution. In this paper, we introduce a probabilistic joint inversion framework combining the very fast simulated annealing optimization technique with generalized fuzzy c-means clustering for coupling of model parameters. Since very fast simulated annealing requires extensive computational resources to converge when dealing with a large number of inversion parameters, we employ sparse parameterization, where models are sampled at sparse nodes and interpolated back to the modelling grid for forward computations. By executing multiple independent inversion chains with varying initial models, our method effectively samples the model space, thereby providing insights into model variability. We demonstrate our joint inversion methodology through numerical experiments using synthetic seismic traveltime and controlled-source electromagnetic datasets derived from the SEAM Phase I model. The results illustrate that the presented approach offers a practical compromise between computational efficiency and the ability to approximate model uncertainties, making it suitable as an alternative for realistic larger-scale joint inversion purposes.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"73 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1365-2478.70043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144582191","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":"Numerical Modelling of Acoustic–Elastic Coupled Equation in Vertical Transversely Isotropic Media","authors":"Bo Zhang,&nbsp;Guochen Wu,&nbsp;Junzhen Shan,&nbsp;Qingyang Li,&nbsp;Zongfeng Jia","doi":"10.1111/1365-2478.70045","DOIUrl":"https://doi.org/10.1111/1365-2478.70045","url":null,"abstract":"<div>\u0000 \u0000 <p>Numerical simulations of fluid–solid coupled media are vital for marine seismic exploration. Anisotropy in real strata and the limitations of standard elastic wave equations in simulating pressure components in marine seismic data (e.g., towed streamer 1C and ocean-bottom 4C data) necessitate alternative approaches. We propose an acoustic–elastic coupled equation for vertical transverse isotropic (VTI) media overlying fluid layers, eliminating the need for explicit boundary handling. Numerical results indicate that the proposed method has slightly higher computational and storage costs compared to standard elastic wave equations. However, the synthetic seismograms preserve converted wave information, which is crucial for S-wave velocity inversion, and effectively simulate Scholte waves at fluid–solid boundaries in shallow marine environments. The equation is highly adaptable, accommodating various marine seismic acquisition methods and providing valuable insights into processing complex marine seismic data.</p>\u0000 </div>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"73 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144573418","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":"Joint Microseismic Event Detection and Location With a Detection Transformer","authors":"Yuanyuan Yang,&nbsp;Claire Birnie,&nbsp;Tariq Alkhalifah","doi":"10.1111/1365-2478.70040","DOIUrl":"https://doi.org/10.1111/1365-2478.70040","url":null,"abstract":"<div>\u0000 \u0000 <p>Microseismic event detection and location are two primary components in microseismic monitoring, which offer us invaluable insights into the subsurface during reservoir stimulation and evolution. Conventional approaches for event detection and location often suffer from manual intervention and/or heavy computation, while current machine learning assisted approaches typically address detection and location separately; such limitations hinder the potential for real-time microseismic monitoring. We propose an approach to unify event detection and source location into a single framework by adapting a convolutional neural network backbone and an encoder–decoder transformer with a set-based Hungarian loss, which is applied directly to recorded waveforms. The proposed network is trained on synthetic data simulating multiple microseismic events corresponding to random source locations in the area of suspected microseismic activities. A synthetic test on a two-dimensional profile of the SEG Advanced Modeling (SEAM) Time Lapse model illustrates the capability of the proposed method in detecting the events properly and locating them in the subsurface accurately; while, a field test using the Arkoma Basin data further proves its practicability, efficiency, and its potential in paving the way for real-time monitoring of microseismic events.</p></div>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"73 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144582167","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":"Algorithms for extraction of reliable density ratios from pre-stack seismic data—Part 2: Applications","authors":"Ivan Lehocki,&nbsp;Tapan Mukerji,&nbsp;Per Avseth,&nbsp;Erling Hugo Jensen","doi":"10.1111/1365-2478.70030","DOIUrl":"https://doi.org/10.1111/1365-2478.70030","url":null,"abstract":"<p>We have developed two inversion algorithms to calculate the density ratio across a reflecting interface using Zoeppritz's equation for P-to-P wave reflections. At any point on the interface, we can calculate the most likely density ratio value with a corresponding standard deviation from a distribution of estimated (density ratio) values. This makes it possible to plot uncertainty maps at any interface of interest. Both inversion algorithms are applied within the near–far angle range to ensure the reliability of density ratio estimates. Although the methods can theoretically handle a wider range of angles, ultra-far angles are avoided due to amplitude distortions that become more pronounced at large incidence angles. A natural consequence of this restriction is that the herein-presented empiricism-free algorithms can be used for all classes of amplitude variation with offset (AVO) responses. At the heart of the first inversion scheme is a solver of a 12th-degree polynomial equation. The roots of the equation are calculated at an arbitrary number of incident angles. The solution space gives rise to a distribution from which the most frequent value (representing the maximum of the distribution) is taken as the most likely value. The second scheme involves solving a 5th-degree polynomial equation for the square of the <i>V</i>_P/<i>V</i>_S ratio of layer 2 (in a two-layered earth model) also at an arbitrary number of incident angles. The most likely density ratio estimate and the associated uncertainty are obtained as a byproduct of the calculation. We test both methods on a seismic dataset from the Barents Sea. The two methods yield very similar density ratio maps on the studied interface. Moreover, except for one well, they give a good match with estimated values from well-log data. This study is the second part of a two-part research. While Part I focuses on the theoretical foundations and synthetic validation of the inversion methods, this paper applies them to real seismic data to evaluate their practical performance.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"73 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144582407","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":"Algorithms for extraction of reliable density ratios from pre-stack seismic data—Part 1: Theory","authors":"Ivan Lehocki,&nbsp;Tapan Mukerji,&nbsp;Per Avseth,&nbsp;Erling Hugo Jensen","doi":"10.1111/1365-2478.70029","DOIUrl":"https://doi.org/10.1111/1365-2478.70029","url":null,"abstract":"<p>We have developed two inversion schemes for probabilistic calculation of density ratio across a reflecting interface from P-to-P wave reflectivity by algebraically inverting Zoeppritz's equation. The density ratio is an attribute that can be directly linked to hydrocarbon saturation. The probabilistic approach helps to model uncertainties in the calculated parameter. The methods are free of empiricism. Contrary to conventional wisdom, we show that ultra-far amplitude variation with offset (AVO) data are not required for the inversion of the density ratio parameter. As a matter of fact, with our schemes, it is advisable to restrict the inversion to near-far angle ranges to minimize the impact of the amplitude-distorting phenomena that (strongly) invalidate the assumptions woven into the derivation of the P-to-P Zoeppritz equation. Moreover, we demonstrate that this equation is suitable for density ratio inversion. The first inversion scheme to predict the density ratio involves repeatedly solving a 12th-degree polynomial equation across various incident angles. The most frequent value in the distribution of solutions serves as the best estimate. The second scheme solves a 5th-degree polynomial equation for the squared <i>V</i>_P/<i>V</i>_S ratio of layer 2 (in a two-layered earth model), also at an arbitrary number of incident angles. The range of the angles used in the inversion can, in principle, be freely selected. The most likely density ratio estimate is obtained as a byproduct of the calculation. We tested the methods on a synthetic example. Both schemes predict the density ratio within one standard deviation of the actual value from near-far angle seismic reflection data. Moreover, the two inversion schemes were compared, showing that <i>Loris</i>, which requires repetitive solving of 12th-degree polynomial equations, is computationally more expensive than <i>Lemur</i>, which solves a 5th-degree polynomial equation. Despite both methods achieving accurate density ratio estimates, <i>Lemur</i>’s computational efficiency makes it the preferred choice for large datasets. This paper is the first part of a two-part study on density ratio inversion methods. Here, we focus on the theoretical foundations of the <i>Loris</i> and <i>Lemur</i> inversion approaches and validate them through synthetic tests. In Part 2, we extend this work by applying the methods to real seismic data and evaluating their performance in a practical exploration setting.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"73 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144582408","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":"Multiple Reflections on Huygens' Principle","authors":"Kees Wapenaar","doi":"10.1111/1365-2478.70038","DOIUrl":"https://doi.org/10.1111/1365-2478.70038","url":null,"abstract":"<p>According to Huygens' principle, all points on a wave front act as secondary sources emitting spherical waves and the envelope of these spherical waves forms a new wave front. In the mathematical formulation of Huygens' principle, the waves emitted by the secondary sources are represented by Green's functions. In many present-day applications of Huygens' principle, these Green's functions are replaced by their time-reversed versions, thus forming a basis for backpropagation, imaging, inversion, seismic interferometry, etc. However, when the input wave field is available only on a single open boundary, this approach has its limitations. In particular, it does not properly account for multiply reflected waves. This is remedied by a modified form of Huygens' principle, in which the Green's functions are replaced by focusing functions. The modified Huygens' principle forms a basis for imaging, inverse scattering, monitoring of induced sources, etc., thereby properly taking multiply reflected waves into account.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"73 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1365-2478.70038","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144598728","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":"S-Wave Velocity Model of Texas Based On Joint Inversion of Interferometry and P-Wave Receiver Functions","authors":"Galina Lyubomirova Simeonova,&nbsp;Leo Eisner,&nbsp;Umair bin Waheed,&nbsp;Alexandros Savvaidis,&nbsp;Sherif Hanafy","doi":"10.1111/1365-2478.70035","DOIUrl":"https://doi.org/10.1111/1365-2478.70035","url":null,"abstract":"<div>\u0000 \u0000 <p>Velocity models are essential for accurately locating the rapidly increasing seismicity in Texas. The region's limited monitoring infrastructure and extensive sedimentary basins underscore the need for developing both P- and S-wave models, especially for precise depth estimation of seismic events. This study utilizes seismic interferometry and surface wave inversion techniques, along with receiver functions, to construct a three-dimensional velocity model for Western, Central and Southern Texas. Our results indicate that the integration of receiver functions significantly improves the stability of the surface wave inversion process. The resulting inverted model aligns well with known geological structures, revealing lower S-wave velocities in sedimentary basins and higher velocities in areas with bedrock exposure. Notably, the velocity contrasts between the sedimentary basins and bedrock can reach up to 30% at equivalent depths. Furthermore, the S-wave velocities derived from our model are considerably lower than those reported in previous research, suggesting that the use of this revised S-wave model may require a reevaluation of the depths at which seismic events are located.</p>\u0000 </div>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"73 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144582390","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}