Geochemical parameters, e.g. maturity, and total organic carbon (TOC) content, play a crucial role in the prediction of sweet spots and the exploration of oil and gas in organic-rich shales. Thermal maturity significantly affects the conversion of solid organic matter (OM) into hydrocarbons and the evolution of microstructures, thereby altering the overall elastic properties of shales. To clarify how the maturity affects shale property, we propose a novel Rock Physics Model (RPM) of organic-rich shale, in which we consider the continuous process of thermal maturity.#xD;Firstly, we present how to estimate maturity level, TOC content, and organic porosity using logging data. Secondly, different from only considering the discrete-stage maturity, we establish a novel RPM, in which a continuous kerogen maturation process serves as a key control condition. Furthermore, we propose how to calibrate the volumetric proportion of each porosity type as a function of maturation. Finally, we apply the RPM to investigate how sweet spot parameters (thermal maturity, TOC content, and brittle mineral content), overpressure and diagenesis affect the overall elastic properties and anisotropy of shale. Results demonstrate that using the proposed RPM we may predict acoustic velocity of shale formations reliably, and kerogen evolution has a noticeable impact on the elastic properties of shale rocks, particularly during the wet gas window stage of mid-to-high maturation. We conclude that thermal maturity emerges as a crucial sweet spot parameter in the case of exploration of oil and gas in organic-rich shales.
{"title":"A novel rock physics model of organic-rich shale considering maturation influence","authors":"Rui Yang, Huaizhen Chen","doi":"10.1190/geo2023-0612.1","DOIUrl":"https://doi.org/10.1190/geo2023-0612.1","url":null,"abstract":"Geochemical parameters, e.g. maturity, and total organic carbon (TOC) content, play a crucial role in the prediction of sweet spots and the exploration of oil and gas in organic-rich shales. Thermal maturity significantly affects the conversion of solid organic matter (OM) into hydrocarbons and the evolution of microstructures, thereby altering the overall elastic properties of shales. To clarify how the maturity affects shale property, we propose a novel Rock Physics Model (RPM) of organic-rich shale, in which we consider the continuous process of thermal maturity.#xD;Firstly, we present how to estimate maturity level, TOC content, and organic porosity using logging data. Secondly, different from only considering the discrete-stage maturity, we establish a novel RPM, in which a continuous kerogen maturation process serves as a key control condition. Furthermore, we propose how to calibrate the volumetric proportion of each porosity type as a function of maturation. Finally, we apply the RPM to investigate how sweet spot parameters (thermal maturity, TOC content, and brittle mineral content), overpressure and diagenesis affect the overall elastic properties and anisotropy of shale. Results demonstrate that using the proposed RPM we may predict acoustic velocity of shale formations reliably, and kerogen evolution has a noticeable impact on the elastic properties of shale rocks, particularly during the wet gas window stage of mid-to-high maturation. We conclude that thermal maturity emerges as a crucial sweet spot parameter in the case of exploration of oil and gas in organic-rich shales.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140655048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The propagation direction of the wavefield is particularly important for migration imaging in the reverse-time migration (RTM) of elastic waves in TI media. However, due to the problem of computational instability of the Poynting vector, the wave field propagation direction estimated based on the Poynting vector method has errors and cannot accurately indicate the real propagation direction of the elastic wavefield. To solve this problem, a method for calculating the optical flow vector of elastic waves in TI media is proposed to obtain the propagation direction. The optical flow vector of elastic waves in TI media is determined by applying the spatial and temporal derivatives of the wavefield at each time step, under the assumption that the wavefields are almost the same at subsequent time steps and are smooth in the spatial direction. As the additional smoothing item is added and the multiple iterative algorithm is introduced in calculating the optical flow vector, the direction is calculated more accurately than the Poynting vector. Based on the optical flow vectors, we can separate the source-wavefield and receiver-wavefield into four directions: up-going, down-going, left-going and right-going wavefields, respectively, and finally perform elastic reverse-time migration (ERTM) imaging based on the optical flow vector traveling-wave separation. We utilize a layered model and the BP model to test our method. The testing results demonstrate that the optical flow vector can overcome the Poynting vector limitations and get more accurate and reliable information regarding the direction of elastic wave propagation in TI media, as well as precisely separate the wavefields. The separated wavefields for migration effectively improve the quality of the ERTM.
波场的传播方向对于 TI 介质中弹性波的反向时间迁移（RTM）中的迁移成像尤为重要。然而，由于 Poynting 向量的计算不稳定性问题，基于 Poynting 向量方法估算的波场传播方向存在误差，无法准确指示弹性波场的真实传播方向。为解决这一问题，提出了一种计算 TI 介质中弹性波光流矢量的方法，以获得传播方向。TI 介质中弹性波的光流矢量是在假定后续时间步的波场几乎相同且在空间方向上平滑的前提下，通过应用每个时间步的波场的空间和时间导数确定的。由于在计算光流矢量时增加了额外的平滑项并引入了多重迭代算法，因此方向的计算比波因廷矢量更精确。根据光流矢量，我们可以将源波场和接收波场分别分离为四个方向：上行波场、下行波场、左行波场和右行波场，最后根据光流矢量行波分离进行弹性反向时间迁移（ERTM）成像。我们利用分层模型和 BP 模型来测试我们的方法。测试结果表明，光流矢量可以克服 Poynting 向量的限制，获得更准确可靠的 TI 介质中弹性波传播方向的信息，并精确分离波场。用于迁移的分离波场可有效提高 ERTM 的质量。
{"title":"Optical flow vector of elastic waves in TI media","authors":"Huixing Zhang, Yancang Feng, Bing-Shout He","doi":"10.1190/geo2023-0231.1","DOIUrl":"https://doi.org/10.1190/geo2023-0231.1","url":null,"abstract":"The propagation direction of the wavefield is particularly important for migration imaging in the reverse-time migration (RTM) of elastic waves in TI media. However, due to the problem of computational instability of the Poynting vector, the wave field propagation direction estimated based on the Poynting vector method has errors and cannot accurately indicate the real propagation direction of the elastic wavefield. To solve this problem, a method for calculating the optical flow vector of elastic waves in TI media is proposed to obtain the propagation direction. The optical flow vector of elastic waves in TI media is determined by applying the spatial and temporal derivatives of the wavefield at each time step, under the assumption that the wavefields are almost the same at subsequent time steps and are smooth in the spatial direction. As the additional smoothing item is added and the multiple iterative algorithm is introduced in calculating the optical flow vector, the direction is calculated more accurately than the Poynting vector. Based on the optical flow vectors, we can separate the source-wavefield and receiver-wavefield into four directions: up-going, down-going, left-going and right-going wavefields, respectively, and finally perform elastic reverse-time migration (ERTM) imaging based on the optical flow vector traveling-wave separation. We utilize a layered model and the BP model to test our method. The testing results demonstrate that the optical flow vector can overcome the Poynting vector limitations and get more accurate and reliable information regarding the direction of elastic wave propagation in TI media, as well as precisely separate the wavefields. The separated wavefields for migration effectively improve the quality of the ERTM.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140668843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In near-surface geophysics, ground-penetrating radar (GPR) surveys are routinely employed in a variety of applications including those from archaeology, civil engineering, hydrology, and soil science. Thanks to recent technical developments in GPR instrumentation and antenna design, 3D surveys comprising several 100.000 traces can be performed daily. Especially in complex environments such as sedimentary systems, analyzing and interpreting the resulting GPR volumes is a time-consuming and laborious task that is still largely performed manually. In the last decades, several data attributes have been proposed to guide and improve such tasks and assure a higher degree of reproducibility in the resulting interpretations. Many of these attributes have been developed in image processing or computer vision and are routinely used, for example, in reflection seismic data interpretation. Especially in sedimentary systems, variations in the subsurface are accompanied by variations of GPR reflections in terms of amplitudes, continuity, and geometry in view of dip angle and direction. A promising tool to analyze such structural features is known as the gradient structure tensor (GST). Up to today, the application of the GST approach is limited to a few 2D GPR examples. Thus, we take up the basic idea of GST analysis and introduce and evaluate the corresponding attributes to analyze 3D GPR data. We apply the proposed GST approach to one synthetic and two field data sets imaging diverse sedimentary structures. Our results demonstrate that the proposed set of GST-based attributes can be efficiently computed in 3D and that these attributes represent versatile measures to address different typical interpretation tasks and, thus, help for an efficient, reproducible, and more objective interpretation of 3D GPR data.
{"title":"3D ground-penetrating radar data analysis and interpretation using attributes based on the gradient structure tensor","authors":"P. Koyan, J. Tronicke","doi":"10.1190/geo2023-0670.1","DOIUrl":"https://doi.org/10.1190/geo2023-0670.1","url":null,"abstract":"In near-surface geophysics, ground-penetrating radar (GPR) surveys are routinely employed in a variety of applications including those from archaeology, civil engineering, hydrology, and soil science. Thanks to recent technical developments in GPR instrumentation and antenna design, 3D surveys comprising several 100.000 traces can be performed daily. Especially in complex environments such as sedimentary systems, analyzing and interpreting the resulting GPR volumes is a time-consuming and laborious task that is still largely performed manually. In the last decades, several data attributes have been proposed to guide and improve such tasks and assure a higher degree of reproducibility in the resulting interpretations. Many of these attributes have been developed in image processing or computer vision and are routinely used, for example, in reflection seismic data interpretation. Especially in sedimentary systems, variations in the subsurface are accompanied by variations of GPR reflections in terms of amplitudes, continuity, and geometry in view of dip angle and direction. A promising tool to analyze such structural features is known as the gradient structure tensor (GST). Up to today, the application of the GST approach is limited to a few 2D GPR examples. Thus, we take up the basic idea of GST analysis and introduce and evaluate the corresponding attributes to analyze 3D GPR data. We apply the proposed GST approach to one synthetic and two field data sets imaging diverse sedimentary structures. Our results demonstrate that the proposed set of GST-based attributes can be efficiently computed in 3D and that these attributes represent versatile measures to address different typical interpretation tasks and, thus, help for an efficient, reproducible, and more objective interpretation of 3D GPR data.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140670277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We investigate an emerging method called surface geometry inversion (SGI) for the inversion of transient electromagnetic (TEM) data. Conventional minimum-structure inversion methods parameterize the Earth model with many mesh cells within which the physical properties are constant and construct a physical property model that is usually smoothly varying as well as fitting the observations. With these smooth models, it is difficult to extract the interface between different geological units, and it can be especially difficult to target drill holes for thin, plate-like targets which are frequently encountered in mineral exploration. Our SGI parameterizes the model in terms of the coordinates of the nodes (vertices) used to connect together the surfaces that define the geological interfaces. The algorithm then inverts for the locations of these nodes, which directly provides geometric information about the target. This can be more useful than a fuzzy image of conductivity, especially for an exploration project. A genetic algorithm (GA) is used to solve the non-linear over-determined optimization problem. We use a finite-element solver to solve the TEM forward modeling problem of each candidate model in the GA population. Because forward modeling is independent for each model, we implement a hybrid MPI + OpenMP parallel method to improve computational efficiency. We investigate a new parameterization method specifically designed for thin, plate-like structures, that is more efficient and can effectively avoid self-intersection. We first illustrate the effectiveness of our SGI algorithm on a synthetic block model before testing the new parameterization method on a synthetic thin plate model. Finally, we apply our SGI to a real dataset collected for the exploration of thin graphitic faults. The constructed model from our SGI corresponds well with the drilling data.
我们研究了一种用于瞬态电磁（TEM）数据反演的新兴方法--表面几何反演（SGI）。传统的最小结构反演方法用许多网格单元对地球模型进行参数化，网格单元内的物理特性是恒定的，并构建一个通常平滑变化的物理特性模型，同时拟合观测结果。利用这些平滑模型，很难提取不同地质单元之间的界面，尤其是在矿产勘探中经常遇到的薄板状目标的钻孔定位。我们的 SGI 根据节点（顶点）的坐标对模型进行参数化，用于将定义地质界面的表面连接在一起。然后，算法反演这些节点的位置，从而直接提供目标的几何信息。这比电导率的模糊图像更有用，尤其是对勘探项目而言。我们使用遗传算法（GA）来解决非线性过确定优化问题。我们使用有限元求解器来解决 GA 群体中每个候选模型的 TEM 前向建模问题。由于每个模型的前向建模都是独立的，因此我们采用了 MPI + OpenMP 混合并行方法来提高计算效率。我们研究了一种专为薄板状结构设计的新参数化方法，这种方法效率更高，能有效避免自交。我们首先在合成块模型上说明了 SGI 算法的有效性，然后在合成薄板模型上测试了新的参数化方法。最后，我们将 SGI 应用于为探索薄石墨断层而收集的真实数据集。我们的 SGI 所构建的模型与钻探数据非常吻合。
{"title":"Surface geometry inversion of transient electromagnetic data","authors":"Xushan Lu, Colin G Farquharson, Peter Lelieévre","doi":"10.1190/geo2023-0566.1","DOIUrl":"https://doi.org/10.1190/geo2023-0566.1","url":null,"abstract":"We investigate an emerging method called surface geometry inversion (SGI) for the inversion of transient electromagnetic (TEM) data. Conventional minimum-structure inversion methods parameterize the Earth model with many mesh cells within which the physical properties are constant and construct a physical property model that is usually smoothly varying as well as fitting the observations. With these smooth models, it is difficult to extract the interface between different geological units, and it can be especially difficult to target drill holes for thin, plate-like targets which are frequently encountered in mineral exploration. Our SGI parameterizes the model in terms of the coordinates of the nodes (vertices) used to connect together the surfaces that define the geological interfaces. The algorithm then inverts for the locations of these nodes, which directly provides geometric information about the target. This can be more useful than a fuzzy image of conductivity, especially for an exploration project. A genetic algorithm (GA) is used to solve the non-linear over-determined optimization problem. We use a finite-element solver to solve the TEM forward modeling problem of each candidate model in the GA population. Because forward modeling is independent for each model, we implement a hybrid MPI + OpenMP parallel method to improve computational efficiency. We investigate a new parameterization method specifically designed for thin, plate-like structures, that is more efficient and can effectively avoid self-intersection. We first illustrate the effectiveness of our SGI algorithm on a synthetic block model before testing the new parameterization method on a synthetic thin plate model. Finally, we apply our SGI to a real dataset collected for the exploration of thin graphitic faults. The constructed model from our SGI corresponds well with the drilling data.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140669625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cross-well electromagnetic (EM) logging has useful implications in oil, gas, and water monitoring, as well as carbon sequestration estimation. Difficulties in the efficient propagation of EM waves through a steel casing inhibit cross-well EM logging at distances greater than 300 m. This study investigates whether high-power transmission and high-efficiency transmitting antennas can resolve the challenges of long-distance cross-well EM logging through steel casings. Theoretical analysis shows that the emission moment should be at least 12 000 A·m2. By calculating the equivalent relative permeability and selecting appropriate coil materials and magnetic cores, the maximum emission magnetic moment can realize a high-power transmission. Based on series and parallel resonant circuits and the AC/DC cable core multiplexing power supply method, the effective transmission bandwidth is broadened and transmission efficiency is increased three-fold. The emission unit is fabricated and tested with a single, fiberglass, and double casing. We observed that the cross-well EM technology performs better for nonmetal casing wells than for metal casing wells. The amplitude and phase curves between two fiberglass casing wells in the range of 425 m are quite smooth. However, the receiving signals in the double-layer steel casing drop to only a few tenths of the value in the fiberglass casing wells, highlighting the difficulty of long-distance EM-wave transmission when using steel casings. Thus, studies on EM transmission through four or more layers of steel casings should be conducted in the future.
{"title":"Research on high-power and high-efficiency emission of cross-well electromagnetic logging","authors":"Yongsheng Chao, Yongli Ji, Defu Zang, Zhiqiang Li, Huaxiong Wang, Yanmin Ren","doi":"10.1190/geo2023-0260.1","DOIUrl":"https://doi.org/10.1190/geo2023-0260.1","url":null,"abstract":"Cross-well electromagnetic (EM) logging has useful implications in oil, gas, and water monitoring, as well as carbon sequestration estimation. Difficulties in the efficient propagation of EM waves through a steel casing inhibit cross-well EM logging at distances greater than 300 m. This study investigates whether high-power transmission and high-efficiency transmitting antennas can resolve the challenges of long-distance cross-well EM logging through steel casings. Theoretical analysis shows that the emission moment should be at least 12 000 A·m2. By calculating the equivalent relative permeability and selecting appropriate coil materials and magnetic cores, the maximum emission magnetic moment can realize a high-power transmission. Based on series and parallel resonant circuits and the AC/DC cable core multiplexing power supply method, the effective transmission bandwidth is broadened and transmission efficiency is increased three-fold. The emission unit is fabricated and tested with a single, fiberglass, and double casing. We observed that the cross-well EM technology performs better for nonmetal casing wells than for metal casing wells. The amplitude and phase curves between two fiberglass casing wells in the range of 425 m are quite smooth. However, the receiving signals in the double-layer steel casing drop to only a few tenths of the value in the fiberglass casing wells, highlighting the difficulty of long-distance EM-wave transmission when using steel casings. Thus, studies on EM transmission through four or more layers of steel casings should be conducted in the future.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140676501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jingshou Liu, Yuanhong Lu, Yang Luo, Haimeng Yang, Lin Lu
Hydraulic fracturing and horizontal well drilling are the key technologies for increasing the production of continental tight sandstone reservoirs. Taking the typical fractured tight sandstone in the Yuan-287 block of the Ordos Basin as an example, a reservoir geological model was established based on the stratigraphic correlation of 206 wells. The model and 3D paleostress field were combined to predict fracture parameters such as density and strike. By using reservoir breakdown pressure (RBP) monitoring data combined with reservoir physical and mechanical parameters, tectonic fracture characteristics, and in situ stress parameters, a quantitative evaluation model of RBP, which predicts the 3D distribution of RBP, was established via the stepwise regression method, and the factors controlling the RBP were analyzed. The rock P-wave velocity, horizontal minimum principal stress and fracture density were found to be three key parameters that control the breakdown pressure of this tight sandstone reservoir. By comparing the fracture opening pressure (FOP) of subsurface tectonic fractures with the RBP, a new method for predicting the optimal water injection pressure (OWIP) of this reservoir was proposed. This work provides a valuable evaluation model for accelerating the efficient development of continental tight sandstone reservoirs.
水力压裂和水平井钻探是提高大陆致密砂岩储层产量的关键技术。以鄂尔多斯盆地元-287区块典型的致密砂岩裂缝为例，基于206口井的地层关联建立了储层地质模型。该模型与三维古应力场相结合，预测了密度和走向等裂缝参数。利用储层破裂压力（RBP）监测数据，结合储层物理力学参数、构造裂缝特征和原位应力参数，通过逐步回归法建立了RBP定量评价模型，预测了RBP的三维分布，分析了RBP的控制因素。研究发现，岩石 P 波速度、水平最小主应力和裂缝密度是控制该致密砂岩储层破裂压力的三个关键参数。通过比较地下构造裂缝的裂缝张开压力（FOP）与 RBP，提出了预测该储层最佳注水压力（OWIP）的新方法。这项工作为加速高效开发大陆致密砂岩储层提供了一个有价值的评估模型。
{"title":"Method for predicting the injection pressure for horizontal wells in fractured tight sandstone reservoirs","authors":"Jingshou Liu, Yuanhong Lu, Yang Luo, Haimeng Yang, Lin Lu","doi":"10.1190/geo2023-0510.1","DOIUrl":"https://doi.org/10.1190/geo2023-0510.1","url":null,"abstract":"Hydraulic fracturing and horizontal well drilling are the key technologies for increasing the production of continental tight sandstone reservoirs. Taking the typical fractured tight sandstone in the Yuan-287 block of the Ordos Basin as an example, a reservoir geological model was established based on the stratigraphic correlation of 206 wells. The model and 3D paleostress field were combined to predict fracture parameters such as density and strike. By using reservoir breakdown pressure (RBP) monitoring data combined with reservoir physical and mechanical parameters, tectonic fracture characteristics, and in situ stress parameters, a quantitative evaluation model of RBP, which predicts the 3D distribution of RBP, was established via the stepwise regression method, and the factors controlling the RBP were analyzed. The rock P-wave velocity, horizontal minimum principal stress and fracture density were found to be three key parameters that control the breakdown pressure of this tight sandstone reservoir. By comparing the fracture opening pressure (FOP) of subsurface tectonic fractures with the RBP, a new method for predicting the optimal water injection pressure (OWIP) of this reservoir was proposed. This work provides a valuable evaluation model for accelerating the efficient development of continental tight sandstone reservoirs.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140673021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kittinat Taweesintananon, R. A. Rørstadbotnen, Martin Landrø, Ståle E. Johansen, B. Arntsen, Matthias Forwick, Alfred Hanssen
Shear-wave (S-wave) resonances are typically observed when the surficial marine sediments over a rock substrate have relatively low S-wave velocities. We observe these phenomena using ocean-bottom fiber-optic distributed acoustic sensing (DAS) in two subsea fiber-optic telecommunication cables in Svalbard, Norway. Strong seismic energy from sufficiently large earthquakes is required to trigger and enhance the multiple order modes of S-wave resonances. Here, we use the interpreted S-wave resonance frequencies of the first two modes to determine the thickness and the S-wave velocity of the near-surface low-velocity layer (LVL) beneath the seafloor. Additionally, we use existing active P-wave seismic reflection data to determine the LVL thickness and to help build a more accurate S-wave velocity model from the S-wave resonance frequencies. The estimated S-wave velocity varies laterally within the LVL formation. Here, we find that the sediments or deposits with high S-wave velocity presented in the estimated LVL model agree with the distribution of some glacigenic sediments and landforms deposited in the survey area. Therefore, S-wave resonances measured by ocean-bottom DAS can be used to characterize the corresponding near-surface LVLs.
当岩石基底上的表层海洋沉积物具有相对较低的 S 波速度时，通常会观测到剪切波（S 波）共振。我们利用挪威斯瓦尔巴群岛两条海底光纤通信电缆中的海底光纤分布式声学传感（DAS）观测到了这些现象。触发和增强 S 波共振的多阶模式需要来自足够大的地震的强大地震能量。在此，我们利用解释的前两种模式的 S 波共振频率来确定海底下近表面低速层 (LVL) 的厚度和 S 波速度。此外，我们还利用现有的主动 P 波地震反射数据来确定 LVL 的厚度，并帮助根据 S 波共振频率建立更精确的 S 波速度模型。估计的 S 波速度在 LVL 层内横向变化。在这里，我们发现估算的 LVL 模型中出现的 S 波速度较高的沉积物或沉积层与勘测区沉积的一些冰原沉积物和地貌的分布一致。因此，可以利用海底 DAS 测量的 S 波共振来描述相应的近地表 LVL。
{"title":"Near-surface characterization using shear-wave resonances: A case study from offshore Svalbard, Norway","authors":"Kittinat Taweesintananon, R. A. Rørstadbotnen, Martin Landrø, Ståle E. Johansen, B. Arntsen, Matthias Forwick, Alfred Hanssen","doi":"10.1190/geo2023-0530.1","DOIUrl":"https://doi.org/10.1190/geo2023-0530.1","url":null,"abstract":"Shear-wave (S-wave) resonances are typically observed when the surficial marine sediments over a rock substrate have relatively low S-wave velocities. We observe these phenomena using ocean-bottom fiber-optic distributed acoustic sensing (DAS) in two subsea fiber-optic telecommunication cables in Svalbard, Norway. Strong seismic energy from sufficiently large earthquakes is required to trigger and enhance the multiple order modes of S-wave resonances. Here, we use the interpreted S-wave resonance frequencies of the first two modes to determine the thickness and the S-wave velocity of the near-surface low-velocity layer (LVL) beneath the seafloor. Additionally, we use existing active P-wave seismic reflection data to determine the LVL thickness and to help build a more accurate S-wave velocity model from the S-wave resonance frequencies. The estimated S-wave velocity varies laterally within the LVL formation. Here, we find that the sediments or deposits with high S-wave velocity presented in the estimated LVL model agree with the distribution of some glacigenic sediments and landforms deposited in the survey area. Therefore, S-wave resonances measured by ocean-bottom DAS can be used to characterize the corresponding near-surface LVLs.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140676697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The building of a subsurface and (anisotropic) velocity model from a single gather of reflection traveltime (kinematic) data is inherently ambiguous since the processing of such data can only determine a horizontal slowness component, not a vertical one. Based thereon I derive a simple algorithm that generates an infinite series of combinations of subsurface - velocity models, all of which will show nearly the same seismic kinematic response, as further demonstrated by simulating wave propagation through a model with different interface dips. This algorithm assumes, firstly, all interface dips remain constant over the distance considered and, secondly, an approximation of the elasticity model – that is, linearization of a phase velocity – valid for weak anisotropy can be used. Furthermore, when applied at the classic, and analytically solvable, case of traveltime analysis for a stack of flat layers with weak transverse isotropy, the algorithm explains theoretically the combination of anisotropy parameters that govern the non-hyperbolic term of a traveltime series: the established [Formula: see text] and its new counterpart [Formula: see text] for a [Formula: see text] - and [Formula: see text] -wave, respectively.
{"title":"Weakly-Anelliptical Traveltime Analysis: Ambiguity between Subsurface and Elasticity","authors":"Björn E. Rommel","doi":"10.1190/geo2023-0274.1","DOIUrl":"https://doi.org/10.1190/geo2023-0274.1","url":null,"abstract":"The building of a subsurface and (anisotropic) velocity model from a single gather of reflection traveltime (kinematic) data is inherently ambiguous since the processing of such data can only determine a horizontal slowness component, not a vertical one. Based thereon I derive a simple algorithm that generates an infinite series of combinations of subsurface - velocity models, all of which will show nearly the same seismic kinematic response, as further demonstrated by simulating wave propagation through a model with different interface dips. This algorithm assumes, firstly, all interface dips remain constant over the distance considered and, secondly, an approximation of the elasticity model – that is, linearization of a phase velocity – valid for weak anisotropy can be used. Furthermore, when applied at the classic, and analytically solvable, case of traveltime analysis for a stack of flat layers with weak transverse isotropy, the algorithm explains theoretically the combination of anisotropy parameters that govern the non-hyperbolic term of a traveltime series: the established [Formula: see text] and its new counterpart [Formula: see text] for a [Formula: see text] - and [Formula: see text] -wave, respectively.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140674526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ming Zhang, Xin Zhang, Jing Liang, Xiaoyu Jiang, L. Gan, Xiping Sun, Xiaowei Yu
Combining PP and PS-waves from multicomponent data is an effective hydrocarbon characterization strategy because these two wave types are sensitive to different subsurface properties. We present a case study using multicomponent data to characterize tight sandstone gas reservoirs in the Jurassic Shaximiao Formation, the western Sichuan Basin, China. In the study area, PP data have difficulties to distinguish sandstones, mudstones and gas sand, while recently acquired multicomponent data show potential for the joint characterization of lithology, porosity, and gas saturation from the combination of PP and PS reflections. Sandstones and mudstones show small P-velocity contrasts and large S-velocity contrasts. Thus, PS data provide a more accurate description of sandstones as a substantial proportion of sandstones are undetectable from PP sections. P-impedance is sensitive to sandstone porosity variation, and seismic-predicted porosities based on impedance inversion are in good agreement with log-interpreted porosities. The ratio of P-velocity to S-velocity is sensitive to gas accumulation, and the ratios derived from joint PP-PS prestack inversion are determined to be better than from PP prestack inversion in terms of their agreements with logs and distinct gas-sand boundaries.
{"title":"Application of multicomponent seismic data to tight gas reservoir characterization: A case study in the Sichuan Basin, China","authors":"Ming Zhang, Xin Zhang, Jing Liang, Xiaoyu Jiang, L. Gan, Xiping Sun, Xiaowei Yu","doi":"10.1190/geo2023-0442.1","DOIUrl":"https://doi.org/10.1190/geo2023-0442.1","url":null,"abstract":"Combining PP and PS-waves from multicomponent data is an effective hydrocarbon characterization strategy because these two wave types are sensitive to different subsurface properties. We present a case study using multicomponent data to characterize tight sandstone gas reservoirs in the Jurassic Shaximiao Formation, the western Sichuan Basin, China. In the study area, PP data have difficulties to distinguish sandstones, mudstones and gas sand, while recently acquired multicomponent data show potential for the joint characterization of lithology, porosity, and gas saturation from the combination of PP and PS reflections. Sandstones and mudstones show small P-velocity contrasts and large S-velocity contrasts. Thus, PS data provide a more accurate description of sandstones as a substantial proportion of sandstones are undetectable from PP sections. P-impedance is sensitive to sandstone porosity variation, and seismic-predicted porosities based on impedance inversion are in good agreement with log-interpreted porosities. The ratio of P-velocity to S-velocity is sensitive to gas accumulation, and the ratios derived from joint PP-PS prestack inversion are determined to be better than from PP prestack inversion in terms of their agreements with logs and distinct gas-sand boundaries.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140672390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Bustamante, G. Fabien-Ouellet, Mathieu J. Duchesne, Amr Ibrahim
Marine seismic surveys can be used to map ice-bearing subsea permafrost on a large scale. However, present seismic processing technologies have limited capacity to image permafrost distribution at depth, mainly due to the low sensitivity of primary reflections and refractions to the velocity inversion found at the base of permafrost. Guided waves and multiples are more sensitive to the velocity variations below the top of permafrost, but they remain challenging to use in physics-based inversion approaches. A deep-learning-based seismic inversion has the potential to improve seismic imaging below the top of permafrost by automatically extracting information from all wave modes. We present a multi-input neural network to estimate seismic velocities from marine seismic data. The network is trained on synthetic data generated from representative distributions of the seismic properties of subsea permafrost. We show that our network can image large velocity contrasts and reversals in depth, typical of subsea permafrost. We use our network to estimate P- and S-wave velocity and Q-factor models from a seismic line in the Beaufort Sea. The neural network indicates highly discontinuous subsea permafrost with variable thickness in the area. Our work shows that deep-learning-based seismic inversion could become a cost-effective technology to map the distribution of subsea permafrost on a large scale and, more generally, high-velocity geological layers located in shallow waters.
海洋地震勘测可用于绘制大范围的含冰海底永久冻土图。然而，目前的地震处理技术对深层永久冻土分布的成像能力有限，主要原因是原初反射和折射对永久冻土底部的速度反演敏感度较低。导波和多重波对冻土层顶部以下的速度变化更为敏感，但在基于物理的反演方法中使用它们仍具有挑战性。基于深度学习的地震反演可以自动提取所有波模式的信息，从而改善冻土层顶部以下的地震成像。我们提出了一种从海洋地震数据中估算地震速度的多输入神经网络。该网络是根据海底永久冻土地震特性的代表性分布生成的合成数据进行训练的。我们的结果表明，我们的网络可以对海底永久冻土的典型特征--深度上的巨大速度对比和反转进行成像。我们使用神经网络估算了波弗特海一条地震测线的 P 波和 S 波速度以及 Q 因子模型。神经网络显示，该地区的海底永久冻土高度不连续，厚度不一。我们的工作表明，基于深度学习的地震反演可以成为一项具有成本效益的技术，用于绘制大范围的海底永久冻土分布图，以及更广泛的浅水区高速地质层分布图。
{"title":"Deep-learning viscoelastic seismic inversion for mapping subsea permafrost","authors":"J. Bustamante, G. Fabien-Ouellet, Mathieu J. Duchesne, Amr Ibrahim","doi":"10.1190/geo2022-0759.1","DOIUrl":"https://doi.org/10.1190/geo2022-0759.1","url":null,"abstract":"Marine seismic surveys can be used to map ice-bearing subsea permafrost on a large scale. However, present seismic processing technologies have limited capacity to image permafrost distribution at depth, mainly due to the low sensitivity of primary reflections and refractions to the velocity inversion found at the base of permafrost. Guided waves and multiples are more sensitive to the velocity variations below the top of permafrost, but they remain challenging to use in physics-based inversion approaches. A deep-learning-based seismic inversion has the potential to improve seismic imaging below the top of permafrost by automatically extracting information from all wave modes. We present a multi-input neural network to estimate seismic velocities from marine seismic data. The network is trained on synthetic data generated from representative distributions of the seismic properties of subsea permafrost. We show that our network can image large velocity contrasts and reversals in depth, typical of subsea permafrost. We use our network to estimate P- and S-wave velocity and Q-factor models from a seismic line in the Beaufort Sea. The neural network indicates highly discontinuous subsea permafrost with variable thickness in the area. Our work shows that deep-learning-based seismic inversion could become a cost-effective technology to map the distribution of subsea permafrost on a large scale and, more generally, high-velocity geological layers located in shallow waters.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140676218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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