General purpose graphic processing unit （GPU） calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has ...General purpose graphic processing unit （GPU） calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has a huge quantity of data and calculation steps. In this study, we introduce a GPU-based parallel calculation method of a precise integration method （PIM） for seismic forward modeling. Compared with CPU single-core calculation, GPU parallel calculating perfectly keeps the features of PIM, which has small bandwidth, high accuracy and capability of modeling complex substructures, and GPU calculation brings high computational efficiency, which means that high-performing GPU parallel calculation can make seismic forward modeling closer to real seismic records.展开更多
Compaction correction is a key part of paleogeomorphic recovery methods. Yet, the influence of lithology on the porosity evolution is not usually taken into account. Present methods merely classify the lithologies as ...Compaction correction is a key part of paleogeomorphic recovery methods. Yet, the influence of lithology on the porosity evolution is not usually taken into account. Present methods merely classify the lithologies as sandstone and mudstone to undertake separate porositydepth compaction modeling. However, using just two lithologies is an oversimplification that cannot represent the compaction history. In such schemes, the precision of the compaction recovery is inadequate. To improve the precision of compaction recovery, a depth compaction model has been proposed that involves both porosity and clay content. A clastic lithological compaction unit classification method, based on clay content, has been designed to identify lithological boundaries and establish sets of compaction units. Also, on the basis of the clastic compaction unit classification, two methods of compaction recovery that integrate well and seismic data are employed to extrapolate well-based compaction information outward along seismic lines and recover the paleo-topography of the clastic strata in the region. The examples presented here show that a better understanding of paleo-geomorphology can be gained by applying the proposed compaction recovery technology.展开更多
A considerable effort has been made in the literature for quality assurance (QA) and quality checking (QC) of the petrophysical log data for computation of reservoir rock property parameters. Well log data plays an in...A considerable effort has been made in the literature for quality assurance (QA) and quality checking (QC) of the petrophysical log data for computation of reservoir rock property parameters. Well log data plays an integral role in building a rock physics model for quantitative interpretation (QI) work. A poor-quality rock physics model may lead to significant financial and HSSE implications by drilling wells in undesired locations. Historically, a variety of techniques have been used including histograms and cross plots for reviewing the feasibility of petrophysical logs for QI work. However, no attempt has ever been made to introduce a simplified workflow. This paper serves two-fold. It provides a simplified step by step approach for building a petrophysics/rock physics model. A case study has been presented to compare the synthetic seismogram generated from the simplified workflow with the actual seismic trace at well locations. Secondly, the paper shows how a few key cross plots and rock property parameters provide adequate information to validate petrophysical data, distinguish overburden and reservoir sections, and to help identify fluids and saturation trends within the reservoir sands. In the mentioned case study, the robustness of the simplified rock physics model has helped seismic data to successfully distinguish hydrocarbon bearing reservoir sands from non-reservoir shales.展开更多
针对传统基于文档的系统工程方法在高复杂度卫星互联网仿真平台开发中存在的系统设计协调性差及早期仿真验证不足等问题,提出采用基于模型的系统工程(model-based systems engineering,MBSE)方法开展卫星互联网仿真平台架构建模。首先,...针对传统基于文档的系统工程方法在高复杂度卫星互联网仿真平台开发中存在的系统设计协调性差及早期仿真验证不足等问题,提出采用基于模型的系统工程(model-based systems engineering,MBSE)方法开展卫星互联网仿真平台架构建模。首先,提出基于MBSE的双V模型(dual V model based on MBSE,DVMBSE)及与外部软件集成验证架构;然后,基于MBSE方法论对卫星互联网仿真平台顶层架构开展需求分析、功能分解及交互结构建模;最后,通过运行逻辑验证与外部模型集成验证实现了模型的有效性验证,从而支撑卫星互联网设计论证。展开更多
基金supported by the National Natural Science Foundation of China (Nos 40974066 and 40821062)National Basic Research Program of China (No 2007CB209602)
文摘General purpose graphic processing unit （GPU） calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has a huge quantity of data and calculation steps. In this study, we introduce a GPU-based parallel calculation method of a precise integration method （PIM） for seismic forward modeling. Compared with CPU single-core calculation, GPU parallel calculating perfectly keeps the features of PIM, which has small bandwidth, high accuracy and capability of modeling complex substructures, and GPU calculation brings high computational efficiency, which means that high-performing GPU parallel calculation can make seismic forward modeling closer to real seismic records.
文摘Compaction correction is a key part of paleogeomorphic recovery methods. Yet, the influence of lithology on the porosity evolution is not usually taken into account. Present methods merely classify the lithologies as sandstone and mudstone to undertake separate porositydepth compaction modeling. However, using just two lithologies is an oversimplification that cannot represent the compaction history. In such schemes, the precision of the compaction recovery is inadequate. To improve the precision of compaction recovery, a depth compaction model has been proposed that involves both porosity and clay content. A clastic lithological compaction unit classification method, based on clay content, has been designed to identify lithological boundaries and establish sets of compaction units. Also, on the basis of the clastic compaction unit classification, two methods of compaction recovery that integrate well and seismic data are employed to extrapolate well-based compaction information outward along seismic lines and recover the paleo-topography of the clastic strata in the region. The examples presented here show that a better understanding of paleo-geomorphology can be gained by applying the proposed compaction recovery technology.
文摘A considerable effort has been made in the literature for quality assurance (QA) and quality checking (QC) of the petrophysical log data for computation of reservoir rock property parameters. Well log data plays an integral role in building a rock physics model for quantitative interpretation (QI) work. A poor-quality rock physics model may lead to significant financial and HSSE implications by drilling wells in undesired locations. Historically, a variety of techniques have been used including histograms and cross plots for reviewing the feasibility of petrophysical logs for QI work. However, no attempt has ever been made to introduce a simplified workflow. This paper serves two-fold. It provides a simplified step by step approach for building a petrophysics/rock physics model. A case study has been presented to compare the synthetic seismogram generated from the simplified workflow with the actual seismic trace at well locations. Secondly, the paper shows how a few key cross plots and rock property parameters provide adequate information to validate petrophysical data, distinguish overburden and reservoir sections, and to help identify fluids and saturation trends within the reservoir sands. In the mentioned case study, the robustness of the simplified rock physics model has helped seismic data to successfully distinguish hydrocarbon bearing reservoir sands from non-reservoir shales.
文摘针对传统基于文档的系统工程方法在高复杂度卫星互联网仿真平台开发中存在的系统设计协调性差及早期仿真验证不足等问题,提出采用基于模型的系统工程(model-based systems engineering,MBSE)方法开展卫星互联网仿真平台架构建模。首先,提出基于MBSE的双V模型(dual V model based on MBSE,DVMBSE)及与外部软件集成验证架构;然后,基于MBSE方法论对卫星互联网仿真平台顶层架构开展需求分析、功能分解及交互结构建模;最后,通过运行逻辑验证与外部模型集成验证实现了模型的有效性验证,从而支撑卫星互联网设计论证。
