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首页> 外文期刊>AAPG Bulletin >Organic-rich Marcellus Shale lithofacies modeling and distribution pattern analysis in the Appalachian Basin
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Organic-rich Marcellus Shale lithofacies modeling and distribution pattern analysis in the Appalachian Basin

机译:阿巴拉契亚盆地富含有机质的Marcellus页岩岩相建模和分布模式分析

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摘要

The Marcellus Shale is considered to be the largest unconventional shale-gas resource in the United States. Two critical factors for unconventional shale reservoirs are the response of a unit to hydraulic fracture stimulation and gas content. The fracture attributes reflect the geomechanical properties of the rocks, which are partly related to rock mineralogy. The natural gas content of a shale reservoir rock is strongly linked to organic matter content, measured by total organic carbon (TOC). A mudstone lithofacies is a vertically and laterally continuous zone with similar mineral composition, rock geomechanical properties, and TOC content. Core, log, and seismic data were used to build a three-dimensional (3-D) mudrock lithofacies model from core to wells and, finally, to regional scale. An artificial neural network was used for lithofacies prediction. Eight petrophysical parameters derived from conventional logs were determined as critical inputs. Advanced logs, such as pulsed neutron spectroscopy, with log-determined mineral composition and TOC data were used to improve and confirm the quantitative relationship between conventional logs and lithofacies. Sequential indicator simulation performed
机译:Marcellus页岩被认为是美国最大的非常规页岩气资源。页岩非常规储层的两个关键因素是单元对水力压裂增产和含气量的响应。断裂属性反映了岩石的地质力学特性,部分与岩石矿物学有关。页岩储层岩石的天然气含量与有机物含量密切相关,而有机物含量是通过总有机碳(TOC)来衡量的。泥岩岩相是垂直和横向连续的区域,具有相似的矿物成分,岩石地质力学性质和TOC含量。岩心,测井和地震数据被用来建立三维(3-D)泥岩岩相模型,从岩心到井,再到区域尺度。人工神经网络用于岩相预测。确定了源自常规测井的八个岩石物理参数作为关键输入。具有测井确定的矿物成分和TOC数据的先进测井(例如脉冲中子光谱法)用于改善和确认常规测井与岩相之间的定量关系。进行了顺序指标模拟

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