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作 者:Lei Wang Shao-Gui Deng Pan Zhang Ying-Chang Cao Yi-Ren Fan Xi-Yong Yuan
机构地区:[1]School of Geosciences,China University of Petroleum,Qingdao 266580,Shandong,China [2]Laboratory for Marine Mineral Resources,Qingdao National Laboratory for Marine Science and Technology,Qingdao 266071,Shandong,China [3]CNPC Key Laboratory for Well Logging,China University of Petroleum,Qingdao 266580,Shandong,China
出 处:《Petroleum Science》2019年第5期1015-1027,共13页石油科学(英文版)
基 金:co-funded by Chinese Postdoctoral Science Foundation(2018M640663);the National Natural Science Foundation of China(41474100,41574118,41674131);National Science and Technology Major Project of the Ministry of Science and Technology of China(2017ZX05009-001)
摘 要:We present systematic investigations on the physics,detection performance and inversion of logging-while-drilling extradeep azimuthal resistivity measurements(EDARM).First,the definitions of EDRAM measurements are discussed,followed by the derivation of the attenuation and phase-shift geometrical factors to illustrate the relative contributions of formation units to the observed signals.Then,a new definition of detection depth,which considers the uncertainty of inversion results caused by the data noise,is proposed to quantify the detection capability of ED ARM.Finally,the B ayesian theory associated with Markov chain Monte Carlo sampling is introduced for fast processing of EDARM data.Numerical results show that ED ARM is capable of detecting the azimuth and distance of remote bed boundaries,and the detection capability increases with increasing spacing and resistivity contrast.The EDARM tool can accommodate a large range of formation resistivity and is able to provide the resistivity anisotropy at arbitrary relative dipping angles.In addition,multiple bed boundaries and reservoir images near the borehole are readily obtained by using the Bayesian inversion.
关 键 词:Extra-deep azimuthal resistivity measurements(EDARM) Detection performance Inversion method Reservoir imaging Detection of multiple bed boundaries
分 类 号:P631.811[天文地球—地质矿产勘探]
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