Petroleum Science >2018,??Issue 2:??270-288 DOI: https://doi.org/10.1007/s12182-018-0229-y
The impact of geological uncertainty on primary production from a fluvial reservoir Open?Access
文章信息
作者：Mohammad Koneshloo, Saman A. Aryana and Xiaoni Hu
作者單位：
Department of Petroleum Engineering, University of Wyoming, Laramie, WY 87061, USA,Department of Petroleum Engineering, University of Wyoming, Laramie, WY 87061, USA; Department of Chemical Engineering, University of Wyoming, Laramie, WY 87061, USA and Department of Geological Sciences, University of Wyoming, Laramie, WY 87061, USA
投稿時(shí)間：2017-07-04
引用方式：Koneshloo, M., Aryana, S.A. & Hu, X. Pet. Sci. (2018) 15: 270. https://doi.org/10.1007/s12182-018-0229-y
文章摘要
Deposition of fluvial sandbodies is controlled mainly by characteristics of the system, such as the rate of avulsion and aggradation of the fluvial channels and their geometry. The impact and the interaction of these parameters have not received adequate attention. In this paper, the impact of geological uncertainty resulting from the interpretation of the fluvial geometry, maximum depth of channels, and their avulsion rates on primary production is studied for fluvial reservoirs. Several meandering reservoirs were generated using a process-mimicking package by varying several controlling factors. Simulation results indicate that geometrical parameters of the fluvial channels impact cumulative production during primary production more significantly than their avulsion rate. The most significant factor appears to be the maximum depth of fluvial channels. The overall net-to-gross ratio is closely correlated with the cumulative oil production of the field, but cumulative production values for individual wells do not appear to be correlated with the local net-to-gross ratio calculated in the vicinity of each well. Connectedness of the sandbodies to each well, defined based on the minimum time-of-flight from each block to the well, appears to be a more reliable indicator of well-scale production.
關(guān)鍵詞
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Geological uncertainty evaluation, Fluvial reservoir modeling, Process-mimicking simulation, Geometry of fluvial channels