Seismic prediction of shale oil lithofacies associations based on sedimentary facies patterns: A case study of the shahejie formation in the Huanghekou Sag

基于沉积相模式的页岩油岩相组合地震预测:以黄河口凹陷沙河街组为例

阅读:1

Abstract

The lithofacies play a pivotal role in studying development patterns, reservoir characteristics, and sweet spot predictions of shale oil. Lithofacies classification typically relies on core observations and conventional well logging analyses, whereas seismic attribute extraction is often employed in regions with sparse or absent wells. However, seismic attribute extraction entails considerable computation and time, and exclusive reliance on seismic attribute analysis can result in multiple interpretations. This paper emphasizes predicting shale oil lithofacies associations based on seismic reflection characteristics and sedimentary facies patterns which can can help avoid these issues. The lithofacies classification scheme has identified seven lithofacies and associations by means of core observations, testing data, and logging curve analysis of the Shahejie Formation in the Huanghekou Sag. Through well-seismic calibration, the seismic reflections and sedimentary patterns of different lithofacies associations were examined to formulate a seismic facies identification chart and propose six models. For areas without wells, based on the distribution of sedimentary facies and in combination with seismic reflection characteristics, identification and delineation are conducted on a planar scale to analyze the distribution features of lithofacies associations. The results of predicting the distribution of shale oil lithofacies associations in the Shahejie Formation indicate that the development pattern of lithofacies associations is basically consistent with that of sedimentary facies units. The primary models developed in the study area encompass delta, sublacustrine fan, and shore-shallow lake. The approach of identifying shale oil lithofacies associations based on seismic reflection and sedimentary backgrounds offers a novel means for discerning lithofacies and associations in sections devoid of cores and specialized well logging data.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。