Application of Thin Reservoir Prediction Technology Based on Frequency Domain in Coal Measure Strata

doi:10.7657/XJPG20210514

Abstract

Abstract:

The Lower Permian Taiyuan formation of marine-continental transitional facies and the second member of the Middle Permian Shanxi formation (Shan 2 member for short) of delta front facies are primary natural gas pay zones in eastern Ordos basin. They are tight lithologic gas reservoirs characterized by thin sand body and small scale. In the Taiyuan formation and the Shanxi formation, there are several coal seams, among which No. 4+5 coal seam in the middle-lower Shan 2 member and No. 9 coal seam at the bottom of the Taiyuan formation are most developed. With lower wave impedance, coal seams show stronger reflection than sandstone and shale with higher wave impedances, so that the former shield the weak reflection from the latter, making it difficult to effectively predict thin sand bodies by using conventional methods such as prestack inversion and seismic attributes. On the geological model of sandstone and shale reservoirs in the target intervals in the study area, we carried out forward modeling and time-frequency analysis, and found that generalized S-transform could adaptively adjust time-frequency analysis window according to signal frequency, and its resolution was higher. In the actual application, strong reflections from coal seams were suppressed, then generalized S-transform was performed to predict thin reservoirs in the study area. The result shows a high coincidence rate between seismic data and well logging data. The method can effectively predict thin reservoirs on the background of coal seams.

Key words: Ordos basin, thin reservoir prediction, coal measure strata, strong reflection suppression, frequency domain, time-frequency analysis, generalized S-transform

CLC Number:

P631.445.91

FENG Xinpeng, WANG Tao, BAI Zhitao, NIE Wancai, HE Zhengguang. Application of Thin Reservoir Prediction Technology Based on Frequency Domain in Coal Measure Strata[J]. Xinjiang Petroleum Geology, 2021, 42(5): 605-611.

Figures/Tables 9

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