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Frontiers in Earth Science
Article . 2022 . Peer-reviewed
License: CC BY
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Frontiers in Earth Science
Article . 2022
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Multi-Factor Evaluation of Deep Karst Dolomite Reservoir Based on Paleogeomorphological Reconstruction, a Case Study From the 4th Member of the Dengying Formation in the Central Sichuan Basin, China

Authors: Zikun Zhou; Zikun Zhou; Xingzhi Wang; Xingzhi Wang; Xiyan Yang; Xiyan Yang; Long Wen; +9 Authors

Multi-Factor Evaluation of Deep Karst Dolomite Reservoir Based on Paleogeomorphological Reconstruction, a Case Study From the 4th Member of the Dengying Formation in the Central Sichuan Basin, China

Abstract

The evaluation of reservoirs is of great importance in exploration practices, and reservoir distribution is dependent on multiple geological factors. The carbonate platform of the fourth member (Z2dn4) of the Dengying Formation (Z2dn) in the Gaoshiti-Moxi area (GMA) was uplifted above sea level during episode II of the Tongwan movement and underwent prolonged karstification by meteoric freshwater in the terminal Sinian, leading to a strong heterogeneity in reservoirs. Paleogeomorphology reflects hydraulic gradients that can affect the intensities of surface karstification and may be approximated by terrain slope gradients. Karst products (especially solution vugs and caverns) exist prevailingly in the Z2dn4; their development mirrors the extents of internal dissolution. Based on paleogeomorphological reconstruction using the elevation method, the slope angles of single boreholes were calculated through the digital elevation model (DEM). In accordance with single-borewell Fullbore Formation MicroImager (FMI) logging data, four electrofacies (host rock, vug, fracture, and cave) were identified in boreholes possessing FMI data. The identified electrofacies were matched with corresponding conventional logging curves to obtain the training data. A model generalized for other boreholes without FMI data was established with the random forest algorithm and the thicknesses of the four electrofacies in each borehole were determined to characterize the extent of karstification. Slope gradients and electrofacies thicknesses, together with multiple physical parameters of reservoirs in boreholes, were utilized for factor analysis. Four factors were obtained and fused into one comprehensive score based on their ratios of variance proportions. The favorability of reservoirs was described by the comprehensive scores of each borehole. These analyses showed that the most advantageous reservoirs are distributed in the vicinity of the platform margin in the west of the GMA, where they enjoy several benefits. Deposition of porous mound-shoal complexes occurs predominantly in the platform margin where large-scale caves are more developed in the mixing karst zone of seawater and freshwater. Meanwhile, the transmeridional lateral migration of hydrocarbons from the regional hydrocarbon-generating center abutting the west of the GMA contributes to earlier entrapment and accumulation in the mound-shoal complexes in the platform margin.

Keywords

Gaoshiti-Moxi area, random forest algorithm, Science, Q, reservoir evaluation, General Earth and Planetary Sciences, factor analysis, paleogeomorphological reconstruction, Deng member

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
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