Multivariate Statistical Analysis Reveals the Heterogeneity of Lacustrine Tight Oil Accumulation in the Middle Permian Jimusar Sag, Junggar Basin, NW China

Abstract

Tight oil and gas accumulation commonly has heterogeneities within the reservoir formation. This heterogeneity, however, is hard to investigate by conventional geological and (organic) geochemical tools and thus is critical and challenging to study. Here, we attempted multivariate statistical analysis to reveal the heterogeneity based on a case study in the lacustrine tight oil accumulation in the middle Permian Lucaogou Formation of the Jimusar sag, Junggar Basin, NW China. Clustering heat maps and multi-dimensional scaling analysis revealed the heterogeneity of tight oil accumulation. The heterogeneity is reflected by the complex relationship between the two reservoir sweet spots as well as the oil migration and accumulation vertically and spatially, rather than the previous thoughts that it is a closed system associated with proximal hydrocarbon accumulation patterns. Multiple biomarkers show that the source rocks and reservoirs have similar characteristics in the lower part of the formation, reflecting a proximal hydrocarbon accumulation pattern in the lower sweet spot (near-source accumulation, abbreviated as NA). This represents a relatively closed system. However, the upper sweet spot and the middle section mudstone sequence intervening the two sweet spots are not a completely closed system in a strict sense. These sequences can be divided into three tight oil segments, i.e., lower, middle, and upper from deep to shallow. The lower segment is sited in the lower part of the middle section mudstone sequence. The middle segment is composed of the upper part of the middle section mudstone sequence and the lower part of the upper sweet spot. The upper segment is composed of the upper part of the upper sweet spot and the overlying upper Permian Wutonggou Formation reservoirs. Oils generated in the lower segment migrated vertically to upper sweet spot reservoirs through faults/fractures, and laterally to distal reservoirs. Oils generated in the middle segment were preserved in reservoirs of the upper sweet spot. Oils in the upper segment require accumulation by vertical and lateral migration through faults/fractures. As such, the tight oil accumulation is complex in the Lucaogou Formation. From base to top, the accumulation mechanisms in the Lucaogou Formation were NA, VLMA (vertical and lateral migration and accumulation), NA and VLMA, thereby showing strong heterogeneities. Our data suggest that these processes might be typical of tight oil accumulations universally, and are important for future exploration and exploitation in the region to consider the heterogeneities rather than a closed system. The multivariate statistical analysis is an effective tool for investigating complex oilsource correlations and accumulation in petroleum basins.

Chemometric Classification of Crude Oils in Complex Petroleum Systems Using t-Distributed Stochastic Neighbor Embedding Machine Learning Algorithm

“…The variable oil density might be related to the complex organic inorganic–interaction during hydrocarbon generation. First, haloduric algae have been universally acknowledged for highly efficient and prolonged oil generation compared with those freshwater algae. , Second, the effects of carbonate and biocarbonate minerals on hydrocarbon generation and expulsion of source rocks are really complex. It was found that pyrolysis reactions are catalyzed by alkali and alkaline earth metal cations, resulting in more hydrocarbons generating from kerogen. − Meanwhile, hydrocarbon expulsion appears to be retarded due to the absorption of carbonate minerals, which results in more heavy components of hydrocarbon that generated at earlier stage retained in the source-rock sequences whereas lighter compounds prefer to be expelled .…”

“…Therefore, linear dimensionality reduction has considerable limitations, particularly when analyzing the geochemical characteristics of hydrocarbons in complex petroleum systems. A relatively low fitting accuracy is obtained when the higher-dimensional relationships of such data are characterized using the linear dimensionality reduction approach, and may yield results that are geologically unreasonable …”

“…A relatively low fitting accuracy is obtained when the higher-dimensional relationships of such data are characterized using the linear dimensionality reduction approach, and may yield results that are geologically unreasonable. 38 Recently, novel dimensionality reduction theories have been proposed that are based on machine learning. The basic premise is to restore the lower-dimensional manifold structure in higherdimensional space and construct a corresponding embedding map, to obtain dimensionality reduction and data visualization.…”

Origin of authigenic albite in a lacustrine mixed-deposition sequence (Lucaogou Formation, Junggar Basin) and its diagenesis implications

“…In recent years, the Permian shale oil exploration in the Junggar Basin has made major breakthroughs (e.g. Cao et al, 2020;Li et al, 2021;Wang et al, 2020a;Wu et al, 2016Wu et al, , 2017. Among them, the organic-rich Lucaogou Formation, a unique lacustrine mixed depositional sequence composed of terrigenous clastic, carbonate minerals, and volcaniclastic sediments (e.g.…”

Oil chemometrics and geochemical correlation in the Weixinan Sag, Beibuwan Basin, South China Sea

“…The chemometric method can simultaneously process the measured parameters or variables based on multivariate statistical treatments. Therefore, this method has been widely used in several disciplines after its development in only a few decades (Bevilacqua et al, 2017;Chabukdhara and Nema, 2012;Madsen et al, 2010;Wang et al, 2020); however, its application in the field of petroleum geochemistry began in the 1980s (Kvalheim et al, 1985;Øygard et al, 1984;Peters et al, 1986;Telnaes and Dahl, 1986;Zumberge, 1987).…”