Estimation of the Oil-in-Place Resources in the Liquid-Rich Shale Formations Exploiting Geochemical and Petrophysical Data in a 3D High-Resolution Geological Model Domain: Baltic Basin Case Study

Abstract

The paper discusses the issue of oil-in-place estimation for liquid-saturated shales in Lower Paleozoic (Silurian and Ordovician) organic-rich formations of the Baltic Basin in North Poland. The authors adopted a geochemical method based on Rock Eval results which directly measure hydrocarbon content present in rock samples. Its application on a real data set required the implementation of correction procedures to consider also those oil compounds which were lost before Rock Eval measurements were taken or are not recorded in S1 parameter. It was accomplished through the introduction of two correction coefficients: c1—for evaporation loss and c2—for heavier compounds underestimation. The first one was approximated on the basis of published results and known properties of crude oil, while the second one was addressed with laboratory experimental procedure which combines Rock Eval pyrolysis and rock sample extraction with organic solvents. The calculation formulas were implemented in the 3D geological model of shale formations reproducing their geometry as well as the spatial variability of the petrophysical and geochemical properties. Consequently, the results of oil-in-place estimation were also available as 3D models, ready for visualization and interpretation in terms of delineation of most favorable zones or well placement. The adopted geochemical method and the results of oil-in-place estimation it produced were confronted with standard volumetric method. Although both of them are volumetric methods, the results depend on different sets of rock properties, which is an advantage for result comparison reasons. The study revealed that the geochemical method of oil-in-place estimation in liquid-rich shales after appropriate adjustment, considering shale formation and reservoir fluid dependent conditions, could provide reliable results and be implemented on the early stage of shale exploration process in a condition of production data inaccessibility.

The Use of Machine Learning in Oil Well Petrophysics and Original Oil in Place Estimation: A Systematic Literature Review Approach

“…Getting to know the estimated volume of oil in place is necessary so as to help when actually computing the recoverable volume of oil in a particular reservoir. According to Sowiżdżał et al [12], methods for oil in place estimation includes Volumetric, Material balance, Production history and Analogy methods. All of these methods use the petrophysical properties of the well to estimate the oil in place.…”

Multidisciplinary Characterization of Unconventional Reservoirs Based on Correlation of Well and Seismic Data

“…Furthermore, the recently developed rock physics template (RPT) technique [36] can estimate the fluid and mineralogical content of a reservoir rock on a cross plot of Vp/Vs ratio against the AI of a P wave (Figure 2). This method has been described in numerous publications [2,11,13,[32][33][34][35][36][37][38][39][40], including focused studies of elastic parameter recognition and RPT analysis of Polish shales [3,4,10,21,[41][42][43]. The process of successfully integrating data at different scales represents the biggest challenge in generating detailed 3D models of reservoirs.…”

“…These analyses were used to quantify the hydraulic fracturing potential of two source intervals located within Silurian and Ordovician strata (Figure 1). Previous research and recent studies covering the parametrical characterization of the research area have been well investigated by numerous authors [2][3][4][5][6][7][8][9][10]. These studies can be divided into three general topics:…”

“…Integration of well logs interpretation of particular parameters and seismic attributes together with the extensive geostatistics tools application (3D) [8][9][10].…”