New Approach for the Probabilistic Assessment of Organic Matter in the Source Rocks of the Bazhenov Formation for Estimation of Shale Hydrocarbons Resources

Abstract

Maps of organic matter distributions are an essential part of the basin modeling process for evaluation of conventional and unconventional hydrocarbon resources. This approach has become widespread for both assessment of the initial oil and gas generation potential and final assessment of the resource base. An important step in this method is pyrolysis of the core material, which is carried out in order to assess the geochemical parameters of source rocks. The data can be used to create maps of the distributions of geochemical parameters, such as the organic carbon content, the hydrogen index, the oxygen index, S1,S2,S3, TMax. The accepted assumption regarding the distribution of these parameters determines the entire modeling result and the final generation volumes. It is difficult to overestimate the impact of this process on the result of assessing the prospects for both traditional and shale hydrocarbons. However, a lot of uncertainty is associated with interpolation of parameters analyzed in wells into the interwell space because different interpolation methods give fundamentally different results. Deterministic interpolation methods are limited because of their nature and thus cannot be used for probabilistic estimation, so they are not considered in this work. There are two interpolation methods that can perform this process in a multivariate form: the geostatistical approach (SGS, GRFS) and the new Amazonas method, which integrates elements of artificial intellect.

The stochastic approach to modeling has the undeniable advantages of estimating probabilities, and it includes uncertainties, which demonstrates the general idea more clearly. In most geology-related fields, the deterministic approach is gradually fading into the background, giving way to stochastic methods.

This article considers a comparison of the SGS and Amazonas methods, their prerequisites and limitations, advantages and disadvantages using the example of a database of geochemical measurements of the Bazhenov source rock data. The results of modeling by both methods are shown in this work along with the issues of statistical stability of the results.

The geostatistical approach in interpolation has been used for decades. It has a simple and understandable operating principle, but there are several fundamental limitations. These limitations are associated with the assumption of stationarity of the random variable under study. The proposed Amazonas method also offers a simple and understandable way to calculate the quantity being analyzed at each point in space. However, the latter does not have the limitations of the geostatistical approach. Besides, this method does not require the condition of stationarity for the quantity being analyzed and is also capable, depending on the settings, of reproducing both smooth and abrupt transitions.