Use of Geological Constraints in Multi-Mineral Modeling for Unconventional Reservoirs

Abstract

Determination of mineral rock composition is an important part of unconventional reservoir formation evaluation because the mineral composition affects hydraulic fracture generation and propagation. Two types of models are usually used for mineralogy modeling—deterministic and stochastic. Both models apply mathematical representations of the logging tool responses; however, stochastic modeling has become more popular due to its consideration of random distributions in the predictor and target variables. Stochastic mineralogy modeling algorithms usually produce solutions by minimizing a function reflecting the differences between the measured and modeled responses. However, due to the non-uniqueness inherent in inversion methods, the solution may not provide petrophysically meaningful results. To avoid producing compromised results, the use of geological constraints is proposed to represent the geological relations between the unknown parameters (inversion variables), leading to a more meaningful mineralogy model. The proposed algorithm incorporates probability functions to generate mineralogical solutions representing geologically and petrophysically sound results. The weight assigned to the penalties in the cost function depends on the probability function assigned to the constraints. Two models are presented using the proposed algorithm: a pyrite-anhydrite constraint based on the iron and sulfur ratio, and a K-feldspar-albite constraint based on the thorium and potassium ratio. Data sets from several different shale plays, from across North America, are processed using the proposed algorithm. The mineral sets are complex and vary from one play to another. The results show excellent agreement with the available core X-ray diffraction measurements. The study demonstrates that the proposed constraints provide an effective improvement, in integrated formation evaluation, especially in unconventional reservoirs with highly complex mineralogy.