Прогнозирование нефтегазоносности южной части Пермского края с использованием регионального трехмерного моделирования

Abstract

The territory of the southern part of Perm Krai is well studied in terms of oil and gas prospecting. About 150 oil and gas fields have been discovered there, over 7000 deep wells have been drilled, and 3D seismic surveys have been completed on the area exceeding 5000 km2. The state of exploration of the territory allows us to have an immense array of geologic information, which can be used to search and predict oil and gas occurrence in structures that remain left out or that have not been studied yet. The research area was limited by the confines of Perm Krai in the south, west, and east and by a conventional line in the north along the boundary of the completed seismic surveys. To study the territory based on the reflecting horizon surface of Perm Krai, a 3D geological model has been built within IRAPRMS software system. The model calculates a regional, a zonal and local constituents of the reflecting horizon of Perm Krai. The local constituent allowed us to single out structures divided into three categories: structures of ascertained oil and gas occurrence, structures that do not contain oil and gas (empty), and structures for which a prediction is needed. In the model, structural parameters representing a trap potential for the accumulation and retention of hydrocarbons were calculated. Moreover, geochemical parameters showing a generation potential and a migration constituent, as well as hydrogeological parameters as indirect data to determine the saturation of structures with hydrocarbons, were downloaded into the model. The obtained data about the importance of each parameter for all structures allowed us to generate a single database and predict oil and gas occurrence by the machine learning method, i.e. through the step-bystep linear discriminant analysis. Based on the results of the linear discriminant analysis, 138 predicted structures were arranged in groups in accordance with degrees of their potential. By applying the built individual probability models, a map of the regional probability of structures’ saturation with hydrocarbons was obtained; this map served as a basis and amendment of oil and gas geological zoning boundaries of the southern part of Perm Krai.