Well - data - driven 3D geological modelling of reservoiss: Xiaermen oilfield case study

Abstract

This research focused on creating a 3D geological model using well data, to enhance model accuracy and support the economic development planning of the Xiaermen oilfield. Data from 40 well were utilized, resulting in a more detailed and accurate model. A sequential workflow was adopted, beginning with large scale (discrete proprieties) and progressing to smaller scale proprieties characterized by greater uncertainty, modeled using a geostatistical method to analyze their distributions across the reservoir. The Sequential Indicator Simulator and Sequential Gaussian Simulation Algorithms were used under stochastic model to distribute reservoir proprieties effectively. This study underscores the importance of well-data-driven 3D Geological Modelling in Reservoir Characterization, highlighting the used methodology in this domain. By integrating a diverse data source, this study identified critical geological feature such as facies distributions, porosity variations and fluid saturations enabling robust decision making processes. Incorporating well data with seismic information, allowed geoscientists to correlate seismic attributes with reservoir properties, significantly improving the accuracy of the resulting geological models. This integration also provided a more precise understanding of the reservoir's structural framework, fault systems, and stratigraphic variations, essential for optimized reservoir management and development.