The Method of DFN in Granite Buried Hill Reservoir Based on Multiple Attribute Constraints: A Case Study of B Field, Chad

Abstract

The granite buried hill reservoir is multiply reconstructed by tectonic, weathering and erosion process. The pores, fractures and caves in the reservoir are well developed together which induces extremely strong heterogeneity, so the common reservoir modeling method is not suitable for the characterization of fractured reservoirs. Taking granite buried hill B reservoir in Chad as example, based on comprehensive analysis of structure interpretation, reservoir inversion, imaging logging, core observation and oilfield dynamic data, a new set of methods for fracture reservoir with “scale classification, multiple constrains, dynamic verification” is proposed. Firstly, the large-scale discrete fracture model is obtained from seismic interpretation by the deterministic method. Then the accurate distribution of medium and small- scale fracture parameter is obtained according to core observation, imaging logging and microscopic slice data. Meanwhile, the fracture development intensity, called structure driver, is built based on the weighting different main controlling factors, such as fault distance, tectonic stress, lithofacies and average curvature. Constrained by the fracture driver, the medium and small-scale discrete fracture network (DFN) model is established by geostatistics. Finally, different scale fracture models are integrated and property models are obtained with upscaling method, at the same time the property models are optimized and verified by static and dynamic data of reservoir.