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Geostatistical modeling for reservoir dominated by faults and fractures

Grant number: 20/02130-2
Support type:Scholarships in Brazil - Master
Effective date (Start): May 01, 2020
Effective date (End): February 28, 2022
Field of knowledge:Physical Sciences and Mathematics - Geosciences - Geology
Cooperation agreement: Equinor (former Statoil)
Principal Investigator:Alexandre Campane Vidal
Grantee:Cristian Ricardo Mendoza Blanco
Home Institution: Centro de Estudos do Petróleo (CEPETRO). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Associated research grant:17/15736-3 - Engineering Research Centre in Reservoir and Production Management, AP.PCPE

Abstract

The reserves in carbonate formation are 50% of known economic reserves all over the world, the majority of them are considered as naturally fractured reservoir. Fracture prediction is important for evaluating and developing fractured reservoirs. However, it is difficult to characterize fractures properly because of their extremely heterogeneity and complexity features. Different types of data are used to describe the fractures, such as seismic attributes, geophysical logs, drilling cores and outcrops. Recently, the combination of multiple attributes is used to detect the seismic edges, to enhance the interpretation for the subtle faults and fractures. One important method is the discrete fracture network (DFN) model. DFN modelling is an advanced approach for fracture modelling, of which different sets of fractures could be created. Each fracture is presented by a plane with specific parameters such as dip angle, dip azimuth, aperture and etc. The fracture model built by DFN approximates the real fracture distribution in plays and deterministic and stochastic fractures can be generated. The petrophysical properties, e.g., porosity and permeability, can be calculated by upscaling the DFN model into cells in order to simulate the reservoir fluid flow. So this project aims to simulate the distribution of faults and fractures of a Brazilian pre-salt reservoir. This will give probability scenarios, providing the potential areas for higher intensities of faults/fractures in the reservoir. (AU)