Estimation of Reservoir Permeability Using Analogue Core Data for Green Field: Case Studies from Niger Delta

Abstract

Permeability is one of the most important parameters of reservoir rocks; it defines the capacity of rocks to transmit fluids in pore spaces. Permeability prediction is of extreme importance in deciding the field development strategy for green reservoirs. The reservoir rocks are made up of grains, cement and pore network. The pore network is made up of larger spaces, referred to as pores, which are connected by small spaces referred to as throats. The pore spaces control the amount of porosity, while the pore throats control the movement of fluids and the quantity of rock permeability. Generally, the sources of permeability measurements in green field are from core data, well test data and Nuclear Magnetic Resonance (NMR) data. However, core information, well test information and NMR information are usually very limited due to high cost of acquisition making justification usually difficult. The consequence is that we have very low ratio of cored to the total reservoirs in the Niger Delta. This paper discusses a methodology for accurately estimating permeability using analogue fields/reservoirs core data in green reservoirs. The main factors to consider in choosing a suitable analogue includes Facies classification, relative depth of the reservoirs, average porosity and histogram of the Gamma ray values between the subject and analogue reservoirs. This selection is usually an integrated effort between the teams Geologist and Petrophysicist. In this study, two fields were selected where permeability prediction was based on analogue core data. A robust Niger delta wide analogue selection process was applied first to identify the analogue field where core data exists. After selection of the analogue field, facies-wise poroperm transform was built. This poroperm transforms were then validated in one of the fields where real core measurements were available post study. This blind test with real core permeability data indicated an excellent match with analogue based permeability model. In the other field, the analogue based permeability was validated against NMR and mobility data acquired in some of the reservoirs. This workflow establishes the robustness of using existing analogue data to reduce the subsurface uncertainty and justify an integrated workflow of estimating permeability in the green field rather than acquiring a new data to support development decision.