Horizontal and Vertical Permeability Determination in Clean and Shaly Reservoirs Using In-Situ Measurements

Abstract

Abstract Measurements of reservoir rock properties are a difficult task. These rock properties usually involve costly coring programs plus extensive laboratory efforts. An alternate method to estimate these rock properties is using well-logging methods, which represent significant technical as well as economic advantage. The purpose of this study is to enhance reservoir description of clean and shaly formations in both vertical and horizontal directions using well-logging data. A new approch has been developed for estimating the J-function in clean/shaly heterogeneous reservoirs. This newly developed correlation has been applied to field data, resulting in good matching. Based on leverett J-function and the new proposed approach for estimating J-function, a new correlation for estimating absolute permeability in the transitions zones has been developed. An investigation of permeability, porosity, and irreducible water saturation relationships leads to develop other two correlations in terms of cementation exponent, m, and saturation exponent, n, for estimating absolute permeability in the irreducible water saturation zones from well-logging data. The feasibility of evaluating permeability distribution of a heterogeneous formation utilizing geophysical well logs has also been investigated, Ben kahla field in Algeria has been selected as a study area. A methodology has been introduced for estimating permeability profile using core and geophysical well log data. Several vertical permeability relationships were obtained as a function of horizontal permeability, hydraulic mean radius, grain size, and the amount and/or type of shale. A procedure for determining vertical permeability from well log data is presented. The field data shows that the permeability correlation for predicting vertical and horizontal permeability can be established for a specific reservoir by using core permeability and well log data.