For decommissioning wells in the central North Sea, evaluation of matrix permeability and risk of fracturing are in focus, but formation permeability, water saturation, and irreducible water saturation of reservoirs are additional critical petrophysical properties. These properties are derived from geophysical logging tool data by using physical and empirical equations. Leveraging a recent physical description of electrolytic conduction in porous media, we introduce a novel log interpretation workflow that highlights the added information from the petrophysical parameter m, traditionally termed the cementation exponent. This workflow is tested using well logging and laboratory data from two wells in the Danish North Sea: the water-saturated biogenic silica-bearing mudstone of the Sten-1 well and the water-wet hydrocarbon-bearing clay-rich chalk reservoir of the Boje-2C well. First, we characterize solid composition from cuttings or core samples and derive porosity in each well from neutron and density logs. Next, we measure specific surface area from cuttings or core samples and compare it with the novel surface area log derived using the electrical resistivity logs. This surface area log is based on the principle that for a given porosity, the conductivity of water-saturated rock decreases as the internal surface area increases due to increasing pore volume occupied by the adsorbed hydrated-ion layer, or bound water. From the surface area log, we estimate permeability using Kozeny’s equation. The new principle assumes Archie’s m-exponent for the movable water to be 1.5, and in both wells, we thus determine the movable water contributing to current flow and assign the remaining water to irreducible water, which then represents the adsorbed hydrated-ion layer. In the Boje-2C well, water saturation in hydrocarbon-bearing intervals was evaluated by assuming independent contributions from bound and bulk water conduction. This approach circumvents the need for defining Archie’s m- or n-exponents. To evaluate the risk of formation fracturing, our methodology involves the assessment of elastic properties using the iso-frame model, fluid substitution, Biot’s coefficient, and vertical elastic strain derived from sonic and density logs. These properties facilitate evaluation of structural integrity and identification of zones prone to pore collapse. The demonstrated workflow advances current reservoir characterization methodologies and addresses limitations in conventional petrophysical analysis.
Proestakis et al. (Wed,) studied this question.