Digital Rocks: Emerging Technology to Business-Proven Capability

Abstract

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 170752, “Digital Rocks: Developing an Emerging Technology Through to a Proven Capability Deployed in the Business,” by J.T. Fredrich, D.L. Lakshtanov, N.M. Lane, E.B. Liu, C.S. Natarajan, D.M. Ni, and J.J. Toms, BP, prepared for the 2014 SPE Annual Technical Conference and Exhibition, Amsterdam, 27–29 October. The paper has not been peer reviewed. This paper describes the development of “digital-rocks” technology, in which high-resolution 3D image data are used in conjunction with advanced modeling and simulation methods to measure petrophysical rock properties. This technology has developed into a proven capability sanctioned for use in the operating assets of a large multinational oil company. Digital-rocks technology can improve evaluation of reservoir quality and quantification of hydrocarbons in place, and it can help inform the development of improved-recovery methods. Introduction The premise of the technology is to apply state-of-the-art high-resolution 3D imaging technologies to derive digital descriptions of reservoir rocks, typically at a resolution of approximately 1–5 Μm, or even lower for complex rocks with significant microporosity less than 1 Μm in dimension. These digital descriptions can be thought of as a numerical grid or mesh and, in conjunction with the appropriate models and numerical algorithms, can be used to perform massively parallel simulations of pore-scale processes of interest. These simulations can then be interpreted to derive macroscopic static and dynamic rock properties. Because the geometrically and topologically complex pore-scale architecture of the rock is captured in the 3D image and faithfully represented in the computational mesh, the numerical solution of the underlying physics is not compromised as long as the image is acquired with the requisite fidelity, and at a suitable resolution and over a representative elementary volume. In the field of computational physics, this general approach is known as direct numerical simulation (DNS). While DNS is often used to describe a solution method for problems in computational fluid dynamics, there exists an underlying generality and the same concept can be applied to other partial-differential equations (PDEs) of interest, thereby expanding application to various rock properties in addition to intrinsic permeability.