Digital Core Analysis: A Collaborative Cloud-Based Environment Leveraging High-Performance Computing

Digital Core Analysis: A Collaborative Cloud-based Environment

Leveraging High-Performance Computing

Finely resolved single and multi-phase pore-scale flow simulation has emerged as a complimentary technique to laboratory Routine and Special Core Analysis (RCAL/SCAL) methods. Digital core analysis is faster, given adequate computational resources, and provides detailed insight into the mechanics of oil displacement and recovery at the micro-scale, even for samples not suitable for RCAL/SCAL. Sensitivities to flow conditions and properties of the rock-fluids system can be explored in a self-consistent way without sample-to-sample error. However, the high-performance computing (HPC) environment required for the digital core analysis approach represents a potential barrier to entry due to infrastructure cost and IT support. Pre- and post-processing of the data can necessitate expert knowledge and/or training, complicating the workflow and creating a steep learning curve for new practitioners.

Here we present a fully automated, on-demand, cloud-based digital core analysis system that overcomes these entry barriers and makes a complex scientific computing application easily and readily accessible. From a web-based UI, the system allows users to upload pore-scale micro-CT or FIB-SEM images of rock samples, explore the pore space characteristics, and perform single and multi-phase lattice-Boltzmann simulations to obtain absolute and relative permeability curves. An example use case and results are presented for an operator leveraging this application for petrophysical property analysis of a sandstone rock sample. While the system carries out the highly complex algorithms, the user achieves all this with a few mouse clicks – expert supervision and manual parameter selection are avoided. Users can share the resulting information throughout their organization, from the field to remote managers, allowing unprecedented collaboration in evaluating and using core analysis results. The advantages of this cloud-based approach are not application specific; they represent a disruptive technology that can be replicated to other complex, computationally intensive workflows within and beyond the oil and gas industry. In this way, the digital core analysis system presented serves as an example of democratizing the power of high performance computing.