Modelling data-driven CO2 sequestration using distributed HPC cyberinfrastructure

In this paper we lay out the computational challenges involved in effectively simulating complex phenomena such as sequestering CO2 in oil and gas reservoirs. The challenges arise at multiple levels: (i) the computational complexity of simulating the fundamental processes; (ii) the resource requirements of the computationally demanding simulations; (iii) the need for integrating real-time data (intensive) and computationally intensive simulations; (iv) and the need to implement all of these in a robust, scalable and extensible approach. We will outline the architecture and implementation of the solution we develop in response to these requirements, and discuss results to validate claims that our solution scales to effectively solve desired problem sizes and thus provides the capability to generate novel scientific insight.