Accelerating and Optimizing Oil and Gas Exploration Planning Using Quantum Inspired Classical Computing or Vector Annealing
D. Pathania, S. Momose, T. Nishimura, M. Ikuta · 2022
Summary Oil and Gas exploration or drill sequence planning is a difficult optimization problem which infeasible to be solved by classical computers today. They are called combinatorial optimization problems (or NPHard). Solving such challenge can yield tremendous benefits in terms of improved success ratio and rescued cost and resources required. These problems are expected to be solved by Quantum Computers (QC) called Quantum Annealing (QA). The current evolution of the quantum hardware or limited availability of actual qubits. This limitation makes the pure QA solution infeasible for solving large-scale real-world problems or large number of qubits. For overcoming limitation and simulating annealing, Vector Engine Accelerator (VE) has the capability of simulating 100K fully connected qubits per PCIe based card. QA works using quantum fluctuations. Quantum Simulated Annealing (SA) or Vector Annealing (VA) works simulating the quantum effect using meta-heuristic approach on a classical computer. VA on VE solution has advantage in comparison to other SA on classical computers is large number of qubits support and capability of accelerating the same. In the presentation we will be showcasing not only the capability to solve combinatorial optimization problem but also user can accelerate the performance and making a real-world applicable solution.