Cloud-Based Array Electromagnetics Contributing to Zero Carbon Footprint

Abstract

Abstract Fluid imaging technologies are used in a wide range of E&P applications. Among geophysical methods, electromagnetics (EM) determines subsurface resistivities and thus respond to fluid changes. On the path to zero CO2 footprint, the biggest potential for EM lies in monitoring geothermal, carbon capture utilization and storage (CCUS), and enhanced oil recovery (EOR) of hydrocarbon reservoirs. For EOR of hydrocarbon reservoirs, EM methods also increase the recovery factor. At the same time, usage of CO2 for flooding can help reaching zero carbon footprint faster. In geothermal applications EM is a standard geophysical method. Monitoring is often carried out in compliance with induced seismicity monitoring to better understand the fluid movement inside the reservoir – here we suggest adding EM. For carbon capture applications, only recently EM methods have become of interest because there is a strong resistivity contrast between CO2 saturated fluid and normal reservoir fluids. We designed a new EM acquisition architecture that combines novel technologies and addresses the need of calibrating surface and borehole data with each other. This is necessary to obtain reservoir scale parameters. We also add various borehole receivers to the system to improve image focus and resolution. Our array acquisition system applies multiple electromagnetic methods as well as microseismic in ONE layout. This reduces operational cost and provides synergy between the methods. In a production scenario, using multi-component EM allows resolving oil and water-bearing zones equally well, as well as obtaining fluid flow directions. The modular architecture allows a fit-for-purpose configuration tailored to specific exploration/monitoring targets (in terms of depth, frequency range, and sensitivity required). The entire system combines hardware with processing and 3D modeling/inversion software, streamlining the workflow for the different methods. Acquiring and interpreting in combination with artificial intelligence and Cloud-based data transmission and quality assurance achieves near real-time operations. The biggest value is in faster operations and making decisions at a time when they can impact acquisition data quality. We use a multi-layered Cloud solution, for acquisition, processing, and interpretation. This acceleration then opens new doors for the breakthrough of this technology from exploration to production and monitoring. It also allows the application envelope to be enlarged to much noisier environments where real time feedback allows for better noise compensation methods. Once all components are commercialized, this could become a real game changer by providing near real-time 3-dimensional subsurface images because of a reduction of operational cost and by reducing the carbon footprint per barrel produced.