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Fluid imaging technologies are used in a wide range of E&P applications. Among geophysical methods, electromagnetics (EM) determines subsurface resistivities and thus responds to fluid changes. On the path to zero carbon footprint, the most significant potential for EM lies in monitoring geothermal, carbon capture, utilization and storage (CCUS), and enhancing oil recovery (EOR). To optimize reservoir fluid monitoring, we calibrate surface measurements to well logs resulting in a 3D anisotropic model consistent with borehole data. This is done before and after depletion or injection to estimate a time-lapse reservoir response. As part of a carbon capture and storage project, we carried out baseline measurements and validated the surface EM data to the 3D anisotropic borehole model. The monitoring workflow for this project can easily be adapted for other applications to support the energy transition. From this, we learned that measurement accuracy requirements higher than 1 % because we are often imaging small anomalies. While there are always limits in acquisition set by industrial noise, we derived two ways of increasing the anomaly. One is by using, similar to a borehole focused logs, focusing methods in the acquisition setup. This is still subject to measurement accuracy limitations and limited to electric fields only. Another way is to add borehole sensors that increase the sensitivity by around a factor of 10. While shallow (around 50 m) is sufficient, they can be extended to deeper borehole sensors, bringing the measurements close to the anomaly and is thus the preferred approach. This, in combination with calibration back to the 3D anisotropic borehole log allows you to certify the data for its information content. This will give you quantifiable ways to derive risk values and significantly reduce acquisition and monitoring operations cost.

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We conducted an initial high-power CSEM (controlled-source electromagnetic method) survey in a coastal salt-flat area in the broader area of Half Moon Bay, in the southern part of Dammam Peninsula in the eastern province of Saudi Arabia. The primary purpose of this work was to verify the technology, but we were also able to detect and characterize potential economic brines in the study area. For a high-quality data acquisition, several transmitter–receiver configurations, different acquisition parameters, and passive and active EM data were collected, evaluated, processed, and interpreted to characterize the subsurface. The long-offset EM (LOTEM) and the focused-source EM (FSEM) were the optimum configurations due to the high-quality of the collected data. This is a starting point for using the CSEM method towards the O&G, geothermal, CO2 sequestration, groundwater, lithium brine, and other natural resources’ exploration and exploitation in the Gulf countries.

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.