An electromagnetic (EM) geophysical survey using Controlled Source Electromagnetic (CSEM) methods was conducted in North Dakota, USA, to evaluate its feasibility for monitoring subsurface CO2 fluid plumes. This study assesses the advantages, constraints, and necessary enhancements of both passive and active electromagnetic techniques in the context of carbon capture and storage (CCS). Surface log-scale resolution was successfully achieved, demonstrating the method's capability to delineate fluid plume boundaries and estimate fluid volumes with high accuracy. These findings underscore CSEM's ability to detect subtle resistivity changes associated with CO2 saturation, an essential factor in monitoring fluid migration and ensuring storage integrity. A detailed petrophysical analysis supported the construction of a robust 3D anisotropic model, which accounted for heterogeneities in reservoir properties and included local noise assessments to optimize survey parameters and data quality. Integrating magnetic and electric field measurements proved crucial in enhancing spatial resolution and sensitivity to subsurface changes, facilitating precise characterization of geological formations and fluid distributions. Results confirmed the effectiveness of this integrative geophysical approach for dynamic reservoir monitoring, enabling time-lapse (4D) imaging to track plume evolution over time. The promising outcomes suggest significant potential for CSEM in ongoing and planned CO2 storage projects, particularly for verifying containment, detecting leakage pathways, and informing injection strategies. Furthermore, the techniques and insights gained from this study hold broader implications for monitoring other subsurface energy storage systems, including underground hydrogen storage, recharge aquifers, and even geothermal reservoir development. As global interest in subsurface storage technologies grows, advanced EM methods like CSEM are poised to be pivotal in supporting sustainable and secure energy transition initiatives.

Summary Carbon Capture, Utilisation, and Storage (CCUS) is a pillar of the energy transition. Two key technical elements are CO2 containment (seal integrity) and storage volumes (dynamic fluid plume) requiring geophysical monitoring. Over the past years, we carried out various electromagnetic surface monitoring surveys. When using the right workflow we can obtain surface data that is reconciled to borehole log scale. This makes the data certifiable in that context. For one application, the storage reservoir is a saline aquifer, we used Controlled Source ElectroMagnetics (CSEM) combined with magnetotellurics (MT) to obtain the background geologic structure. It included a high-power CSEM transmitter (200 KVA) and multi-component receivers to see resistive and conductive strata. Presently, we prepare for CO2 to be stored in basalt formation, where it solidifies. When CO2 is injected into basalt, it is first gaseous or liquid phase (pressure dependent) which causes a reduction in resistivity of the basalt reservoir followed by a strong resistivity increase when it solidifies. Another application is to contain CO2 under hydrocarbon reservoirs associated with salt dome provinces. We verified CSEM imaging over various salt domes to image the reservoir boundaries accurately.

The Controlled-Source Electromagnetic (CSEM) method is one of the electromagnetic methods utilized in geophysical exploration. This method provides a subsurface image through the resistivity anomalies of materials encountered by electromagnetic waves. The research area is located near a major city, resulting in high electromagnetic noise. Electromagnetic noise can be categorized into two types of the noise namely periodic noise and sporadic noise. Eliminating noise is a crucial objective to enhance data quality, as it can introduce uncertainty into interpretations. Three noise removal techniques are employed: pre-stack to filter the harmonic noise, stacking to remove the sporadic noise, and post-stack for smoothing. The CSEM data used consists of signals in the time domain with a 10-second period and a 50% duty cycle. The results of applying these noise removal techniques indicate that all three methods are highly effective in noise reduction. The pre-stack technique can remove periodic noise, while sporadic noise is addressed by the stacking technique, and signal smoothing can be achieved using the poststack technique.

The Controlled-Source ElectroMagnetic (CSEM) method provides crucial information about reservoir fluids and their spatial distribution. Carbon dioxide (CO2) storage, enhanced oil recovery (EOR), geothermal exploration, and lithium exploration are ideal applications for the CSEM method. The versatility of CSEM permits its customization to specific reservoir objectives by selecting the appropriate components of a multi-component system. To effectively tailor the CSEM approach, it is essential to determine whether the primary target reservoir is resistive or conductive. This task is relatively straightforward in CO2 monitoring, where the injected fluid is resistive. However, for scenarios involving brine-saturated (water-wet) or oil-wet (carbon capture, utilization, and storage—CCUS) reservoirs, consideration must also be given to conductive reservoir components. The optimization of data acquisition before the survey involves analyzing target parameters and the sensitivity of multi-component CSEM. This optimization process typically includes on-site noise measurements and 3D anisotropic modeling. Based on our experience, subsequent surveys tend to proceed smoothly, yielding robust measurements that align with scientific objectives. Other critical aspects to be considered are using magnetotelluric (MT) measurements to define the overall background resistivities and integrating real-time quality assurance during data acquisition with 3D modeling. This integration allows the fine tuning of acquisition parameters such as acquisition time and necessary repeats. As a result, data can be examined in real-time to assess subsurface information content while the acquisition is ongoing. Consequently, high-quality data sets are usually obtained for subsequent processing and initial interpretation with minimal user intervention. The implementation of sensitivity analysis during the inversion process plays a pivotal role in ensuring that the acquired data accurately respond to the target reservoirs’ expected depth range. To elucidate these concepts, we present an illustrative example from a CO2 storage site in North Dakota, USA, wherein the long-offset transient electromagnetic method (LOTEM), a variation of the CSEM method, and the MT method were utilized. This example showcases how surface measurements attain appropriately upscaled log-scale sensitivity. Furthermore, the sensitivity of the CSEM and MT methods was examined in other case histories, where the target reservoirs exhibited conductive properties, such as those encountered in enhanced oil recovery (EOR), geothermal, and lithium exploration applications. The same equipment specifications were utilized for CSEM and MT surveys across all case studies.

In carbon capture, utilization, and storage (CCUS) monitoring, dynamic plume monitoring and reservoir seal are key issues. Plume monitoring is best addressed with electromagnetics (sensitive to the resistivity contrast) and reservoir leakage with microseismics. A case history from North Dakota illustrates how we can tie surface-controlled source electromagnetic (CSEM) measurements to the three-dimensional (3D) anisotropic models derived from the available logs. This allows us to certify baseline measurements within the context of the borehole information. The key to this workflow is to derive a 3D anisotropic model from the logs that include all the log responses and lithology. An initial 3D modeling feasibility has in-field noise measurements to determine the best survey operational parameters based on expected fluid substitution models and noise levels. For the acquisition, careful instrument calibration and verification of all acquisition parameters are essential. Concurrent with the acquisition, a near-real-time quality assurance is carried out, which includes the results in a feedback verification loop to influence the data quality of the acquisition positively. With this process, we are able to define the length of acquisition time that yields sufficiently good data quality that can then be used for unsupervised inversion. The only influencing component in the inversion is the data weights derived from the repeated measurements (stacking weight). The resulting sensitivities show us that the data are sensitive in our case history (North Dakota) to a depth of 3,000 m. We carried out magnetotelluric and CSEM measurements. All data are consistent and match the 3D response of the anisotropic electrical log as well as the seismic section available in the area. The entire process is data-driven with minimum human interaction or inclusion of model assumptions. Achieving log scale resolution from surface measurements is a significant breakthrough, and thus, we are able to verify baseline measurement before we actually do the repeat measurement and, based on the results, further fine-tune the repeat survey.

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.

We are proposing to use and array acquisition system that can be used for applying in a single layout multiple electromagnetic methods as well microseismics. It reduces greatly operational cost and provides synergy between the methods. For hydrocarbon exploration, resolve either reservoirs fluid directly or the boundaries to the host rock. Over the past decade, we have optimized a new generation of electromagnetic hardware/software that can be used for land, marine and borehole applications. Optimization includes target resistivity and choice of component/sensors. The system uses a seismic-like architecture with nodes, each of which can be expanded with sub-arrays For hydrocarbon applications, the independent node concept is more efficient. The deployed entire system includes for the different methods processing and 3D inversion software. In India, this could be a very useful system also for sub-basalt imaging in Deccan Trap exploration.

Electromagnetic measurements can significantly contribute to imaging and monitoring of the reservoir fluid movement for hydrocarbon, geothermal, and CO2 sequestration scenarios. Among electromagnetic measurements, passive methods such as magnetotellurics (MT) give a good overview picture while controlled source electromagnetics (CSEM) addresses more details of the flood front location. Since Earth’s resistivities vary over several orders of magnitude, adopting the methodology to the target resistivity is important. For conductive targets, we usually use magnetic fields and for resistive targets the electric fields (but not exclusively). Using field data from hydrocarbon and CO2 applications, we illustrate the importance of a workflow and adaption to the target on hand. Verifying the geophysical acquisition and processing steps with 3D modeling and checking them against a 3D anisotropic log-derived model maintains confidence in the workflow and minimizes the influence on the data. This allows us to predict data validity and to certify the data with respect to the borehole logs.

During the energy transition, geophysics will need to focus on novel green energy applications and to reduce the carbon footprint of hydrocarbon production. For both reservoir, monitoring is important, in particular dynamic monitoring of reservoir fluids. For renewable energies such as geothermal, electromagnetics has always been the geophysical ‘work horse’, while mostly microseismic has been used for monitoring. For hydrocarbon reservoirs, added value toward ZERO carbon footprint is obtained by increasing the recovery factor by of 30-40 % and thus reducing the cost/carbon emission per produced barrel. In addition, CO2 is sequestered in brine saturated reservoirs and also needs to be monitored. We are addressing the fluid monitoring issue here for electromagnetics and are reviewing how hardware, methodology and application are interlinked to build a complete system. Various applications and case histories where the results can be verified by borehole logs support this. The key issue is that our measurement need to respond to geologic realistic Earth formations which are, generally speaking, anisotropic. We direct the entire design of the system in solving that problem with direc-tional sensitive measurements. Next, when we want to monitor reservoir change we require a repeatability and accuracy hereto not necessary. By carefully controlling the entire hardware design from sensor to applications stage this can be achieved and we can obtain log scale resolution from surface measurement which was hereto not possible.

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.

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.

Focusing geophysics to improve recovery factor of hydrocarbon reservoirs adds value and contributes toward ZERO carbon footprint by increasing the recovery factor by of 30-40 % and thus reducing the cost/carbon emission per produced barrel. Thus, the Enhanced Oil Recovery (EOR) market is expected to grow more than 3.5% annually. This will be even more fueled by the Green-House-Gas (GHG) reduction and subsequent CO2 injection into the reservoirs as they are being produced. Presently, geophysics only ac-counts for a small percentage of this market, thus its growth is inevitable since more deterministic observation lead higher operating efficiency. Imaging the fluids (hydro-carbon, water, and CO2) is a key component to optimized production and injection. We designed a novel electromagnetic (EM) acquisition system that combines mul-ti-physics fluid imaging and acquires surface and borehole data with high fidelity. Borehole calibration is needed to upscale reservoir data and parameters to measurement scale. Multiple electromagnetic methods are used as well as microseismics in one layout for Exploration and Production (E & P) problems. Multi-components in electromagnetics allows resolving oil and water-bearing zones equally well while achieving the best ac-curacy suitable for repeat measurements. Because sedimentary basins are intrinsically anisotropic, considering 3-dimensional anisotropy is essential from measurement and 3D modeling viewpoint. Thus, the results have the better subsurface images. Here, we combine hardware design, methodology, 3D modeling, processing, and interpretations into an integrated technology and demonstrate the success with verifiable case histories.

The North Dakota CarbonSAFE (Carbon Storage Assurance Facility Enterprise) project is part of the U.S. Department of Energy initiative to develop geologic storage sites to store 50+ million metric tons of carbon dioxide (CO2) from industrial sources. Geophysical methods are key for characterizing the geologic formations to store CO2 and monitor the injected CO2 over time to ensure containment. In the integrated multimeasurement geophysical approach considered for this project, it is expected that the controlledsource electromagnetic (CSEM) method is a strong contributor to mapping the CO2 movement. A feasibility study of the CSEM method, including 1D and 3D modeling and a field noise test, was conducted to determine its effectiveness in monitoring CO2 in the Broom Creek and Deadwood Formations. The study results demonstrate that the CSEM method can be used for CO2 storage monitoring in the study area. Preliminary inversion results of magnetotelluric (MT) and CSEM field data confirm the quality of the anisotropic model developed in this study.

Fluid imaging is one of the key geophysical technologies for the energy industry during energy transition to zero footprint. We propose better Cloud-based fluid distribution imaging to allow better, more optimized production, thus reducing carbon dioxide (CO2) footprint per barrel produced. For CO2 storage, the location knowledge of the stored fluids is mandatory. Electromagnetics is the preferred way to image reservoir fluids due to its strong coupling to the fluid resistivity. Unfortunately, acquiring and interpreting the data takes too long to contribute significantly to cost optimization of field operations. Using artificial intelligence and Cloud based data acquisition we can reduce the operational feedback to near real time and even, for the interpretation, to close to 24 h. This then opens new doors for the breakthrough of this technology from exploration to production and monitoring. It allows the application envelope to be enlarged to much noisier environments where real time acquisition can be optimized based on the acquired data. Once all components are commercialized, the full implementation could become a real game changer by providing near real time 3-dimensional subsurface images in support of the energy transition.

Exploration for hydrocarbon is often difficult when the overlaying strata is of high seismic velocity as it is for basalt, salt and carbonates. Many the world reservoirs are in carbonates. Mapping the reservoir laterally is thus difficult and developing carbonate reservoirs is expensive. We propose to use controlled source electromagnetic (CSEM) method to image the fluid better. In SE Asia commonly magnetotellurics, a passive method, is being used [1], but they are less sensitive to deep subsurface resistivity variations as CSEM. Pioneering work with CSEM was done in the 1980s in Australia and Europe [2] where CSEM was used to map resistive reservoirs / carbonates. Since then, the equipment and modeling methods have significantly improved, and the problem is addressed more cost effective thus reducing exploration cost by several fold. Applying a new differential measurement methodology and using 3-dimensioanal (3D) anisotropic model derived from well logs and 3D modeling we are able remove near surface anomalies and illuminate the deep the reservoir target and its lateral variations. Thus, we have a cost-effective solution for many exploration and production problems associated with carbonates.

Summary In the present energy transition phase, we must decrease the carbon dioxide footprint of indispensable hydrocarbon energies worldwide, and increase the usage of renewable energies, such as geothermal energy. The increasing interest in carbon dioxide storage monitoring and geothermal exploration for a cleaner low-carbon energy future make passive and active electromagnetic (EM) instrumentation essential technologies to support the reduction of greenhouse gas emissions during the energy transition phase. Passive EM methods, such as AMT (audiomagnetotellurics) and MT (magnetotellurics), employ natural energy as incoming plane waves as the source recorded by receivers that measure the magnetic and electric fields. Active EM methods, so-called controlled-source electromagnetic (CSEM) methods, require a high-power transmitter that generates artificial EM fields with prescribed signal characteristics and an array of receivers that measure the magnetic and electric fields. The Long-offset transient electromagnetic (LOTEM), a type of CSEM method and AMT and MT instrumentation, can monitor fluids' injection and propagation patterns in a carbon-storing formation or a geothermal producing field. These methods are also adequate for geothermal exploration.