There has been great promise in the controlled-source electromagnetic (CSEM) method since its inception in 2002, following a field trial offshore Angola. The subsequent emergence of three contractors, OHM Ltd in the UK, EMGS in Norway, and AGO in the US (now WG-EM), was fueled by that promise and led to large market capitalizations and aggressive marketing of the technology. However, adoption was slower than predicted, and in late 2009 the industry is in a much more humbling place. Nine years on from the first proof-of-concept survey, it is instructive to reflect on the reasons for the slow adoption of CSEM methods.

Originally promoted as an exploration tool that could be used ahead or instead of seismic acquisition, the method has been applied globally in a variety of geological settings with mixed results. When CSEM data are analyzed in isolation, the interpretation can be fraught with uncertainty. We are finding that CSEM is at its most powerful when interpreted within a geological framework alongside other geophysical and petrophysical data, including seismic and well log information. As a result, we believe that CSEM is applicable and perhaps even better suited in appraisal and monitoring settings.

Traps and pitfalls in CSEM interpretation

The left image is a traditional CSEM output that maps resistivity without regard to structure. The right image includes well and seismic data to map saturation within reservoir boundaries. (Images courtesy of OHM Rock Solid Images)


In many situations electrical resistivity is driven by the properties and distribution of fluids in the earth. Commercial hydrocarbon deposits may be many times more resistive than surrounding lithologies and therefore can be detected using CSEM tools. In contrast, seismic data are sensitive to boundaries between lithologic units but are less sensitive to fluid changes within these units. Given high-quality seismic and well data and sophisticated seismic inversion and rock physics tools, we can sometimes relate these seismic changes to saturation effects. Nevertheless, the change in resistivity caused by variations in saturation should be much easier to detect.

However, despite the increased sensitivity of resistivity data over seismic for the determination of saturation, there are two inherent challenges to interpreting CSEM data. First, the structural resolution of CSEM data is poor. Second, the cause of resistivity anomalies (particularly high-resistivity features) cannot be uniquely linked to the presence of hydrocarbons in the subsurface when taken in isolation. In many situations these are equally likely to be caused by other high-resistivity material (for example, tight carbonates, salt, or volcanics). Both of these limitations must be addressed when considering the applicability of CSEM to answer a geophysical question and, as far as possible, mitigated by the interpretation approach adopted.

CSEM data can, of course, be interpreted in isolation, and if there were no seismic data or wells in the vicinity of the CSEM dataset (for example, if a survey were performed in a frontier area), then this would be necessary. However, with no constraints on this interpretation, the result will suffer from the non-uniqueness and ambiguity which blight unconstrained interpretation approaches. Although resistivity is imaged, the poor structural resolution of the method means that such images are diffuse and difficult to interpret. The uncertainty in the depth of features is large, so they cannot be unambiguously attributed to a particular stratum. If there are multiple resistive features, these cannot be easily separated, and small resistive bodies are likely to be lost or smoothed into surrounding strata. Even assuming that localized resistivity anomalies can be found, the cause of these anomalies cannot be unambiguously linked to the presence of hydrocarbon.

Given the level of uncertainty and non-uniqueness that exists in an unconstrained interpretation when considered in isolation, the question arises: is it appropriate to perform CSEM surveys where there is neither seismic nor well control? The answer to this question is almost certainly no if the objective of the survey is to de-risk an exploration program.

In the presence of seismic and well information, the question that we are trying to answer with the CSEM data becomes significantly better posed. The question is no longer one addressed at finding a reservoir but rather one of determining the content of a defined structure. Using seismic information the reservoir structure is known (but potentially not its content or extent), and we have independent constraints on the surrounding strata within which it is embedded. This is therefore a constrained interpretation problem and one that the CSEM data are in a much better position to answer.

The uncertainty in the CSEM interpretation result will depend on how comprehensive a background model can be constructed. For example, in frontier areas where only sparse 2-D seismic data are available, it may be possible to identify regions of elevated resistivity; however, without well log information the risk attached to interpreting these as hydrocarbons remains high. In contrast, in producing fields where a detailed background model can be constructed from existing seismic, well, and production data, it will be possible to identify with much more certainty the fluid saturation and changes in this through time.

Where does CSEM fit?
A matrix of CSEM interpretation risk and value in different stages within the upstream oilfield lifecycle. The highest value to be gained from CSEM is in the appraisal and monitoring stages.


Like all remote sensing techniques, CSEM has strengths and limitations. CSEM can be applied to any stage of the upstream oilfield lifecycle. Take the following settings and questions often asked at these stages:
• Frontier exploration: What is the structure in this area?
• Exploration: What is the
resistivity within the seismically defined structure?
• Appraisal: In a field with established reservoir properties, how do they vary and what is the best development strategy?
• Monitoring: How do reservoir properties vary across the field and through time?

Using the right tool to answer the problem at hand is key. Seismic is exceptional at defining structure, stratigraphy, and (usually) lithology but struggles with fluid content and saturation. CSEM measures resistivity and is exceptional at determining fluid saturation (previously only reliably determined from well data) but has difficulty with determining structure.

If the goal in applying technology is to achieve the lowest interpretation uncertainty and highest value, then tools must be targeted to the stage at which they can offer the greatest benefit. For seismic methods, frontier exploration is the area of maximum impact where structure over large areas can be imaged. However, CSEM, with its sensitivity to fluid saturation, is likely to add the greatest value in the appraisal and monitoring stages, where well and seismic data can be used to constrain the interpretation.

OHM recently completed a two-year research study in collaboration with BP and funded by the UK’s Technology Strategy Board to examine CSEM’s suitability in appraisal and monitoring.

A complex 3-D channel structure was used as the background model, and the example showed that CSEM can be used to map changes in fluid properties in repeatable surveys without the need for permanent installations. The key to this successful trial was a truly integrated approach using all available geophysical and petrophysical datasets and using rock physics as the glue holding the different methods together.

The CSEM industry is dealing with the ramifications of dramatic growth and impressive technological advances, unfortunately tempered by some disappointments. We believe that CSEM is an integral component in achieving hydrocarbon exploration and development success; however, for the method to achieve its potential, it must be used carefully within an integrated geophysical framework.