Reflectivity versus angle of incidence for wet (blue line) and 85% gas case (red line, left); normalized radial CSEM amplitude versus source-receiver distance for wet (base case) and 85% gas case (right). Note that the difference between the wet and gas-case CSEM amplitude ranges from a factor of five for shaly sand (orange line) to a factor of eight for clean sand (red line) at the maximum spacing of 32,810 ft (10,000 m). (Figures courtesy of OHM)

Lengthy adoption times for new technology have been the hallmark of the upstream oil and gas technology. With a few exceptions, it’s not unusual to see 15 to 20 years separation, or sometimes longer, between proof of concept and full commercial use of a given technology or method.

Controlled source electromagnetic (CSEM) surveying seems to have bucked this trend. As has been reported in many other articles, CSEM technology has enjoyed very rapid pick-up (from the original proof-of-concept survey offshore Angola in November 2000) and has become a mainstream exploration tool applied in a wide variety of exploration environments.

Over the past few years, Rock Solid Images (a wholly owned subsidiary of OHM) has been quietly working with CSEM data with particular emphasis on integration of CSEM with surface seismic. What have we learned?

You still need seismic!

Despite some claims to the contrary, CSEM data is not an alternative to seismic data – it’s not a magic bullet that can unambiguously detect hydrocarbons. Non-uniqueness is an inherent issue with any surface-based geophysical measurement of the subsurface; there will be many different earth-models we can consider that will provide the same CSEM (or indeed seismic) response.

The key point to remember about CSEM is that we are exploring the subsurface using an electrical system rather than acoustic-based, with fundamentally different physics controlling the response and the sensitivity to rock and fluid properties. Seismic and CSEM data will respond very differently to a given structure. In some cases the seismic information may provide a more useful dataset to meet a particular exploration objective. In other cases it will be CSEM.

But in all cases, the combination of the two methods will be the most valuable since we can exploit the strengths of each to gain a more complete understanding of the earth.

Uncertainties

CSEM is sensitive to changes in resistivity in the subsurface. If a CSEM dataset has been acquired and processed appropriately, a CSEM anomaly is indicative of the presence of a resistive layer or body in the subsurface. Oil and gas accumulations in the subsurface can cause such increases in resistivity. However, other features such as volcanics, salt stringers or tight carbonates may produce a similar anomaly. In many situations these ambiguities cannot be resolved on the basis of this single data type, and further information is required.

The same can be said of seismic: In many situations the interpretation of seismic data alone can result in similar ambiguities. Geophysicists know only too well to be wary of interpreting bright-spot anomalies without a thorough understanding of the rock physics behind these features.

Modeling is the key

When planning a seismic acquisition program, it’s important to understand parameters such as depth to target, overall structural complexity and illumination angles needed to image the area(s) of interest. Inappropriate seismic acquisition parameters can be costly but usually still lead to a usable, if sub-optimal, dataset.

Careful planning of CSEM acquisition campaigns is critical. An inappropriate choice of acquisition parameters such as source frequencies and receiver locations may result in a dataset that simply cannot provide any useful information. Modeling is without doubt the key to a successful CSEM survey program; the more information we have regarding likely zones of interest, depths, lateral extent and bulk properties of reservoirs, the better job we can do in designing a fit-for-purpose CSEM program. Surveys must also be designed with acquisition parameters chosen to provide contingency for unexpected structures or features in the subsurface — the earth is often more complex in reality than we predict.

An integrated approach

To get the most out of geophysical data, we must integrate different methods to use the strengths and mitigate the weaknesses of each. The following well-based model example, taken from a Norwegian dataset, provides an excellent example of the power of integrating CSEM, seismic and wireline data.

The first figure shows the difference in seismic amplitude variations with azimuth (AVA) and CSEM normalized amplitude response between a water-wet reservoir and the same reservoir charged with 85% gas. As is readily apparent, there is a significant change in seismic and CSEM character between these two scenarios.

The second figure shows the same comparison between water and a non-commercial 30% gas case.

The differences between these two cases are striking. The seismic shows little change between the 80% and 30% case, whereas there is a very large change in the CSEM amplitude response.

In this zone seismic can distinguish a wet reservoir from gas-charged but cannot differentiate commercial gas from “fizz.” Not so for CSEM, which provides a clear distinction between commercial and non-commercial gas.

Is this an example, then, of where we don’t need seismic? Absolutely not. Seismic provides structural and stratigraphic detail that cannot be interpreted from CSEM, which has much poorer vertical resolution. In fact, this is a great example of the value that can be unlocked with a sensible combination of seismic and CSEM data.

The future

CSEM technology is maturing rapidly, but much work remains to be done. In response to suggestions from a number of our customers, OHM and Rock Solid Images launched the WISE industry-backed consortium to research and develop ways to better integrate seismic and CSEM data. WISE, an acronym for well-driven integration of seismic and EM, currently has six industry sponsors, including several major oil and gas players in the CSEM field.

WISE was launched in February of 2008 and already has released its first product, an integrated 1-D seismic and CSEM modeling system which allows for simultaneous modeling of both prestack seismic and CSEM data as a function of reservoir properties such as thickness, fluid type and saturation.

Combining disparate geophysical datasets is a logical step forward that is already proving its value in reducing exploration risk. By using CSEM in conjunction with advanced prestack seismic imaging and rock physics-driven inversion methods, we will be able to determine rock and fluid properties, and ultimately changes in these properties over time, with much greater confidence than is possible using traditional seismic-only methods.