Only by accessing a variety of different data sources and technologies that a complete picture of the subsurface and its economic potential are developed.
Resistivity is an important rock property for hydrocarbon exploration since hydrocarbon charged reservoirs are characterized by high resistivity. Furthermore, structures that can be difficult to image reliably with seismic, like salt, basalt and basement, are typically associated with a high resistivity contrast, making EM methods an excellent complementary measurement to seismic for structural imaging and geological model building. EM methods are widely used in the onshore mining industry and are expected to play a leading role in the emerging marine mineral exploration industry.
CSEM has applications in all stages of the exploration cycle from the early phases of regional exploration and lead identification through prospect maturation and appraisal of discoveries.
CSEM data are independent from and complementary to seismic data. Integration of CSEM data with seismic and other geophysical and geological data can significantly improve the understanding of the subsurface. While 3D seismic is ideal for structural and sedimentary facies mapping, obtaining reliable information on reservoir fluids from seismic is difficult. Well failure analyses demonstrate that charge and seal are the most common failure mechanism in exploration wells. Additionally, hydrocarbon volume estimates are often difficult to predict and tend to be over estimated associated with a high uncertainty range.
CSEM data provides reliable information about the large-scale resistivity of the subsurface, which in a sedimentary basin is mainly driven by the porosity and permeability of the rocks and the conductivity of the fluid within them. Providing information about reservoir fluids is one of the key strengths of CSEM.
Porous reservoir rocks with high brine saturation are conductive. However, when the brine is replaced by hydrocarbons during the charging process, the reservoir rock will become more and more resistive. A reservoir rock with high hydrocarbon saturation will be highly resistive. Because of this resistivity behavior, CSEM data can distinguish highly saturated hydrocarbon reservoirs from low saturation and brine filled reservoirs. CSEM is therefore often used for de-risking of AVO and seismic amplitude driven prospects.
The presence or absence of a resistive anomaly impacts the prospect charge risk and the seal integrity risk, and by providing information on these elements of the petroleum system, CSEM brings an important piece to the prospect evaluation.
In addition, resistivity anomaly size and strength in the CSEM image provide valuable information on prospect area, hydrocarbon sand thickness, and saturation, which helps to assess prospect resources. EMGS has developed a quantitative workflow for integrating CSEM data in the prospect evaluation process. Key steps are CSEM sensitivity analysis including assessment of false-negative risk, a statistical approach for anomaly identification and size estimation, integration with seismic and well data, and a false-positive risk assessment (i.e. anomaly not fluid related).
Output of the workflow is an updated probability of success (PoS) and volume distribution based on the CSEM observations. Together these parameters form the basis for the probability of economic success (Pe).
Through downgrading and upgrading prospects in terms of probability of success and expected volumes, the portfolio becomes polarized, allowing for better informed drilling decisions. This ability of CSEM to polarize a portfolio of prospects was demonstrated on several large CSEM campaigns that EMGS acquired for Pemex in Mexico: