In this paper we propose a new workflow to perform Petrophysical Joint Inversion (PJI) of surface to surface seismic and Controlled Source ElectroMagnetic (CSEM) data, to recover reservoir properties (clay volume, porosity and saturation). Seismic and CSEM measurements provide independent physical measurements of subsurface that complement each other. In the case of well-logs, the basis of the PJI training dataset, taking advantage of such complementarity is straightforward. Indeed, elastic and electric measurements of earth properties sense the same earth volume at much the same scale. When applying the training dataset to the surface data derived geophysical attributes, the order of magnitude gap in between the scale at which those elastic and electric attributes represent the earth undermines dramatically PJI validity. Various CSEM inversion constraining methods (regularization breaks, prejudicing, use of an a priori model etc) help to reconcile seismic and CSEM resolution, but they are usually proven to be insufficient or inaccurate. In addition to these methods, we suggest adding a further downscaling step, so the recovered electric attribute resolution can be adequate with respect to the seismic one, hence fit for purpose. Such downscaling is designed to be consistent in electrical attribute space via transverse resistance within a rockphysics framework. The workflow will be demonstrated on a case study.
It is well known that no single geophysical method can provide a completepicture of the earth and its properties and recently integrated interpretationand joint inversion of multiple data types has become a much studied topic(Chen et al, 2007; Harris et al, 2009; Jegen et al, 2009; de Stephano et al,2011). The seismic method is in many situations the tool of choice: it isgeneral and widely applicable, and can provide detailed images of sub-surfacestructure and stratigraphy from which complex geological models can beconstructed. If seismic methods can provide the answer to the question ofinterest then this is undoubtedly the tool to use. However although seismicdata are extremely sensitive to the changes in lithology occurring at theboundaries between geological units, they are less sensitive to fluid changeswithin these units. This is because acoustic and elastic properties of theearth show only small changes when the fluid content or saturation is changed.These changes can in some circumstances be detected and used to provideinformation on fluid distribution. In other situations this is difficult orimpossible to do with certainty, and complementary geophysical methods must beemployed to meet the reservoir characterization goal.
In many situations electrical resistivity is driven by the properties anddistribution of fluids in the earth. Commercial hydrocarbon deposits may bemany times more resistive than surrounding lithologies. This change inresistivity caused by variations in fluid content and saturation can, inprinciple, be detected using CSEM tools (See Constable & Srnka 2007 for areview of CSEM technology). However when only CSEM data are considered,structural resolution is poor because of the diffusive nature of the EM fields,and the results can be ambiguous because the effect of an increase in porefluid resistivity cannot be distinguished from the effect of a decrease inporosity. The presence of frustrating resistors in the section (for exampletight carbonates, cemented sandstones or volcanics) can also complicate theinterpretation.
Well-log data provide a range of measurements, including both resistivity andacoustic/elastic properties as well as a range of further properties. Apetrophysicist analyzing this well log data will take all of these measurementsand integrate them together to provide an interpretation of the lithology andfluid properties. The resistivity measurement in particular provides keyinformation on the fluid content at the well bore. However such informationcannot provide any constraint on the variation of properties away from thewell, across a reservoir.
For any given geophysical question, the most robust answer will be obtained byusing the tool, or combination of tools best suited to the task, andintegrating the resulting data within a rock physics framework, to provide ashared earth model that is geologically reasonable, and consistent with each ofthe geophysical data types available. Careful integration of multiple datatypes can allow the strengths in one method to compensate for the weaknesses inanother.
Here we consider three data types: seismic, controlled source electromagnetic(CSEM), and well log data. The workflow applied is shown in figure 1. CSEM dataare first inverted to provide a measure of resistivity. Because of the poorstructural resolution of CSEM data taken in isolation, this inversion isconditioned with seismic structural information. From the results, thetransverse resistance (the vertically integrated resistivity), which is wellconstrained by the CSEM method, can be calculated within the intervals ofinterest.