Determination of reservoir properties from the integration of CSEM, seismic, and well-log data
Peter Harris, Rock Solid Images, and Lucy MacGregor, Offshore Hydrocarbons Mapping, discuss the advantages in reservoir interpretation of integrating data from controlled source electromagnetic (CSEM) and seismic data, illustrated by an example from the Nuggets-1 gas reservoir in the UK Northern North Sea. The problem of remote characterization of reservoir properties is of significant economic importance to the hydrocarbon industry. For example, in exploration the ability to determine the gas saturation in an identified prospect would avoid the costly drilling of un-economic low saturation accumulations. During development and production, a detailed knowledge of the reservoir properties and geometry, and changes in these parameters through time, can aid optimization of well placement and enhance overall recovery rates. A range of geophysical techniques can be applied to this problem. Seismic data are commonly used to develop geological models of structure and stratigraphy. Amplitude variation with offset (AVO) and inversion for acoustic and elastic impedance may also be used to constrain reservoir properties such as elastic moduli and density. These can in turn be related to mineralogy, porosity, and fluid properties through rock physics relationships (for example, Mavko et al., 1998). However seismic data alone in many situations cannot give a complete picture of the reservoir. Ambiguities exist, for example, in AVO responses which may be caused either by fluid or lithological variations, and cannot be separated on the basis of the seismic data alone. The controlled source electromagnetic (CSEM) method is becoming widely used in the offshore hydrocarbon industry, and has been applied successfully in a variety of settings (see for example, Srnka et al., 2006; MacGregor et al., 2006; Moser et al., 2006). The CSEM method uses a high powered horizontal electric dipole to transmit a low frequency electromagnetic signal through the seafloor to an array of multi-com-ponent electromagnetic receivers. Variations in the received signal as the source is towed through the array of receivers are interpreted to provide the bulk electrical resistivity of the seafloor, through a combination of forward modelling, geophysical inversion, and imaging. The bulk resistivity of a porous rock is to a large degree controlled by the properties and distribution of fluids within it. Typical brine saturated sediments have a resistivity in the range 1-5 .m. Replacing the seawater with resistive hydrocarbon can result in an increase in the bulk resistivity of the formation by 1-2 orders of magnitude. CSEM sounding exploits this dramatic change in physical properties to distinguish water bearing formations from those containing hydrocarbons. However, as for seismic data, potential ambiguities exist in the interpretation of CSEM data. For example, tight limestones, volcanics, or salt bodies may also have high resistivity, and could give a CSEM response similar to that of a hydrocarbon reservoir. In addition, because of the diffusive nature of electromagnetic fields in the earth, the structural resolution is generally lower than that given by seismic data. Since the CSEM and seismic data are controlled by very different physical processes, it is clear that a careful combination of seismic and CSEM data, exploiting the strengths of each, can supply information which is not available or is unreliable from either type of data alone, thus reducing ambiguity and risk. A number of approaches to the integration of disparate data types have been proposed (e.g. Musil et al., 2003; Gallardo & Meju., 2004; Hoverston et al., 2006). Here we illustrate the advantages of an integrated interpretation using CSEM and seismic data collected on the Nuggets-1 gas reservoir.