OTC 23699

Integrating Seismic, CSEM and Well Log Data for Reservoir Characterisation Lucy MacGregor, RSI David Andreis, RSI

Copyright 2012, Offshore Technology Conference This paper was prepared for presentation at the Offshore Technology Conference held in Houston, Texas, USA, 30 April–3 May 2012. This paper was selected for presentation by an OTC program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Offshore Technology Conference and are subject to correction by the author(s). The material does not necessarily reflect any position of the Offshore Technology Conference, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Offshore Technology Conference is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of OTC copyright.

Abstract It is well known that no single geophysical method can provide a complete picture of the earth and its properties and recently integrated interpretation and 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 is general and widely applicable, and can provide detailed images of sub-surface structure and stratigraphy from which complex geological models can be constructed. If seismic methods can provide the answer to the question of interest then this is undoubtedly the tool to use. However although seismic data are extremely sensitive to the changes in lithology occurring at the boundaries between geological units, they are less sensitive to fluid changes within these units. This is because acoustic and elastic properties of the earth show only small changes when the fluid content or saturation is changed. These changes can in some circumstances be detected and used to provide information on fluid distribution. In other situations this is difficult or impossible to do with certainty, and complementary geophysical methods must be employed to meet the reservoir characterization goal. 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. This change in resistivity caused by variations in fluid content and saturation can, in principle, be detected using CSEM tools (See Constable & Srnka 2007 for a review of CSEM technology). However when only CSEM data are considered, structural resolution is poor !"#$%&"'()'*+"',-))%&-."'/$*%0"'()'*+"'12')-"3,&, and the results can be ambiguous because the effect of an increase in pore fluid resistivity cannot be distinguished from the effect of a decrease in porosity. The presence of frustrating resistors in the section (for example tight carbonates, cemented sandstones or volcanics) can also complicate the interpretation. Well-log data provide a range of measurements, including both resistivity and acoustic/elastic properties as well as a range of further properties. A petrophysicist analyzing this well log data will take all of these measurements and integrate them together to provide an interpretation of the lithology and fluid properties. The resistivity measurement in particular provides key information on the fluid content at the well bore. However such information cannot provide any constraint on the variation of properties away from the well, across a reservoir. For any given geophysical question, the most robust answer will be obtained by using the tool, or combination of tools best suited to the task, and integrating the resulting data within a rock physics framework, to provide a shared earth model that is geologically reasonable, and consistent with each of the geophysical data types available. Careful integration of multiple data types can allow the strengths in one method to compensate for the weaknesses in another. Here we consider three data types: seismic, controlled source electromagnetic (CSEM), and well log data. The workflow applied is shown in figure 1. CSEM data are first inverted to provide a measure of resistivity. Because of the poor structural resolution of CSEM data taken in isolation, this inversion is conditioned with seismic structural information. From the results, the transverse resistance (the vertically integrated resistivity), which is well constrained by the CSEM method, can be calculated within the intervals of interest.

2 OTC 23699

Seismic data are also inverted and calibrated using rock physics models derived from well log calibration to give a measure of the porosity of the target intervals. Using an appropriate rock physics relationship between resistivity, saturation and porosity (see for example Archie, 1942; Carcione et al, 2007; Han et al, 2011) and assuming 100% water saturation, the porosity sections can be transformed to an equivalent seismically derived resistivity section. Since this seismically derived transverse resistance takes into account variations in thickness and porosity, and assumed 100% water saturation, any deviation from this curve indicates a change in the resistivity of the pore fluids. Therefore by comparing the CSEM derived transverse resistance with the seismically derived value, areas containing resistive pore fluid, indicating hydrocarbon charge, can be isolated. The ultimate goal of a geophysical analysis is to find a constrained model of geology, lithology and fluid properties. To achieve this the earth can be interrogated with a number of tools. Each data type must be interpreted within an integrated framework so that the resulting shared earth model is consistent with all the data used in its construction. The field of data integration and shared earth modelling is large, and rapidly expanding with technology moving from qualitative to quantitative approaches. There are many challenges, for example combining different physical properties, using technologies that sense the earth at a range of different scales is not straightforward. However there are also many opportunities, if these challenges can be overcome, to improve the quality and constraints of geophysical information on which commercial decisions are based. References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

Figure 1: Workflow for the integrated analysis of seismic, CSEM and well log data. Seismic and CSEM data are inverted to provide impedance and resistivity properties respectively. Analysis of well log data provides calibrated rock physics models, which are used to convert these physical measurements into rock and fluid properties which when interpreted together give an indication of fluid distribution.

OTC 23699 3

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