--> ABSTRACT: Integrating Seismic, CSEM and Well Log Data for Reservoir Characterisation, by MacGregor, Lucy; #90135 (2011)

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Integrating Seismic, CSEM and Well Log Data for Reservoir Characterisation

MacGregor, Lucy 1
(1)Rock Solid Images, plc, Aberdeen, United Kingdom.

Well logs provide a high resolution measurement of the properties of a reservoir and the surrounding strata, however properties can only be determined in a small area local to the well. Often measurements of reservoir properties across the extent of a field are desirable for reservoir management or production optimization. Remote geophysical measurements are therefore required. Seismic data are most commonly used for this purpose, however in recent years CSEM methods, which measure the resistivity structure of the seafloor have also been widely applied. CSEM methods use a high powered source to transmit low frequency signals through the earth to an array of receivers. By interpreting the received signals using forward modelling and inversion approaches, the resistivity structure of the seafloor can be determined. In many situations electrical resistivity is driven by the properties and distribution of fluids in the earth. Resistivity well logs often show that commercial hydrocarbon deposits may be many times more resistive than surrounding lithologies. In principal such variations should be readily detected using CSEM tools. In contrast, seismic data are sensitive to boundaries between lithologic units but are less sensitive to fluid changes within these units. Given high quality seismic and well data and sophisticated seismic inversion and rock physics tools, we can sometimes relate these seismic changes to saturation effects. Nevertheless, the change in resistivity caused by variations in saturation should be much easier to detect. However, despite the increased sensitivity of resistivity data over seismic for the determination of saturation, there are two inherent challenges to interpreting CSEM data. Firstly, the structural resolution of CSEM data is poor. Secondly, the cause of resistivity anomalies (particularly high resistivity features) cannot be uniquely linked to the presence of hydrocarbons in the subsurface when taken in isolation. It is clear that a careful combination of all three data types can supply information that is not available, or is unreliable from any one data type alone. By integrating complementary sources of information and exploiting the strengths of each, estimates of rock and fluid properties such as gas saturation and porosity can be obtained with greater confidence than from any one data type alone.

 

AAPG Search and Discovery Article #90135©2011 AAPG International Conference and Exhibition, Milan, Italy, 23-26 October 2011.