There is a potential for improving the reliability of standard core tests for seismic monitoring studies. A primary concern is to quantify and correct for core damage effects, which significantly enhance the stress dependency of wave velocities. Careful laboratory procedures and modeling efforts may reduce such effects. However, no simple procedure is currently available to eliminate this problem. The use of simplified laboratory test procedures, in particular application of an inappropriate effective stress principle, may lead to erroneous interpretations.
Time lapse (4D) seismics provides a potentially powerful tool to identify changes in a reservoir induced during production. This is accomplished by running repeated seismic surveys throughout the production period, looking for changes in the seismic response. Such changes can in principle be ascribed to several parameters, the most obvious being fluid saturation, pore pressure and temperature1,2. Thus, by monitoring the reservoir at various time steps during an enhanced oil recovery operation such as a water injection, one may identify non-flooded compartments within the reservoir. This information permits subsequent positioning of new production and injection wells or modification of the existing depletion strategy in a way that improves the total recovery of the reservoir significantly. During the last 5 years or so the number of commercial 4D seismic surveys has increased from less than 5 to around 25 per year. The cost of a reservoir monitoring project is in many places comparable to that of drilling a new well, and benefits have in many cases proven so large that most companies now consider it as a natural part of reservoir management.
There are, however, a number of factors that influence the success for such surveys, be it related to the reservoir itself in terms of depth, stresses, temperature and structural and compositional complexity, or to intrinsic reservoir properties like the rock and fluid properties at the given reservoir conditions. The success is also affected by the quality of the seismic acquisition parameters during the surveys, for instance the degree of repeatability between subsequent surveys3, as well as the final processing of the seismic data (see for instance Lumley et al4 for a technical risk summary). Due to this substantial variability, one should always perform a seismic monitoring feasibility study in advance to quantify to what extent expected production induced changes may be detectable or not from a planned seismic monitoring study. Such a study needs integrated input from a number of disciplines: After building a proper reservoir model, reservoir simulations have to be undertaken to produce relevant scenarios to be expected throughout production. Thereafter, these must be translated into corresponding seismic parameters from rock physical principles before, finally, seismic modeling can be undertaken for various acquisition geometries and subsequent processing alternatives can be tested out.
Traditionally, seismic monitoring parameters have been deduced from post-stack data through changes in the vertical P-wave reflection coefficient, expressed by the corresponding acoustic impedance ZP=?VP, where VP is the acoustic P-wave velocity and ? the density of mass. This has essentially allowed for inversion for only one effective reservoir parameter. Knowing that there may be concurrent changes in several parameters, this has made the interpretation of the seismics difficult. More recently, however, practical use of AVO data has been introduced5, enabling also the corresponding shear wave impedance ZS to be determined. This simultaneous determination of P- and S-wave impedances has allowed for distinction between changes in multiple reservoir properties like for instance both saturation and pore pressure, assuming that other parameters remain constant.