Quantitative estimation of compaction and velocity changes using 4D impedance and traveltime changes

Abstract

In some hydrocarbon reservoirs, severe compaction of the reservoir rocks is observed. This compaction is caused by production, and it is often associated with changes in the overburden. Time‐lapse (or 4D) seismic data are used to monitor this compaction process. Since the compaction causes changes in both layer thickness and seismic velocities, it is crucial to distinguish between the two effects. Two new seismic methods for monitoring compacting reservoirs are introduced, one based on measured seismic prestack traveltime changes, and the other based on poststack traveltime and amplitude changes. In contrast to earlier methods, these methods do not require additional empirical relationships, such as, for instance, a velocity‐porosity relationship. The uncertainties in estimates for compaction and velocity change are expressed in terms of errors in the traveltime and amplitude measurements. These errors are directly related to the quality and repeatability of time‐lapse seismic data. For a reservoir at 3000‐m depth with 9 m of compaction, and assuming a 4D timeshift error of 0.5 ms at near offset and 2 ms at far offset, we find relative uncertainty in the compaction estimate of approximately 50–60% using traveltime information only.

Time-lapse full-waveform inversion with ocean-bottom-cable data: Application on Valhall field

“…Instead of analyzing small and large offsets separately as in Zadeh et al (2011), FWI naturally takes all types of waves into account, including diving waves, supercritical reflections, and multiscattered waves. The structural depth and velocity changes can be well-represented in FWI inverted models; therefore, separate analyses are not necessary, as in conventional time-lapse methods (Landrø and Stammeijer, 2004). In addition, FWI makes no assumption about the subsurface structures and involves less manual interaction.…”

“…This information needs to be transferred to reservoir properties by reservoir modeling (Lumley and Behrens, 1998). Quantitative 4D techniques are used to estimate reservoir compaction and velocity changes using time shift and time strain in the data (Landrø and Stammeijer, 2004;Zadeh et al, 2011). Amplitude variation with offset (AVO) analysis inverts partial-angle stacks for elastic impedance changes (Sarkar et al, 2003;Tatanova and Hatchell, 2012).…”

Analysis of time-lapse travel-time and amplitude changes to assess reservoir compartmentalization

“…In conventional time-lapse seismic processing, both the baseline and monitor observations are processed using identical workflows and, in many instances, the same velocity model (i.e., baseline model), as discussed in Landr¿ and Stammeijer (2004). When the subsurface velocity changes are small or only the near-offset data are used, the estimated time-lapse seismic travel-time shifts will be quantitatively close to the true model values (e.g., fractional ms error as shown in Figures 9 and 10).…”

“…Using a 1D expression to describe the travel-time difference due to geomechanical effects (equation 1, Landr¿ and Stammeijer 2004), Hatchel and Bourne (2005) and R¿ste, Stovas and Landr¿ (2005) propose a linearized relation to link changes in layer velocity and thickness using a dilation factor.…”

Using image warping for time-lapse image domain wavefield tomography

“…In some time-lapse seismic analysis, the time shift information is omitted because the monitor data or images are aligned with the baseline to compare the amplitudes. In other studies, time shifts picked at certain horizons are used to study the reservoir velocity changes or the strain field changes above the reservoir (Landrø and Stammeijer, 2004;Barkved and Kristiansen, 2005). However, these analyses are conducted on poststack data, which have already lost some information during the stacking process.…”