Formation Pressure Prediction With Seismic Data From the Gulf of Mexico

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Abstract
Summary. in this study, we derive seismic formation-pressure logs using seismic data from offshore Louisiana to delineate the distribution of overpressured zones in the subsurface. The seismic-data processing consists of velocity modeling, wavelet processing, and seismic inversion. From the acoustic impedances produced by seismic inversion, we derive seismic velocity and density logs at every seismic trace location using a relationship between sonic velocities and acoustic impedances. We use these logs to compute the seismic formation-pressure logs vs. depth. Formation-pressure logs are calculated with the assumption that compressional velocity, mean density, and depth are proportional to formation pressure. These logs are constrained at every depth by estimated matrix and fluid compressional velocities (V max and V min). Vmax and Vmin are derived from porosity and sonic well-log information. Results include profiles of seismic-velocity, seismic-density, and formation-pressure logs for two intersecting seismic lines from off-shore Louisiana. Logs from one well are used to constrain the data processing. The seismic formation-pressure sections delineate a large region of overpressured shales in the subsurface. Introduction An important parameter in hydrocarbon exploration and exploitation is formation (or pore) pressure. In particular, detection of ab-normally high formation pressures, or overpressured zones, can provide valuable information for exploration and exploitation purposes. High formation pressures are common in the Gulf of Mexico. Overpressured sediments are generally caused by a sequence of events wherein water becomes trapped by faults or nonpermeable barriers in sediments at depths where, otherwise, the water would have been forced out by normal increases in overburden pressure. Abnormal fluid pressure is also caused by the release of water into the pore system during clay diagenesis (smectite/illite transformation) and other mechanisms. High formation pressures cause major changes in subsurface-rock parameters. In overpressured shales (which contain pressured water), seismic velocity and density are lower and porosity is higher than if the pressured water had been able to escape. Detection of overpressured sediments can contribute to the overall analysis of a basin's hydrocarbon potential. Abnormal pressures exert partial control on the type and quantity of hydrocarbons accumulated because pressure potential determines the direction of fluid flow and overpressuring partly controls the geometry of growth faults and related folds in basins where shale structures dominate. In the area of hydrocarbon exploitation, knowledge of formation-pressure distribution can aid in conducting safe, efficient drilling operations. In this study, such techniques as velocity modeling, seismic wavelet deconvolution, and inversion are incorporated to derive velocity and density logs more accurately from seismic data in both time and depth domains. [In this paper, seismically derived "logs" refers to a derived section where each output trace (log) was generated from one seismic trace of the original seismic section.] These seismically derived velocity and density logs, referred to simply as seismic velocity and density logs, are used to compute the final desired output-seismic formation-pressure logs. Seismic-Data-Processing Procedure Several key processing steps must be done before seismic formation pressure can be estimated. The accuracy of the processing results is vital to ensure reliable formation-pressure estimates. The key processing steps include velocity modeling, well-log processing, postmigration-wavelet processing, and seismic inversion. Fig. 1 illustrates the processing sequence. Velocity Modeling. It is well known that when complex velocity fields are present, estimated processing and parameter results that depend on accurate velocity measurements may be degraded. Velocity-dependent processes include migration, seismic inversion (owing to the low-frequency velocity component), and finally seismic formation-pressure estimation. In this study, velocity modeling is performed with inverse-normal-incidence-ray tracing (Fig. 2). The normal moveout velocities constitute the main input, along with horizon data that describe the primary reflections on the premigrated seismic section. As a result of velocity modeling, root-mean-square (RMS) velocities are obtained in migrated and unmigrated space for subsequent seismic inversion and migration, respectively. The data used in this study show overpressured conditions, evident in velocity scans, as anomalously low-velocity zones. A particular characteristic of overpressured conditions in the velocity scans is the absence of coherent events inside these low-velocity zones. The corrected (by modeling) velocities show the overpressured zones to be quite localized. At this stage, the velocity model (RMS velocity in unmigrated space) can be supplied to the migration process to obtain the imaged section. The velocity modeling will require further effort to develop a low-frequency model for input to the seismic inversion process. After seismic data are migrated, other processes are applied that affect the timing (location) of events in the section. Compensation for seismic wave attenuation (Q and dispersion effects is applied, as described later. The compensation process moves events to slightly earlier times in the section. Consequently, new horizons in migrated, Q-compensated space are picked and intersected with the original migrated velocity field. These new horizon data make up the actual structural model that best resembles the subsurface geology. Interval velocities in migrated space are now computed from the migrated RMS-velocity field that was intersected with the new horizons. Reconciliation of interval and sonic velocities is then performed in a time- and space-variant manner to yield an accurate low-frequency velocity model for seismic...

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