Time‐lapse seismic reservoir monitoring has advanced rapidly over the past decade. There are currently about 75 active projects worldwide, and more than 100 cumulative projects in the past decade or so. The present total annual expenditures on 4-D seismic projects are on the order of $50–100 million US. This currently represents a much smaller market than 3-D seismic, but the use of 4-D seismic has grown exponentially over the past decade and is expected to continue to do so.
Nonrepeatable noise, caused by differences in vintages of seismic acquisition and processing, can often make comparison and interpretation of time-lapse 3-D seismic data sets for reservoir monitoring misleading or futile. In this Gulf of Mexico case study, the major causes of nonrepeatable noise in the data sets are the result of differences in survey acquisition geometry and binning, temporal and spatial amplitude gain, wavelet bandwidth and phase, differential static time shifts, and relative mispositioning of imaged reflection events. We attenuate these acquisition and processing differences by developing and applying a cross-equalization data processing flow for time-lapse seismic data. The cross-equalization flow consists of regridding the two data sets to a common grid; applying a space and time-variant amplitude envelope balance; applying a first pass of matched filter corrections for global amplitude, bandwidth, phase and static shift corrections, followed by a dynamic warp to align mispositioned events; and, finally, running a second pass of constrained space-variant matched filter operators. Difference sections obtained by subtracting the two data sets after each step of the cross-equalization processing flow show a progressive reduction of nonrepeatable noise and a simultaneous improvement in timelapse reservoir signal.
A significant degradation in the quality of Kirchhoff 3-D migration images often arises because the migration operator summation trajectory is too steep for the input seismic trace spacing and frequency content. We present an operator anti-aliasing method that suppresses this problem, based on local triangle filtering. The N -point anti-alias triangles are efficiently applied as 3-point filters after causal and anticausal integration of the seismic trace data. We implement our method on a massively parallel CM-5 in a memory and floating-point efficient algorithm, and compare our anti-aliasing method to a standard Kirchhoff migration using a 3-D salt intrusion dataset from the Gulf of Mexico. Our results indicate that our anti-aliasing method greatly enhances the 3-D resolution of steep salt-sediment interfaces and faults, and suppresses false reflections caused by conventional Kirchhoff-migration aliasing artifacts.
W e are about to face a surge in the need for geophysical characterization and monitoring of subsurface reservoirs and aquifers for CO 2 sequestration projects. Global energy demand is rising signifi cantly, expected to double over the next 20-30 years, driven by world population increase and the rapid growth of emerging economies. At the current rate of development of alternate energy sources, it is possible that the world may have to rely even more heavily on carbonbased fuels than at present to meet the impending energy demand (Figure 1). With global oil production near its peak or perhaps already in decline, this will place an increased emphasis on coal and LNG (liquid natural gas) in the carbonbased energy mix, and on unconventional hydrocarbon resources like tight gas, coal-bed methane, and heavy-oil tar sands. All of these carbon-based energy sources, especially coal-fi red power plants, LNG, and tar-sand operations, will create a growing supply of excess CO 2 . Irrespective of whether man-made CO 2 emissions are a signifi cant cause of global climate change, or simply well-correlated with global temperature rise, there will be increasing pressure from world governments to reduce the amount of CO 2 emissions to the atmosphere, via policy change (e.g., Kyoto, Copenhagen) or via fi nancial measures (e.g., carbon tax, cap and trade). Capturing industrial CO 2 at its various sources and injecting it into deep geologic formations for longterm storage (sequestration) appears to be one of the most promising methods to achieve signifi cant reductions in atmospheric CO 2 emissions.Th e basic CO 2 sequestration approach will be to capture it at a source (e.g., coal-fi red power plant, LNG facility, or tar-sands operation) and inject it into a deep geologic formation located nearby. Subsurface storage targets include depleted hydrocarbon reservoirs, and saline aquifers. A massive undertaking has already started to locate and rank subsurface reservoir candidates for CO 2 sequestration among the world's sedimentary basins, and future work will require detailed geologic and geophysical site characterization of these reservoirs/aquifers in terms of better defi ning storage capacity (volume, porosity), injectivity (permeability, pressure regime, etc.), and sealing effi ciency (permeability barriers, structural and stratigraphic traps, fault seal, CO 2 trapping mechanisms, CO 2 capillary pressures, geochemistry, etc.). Australia has recently become the fi rst nation in the world to open up off shore exploration leases specifi cally for the purpose of locating potential subsurface CO 2 storage sites in preparation for a future market in CO 2 sequestration ( Figure 2). Th e role for seismicIn addition to site characterization, there will be a huge demand for geophysical monitoring and verifi cation technol-
We autocorrelate the continuously recorded seismic wavefield across a dense network of seismometers to map the P wave reflectivity response of the Jakarta Basin, Indonesia. The proximity of this mega city to known active faults and the subduction of the Australian plate, especially when the predominance of masonry construction and thick sedimentary basin fill are considered, suggests that it is a hot spot for seismic risk. In order to understand the type of ground motion that earthquakes might cause in the basin, it is essential to obtain reliable information on its seismic velocity structure. The body wave reflections are sensitive to the sharp velocity contrasts, which makes them useful in seismic imaging. Results show autocorrelograms at different seismic stations with reflected‐wave travel time variations, which reflect the variation in basement depth across the thick sedimentary basin. We also confirm the validity of the observed autocorrelation waveforms by conducting a 2‐D full waveform modeling.
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