David Lumley

Time-lapse seismic reservoir monitoring

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

Cross‐equalization data processing for time‐lapse seismic reservoir monitoring: A case study from the Gulf of Mexico

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.

Imaging complex geologic structure with single-arrival Kirchhoff prestack depth migration

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 time-lapse reservoir signal.

Assessing the technical risk of a 4-D seismic project

We compare various forms of single‐arrival Kirchhoff prestack depth migration to a full‐waveform, finite‐difference migration image, using synthetic seismic data generated from the structurally complex 2-D Marmousi velocity model. First‐arrival‐traveltime Kirchhoff migration produces severe artifacts and image contamination in regions of the depth model where significant reflection energy propagates as late or multiple arrivals in the total reflection wavefield. Kirchhoff migrations using maximum‐energy‐arrival traveltime trajectories significantly improve the image in the complex zone of the Marmousi model, but are not as coherent as the finite‐difference migration image. By carefully incorporating continuous phase estimates with the associated maximum‐energy arrival traveltimes, we obtain single‐arrival Kirchhoff images that are similar in quality to the finite‐difference migration image. Furthermore, maximum‐energy Greens function traveltime and phase values calculated within the seismic frequency ban...

4D Seismic Data Processing Issues And Examples

At the initial stage of any 4-D project, Chevron’s business unit engineers and geoscientists usually ask an obvious question: “Do you think it will work?”

Subsurface fluid flow properties from time-lapse elastic wave reflection data

4D seismic data acquisition efforts can be divided into three major categories: “legacy”, “re-shoot” and “4Ddesign ” projects. In legacy 4D seismic projects, multiple vintages of overlapping 3D seismic data sets are analyzed for time-lapse effects, but none of the 3D surveys were originally acquired with a 4D application in mind. In reshoot 4D seismic projects, the baseline 3D seismic survey was not acquired for 4D purposes, but the subsequent reshoot 3D survey was designed, at least in part, with a 4D objective in mind. Finally, in 4D-design projects, at least two of the time-lapse 3D seismic surveys were specifically designed and acquired to optimize the subsequent reservoir monitoring analysis.

Estimation of Reservoir Pressure And Saturations By Crossplot Inversion of 4D Seismic Attributes

Time-lapse (4D) seismic is a procedure where a reservoir is imaged with reflected seismic energy at several time steps while being depleted. This technology is successful when changes in dynamic reservoir properties, such as pressure, saturation of fluids and temperature produce an observable change in the seismic impedance contrast of the medium in 3D space. A careful analysis combining rock physics measurements, reservoir simulation and forward seismic modeling is required to identify if changes in reservoir properties can produce seismically observable impedance changes, and if so, how they are related to dynamic fluid flow in the reservoir. In current industry practice, angle- averaged (or stacked) P-to-P wave reflection seismic images, approximating P-wave impedance changes, are used in time- lapse seismic analysis. Introduction of angle dependency in P-to-P wave reflection data allows us to estimate both P- wave and S-wave impedance changes over the reservoir. Utilizing multi-parameter images from angle-dependent elastic time-lapse seismic surveys, or 4D AVO (amplitude variation with offset) attributes, we demonstrate the potential to invert for multiple reservoir properties such as changes in saturation of fluids and pressure. Estimates of saturation and pressure changes allow integration of time-lapse seismic with reservoir engineering models to improve reservoir fluid-flow prediction and enhance reservoir management decisions.

The next wave in reservoir monitoring : The instrumented oil field

We present a method to simultaneously estimate pressure and saturation changes in a producing hydrocarbon reservoir using time-lapse (4D) seismic attributes. 4D seismic attributes are displayed in a crossplot domain, where pressure and saturation axes can be estimated deterministically or interpretively. These axes form the basis for a linear or nonlinear coordinate transformation to the pressure-saturation domain. A final calibration to production data is required to convert the qualitative results to quantitative estimates of pressure and saturation. Our method is applied to 4D seismic data sets acquired over producing North Sea reservoirs in the Schiehallion and Gullfaks fields.

Reservoir monitoring; a multidisciplinary feasibility study

The next wave in reservoir monitoring will be the “instrumented oil field.” The defining concept is twofold. First, arrays of seismic and other geophysical sensors will be permanently deployed at or near the surface, and in boreholes, associated with a producing hydrocarbon reservoir. These permanent arrays will provide on-demand imaging capability of large-scale reservoir fluid flow. Second, injecting and producing wells will be instrumented with downhole sensors such as pressure, temperature, and saturation gauges to monitor small-scale fluid flow local to the wells.

Business and technology challenges for 4D seismic reservoir monitoring

There is a recognized need to combine the skills of geoscientists and engineers to build quantitative reservoir models that incorporate all available reservoir data. These integrated models are critical for forecasting, monitoring, and optimizing reservoir performance because they will enable more accurate flow simulation studies, identification of permeability flow paths and barriers, mapping of bypassed oil, and monitoring of pressure and saturation fronts.