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4D Assisted History Matching—Closing the Loop

The traditional technique of manually adjusting reservoir simulation models to achieve a history match is time consuming and problematic at best; adding 4D seismic data to the equation only increases the complexity of the task. The inclusion of 4D seismic, however, results in better constrained simulation models and a greater understanding of the uncertainty inherently associated with models. Numerous published works have shown that 4D Assisted History Matching (4DAHM) can enhance the business value of existing 4D seismic and enable rapid matching of new models to the recorded seismic responses, more than justifying the application of this new approach.

Consider the following example, where a group needed to determine the swept regions of an injector/producer pair in an offshore turbidite field. After a monitor survey was completed, the team was tasked with determining the match quality between the measured 4D response and the modeled simulation cellular grid properties. The group turned to the CoViz 4DAHM workflow, which offers both GUI and command line access for ease-of-use and extensibility; the result of the workflow is a script containing Match Quality (MQ) information for input into an external program containing the appropriate history matching algorithms.

Figure 1. Schematic of the 4D Assisted History Matching workflow in CoViz 4D (from Hodgson et al.: The Leading Edge, May 2017 pg. 401).

After entering the required inputs to the 4DAHM workflow (reservoir simulation model, rock and fluid properties, reference constants, an average velocity grid, seismic template grid, a wavelet file, and anomaly information), a seismic extraction was computed by summing the negative amplitudes present over the reservoir unit; a similar extraction was done for the reservoir simulation cell properties. A visual comparison of the 4D Seismic (SNA) response and the modeled EEI percentage difference showed elements of similarity.

Figure 2. Example 4D Seismic (SNA) response extracted from a sand body (left) and modeled EEI percentage difference from baseline survey (right).

The CoViz 4DAHM “feature mapping” workflow enables the use of polygons to delimit which regions should be considered to assess local match qualities and sensitivities. The team used polygons to segment the reservoir around known anomalies that correspond to specific geophysical effects (in this case, the swept area between a producer/injector pair). The 4DAHM workflow reduces the reservoir physics and its simulation to a simple binary representation to show where the 4D seismic response and simulation model agree or disagree with each other; where there is 4D signal, green areas indicate a match and blue areas indicate a mismatch. Although there were sizable areas of mismatch, considering that the Match Quality results were generated without any specific optimizations or calibration of the reservoir model the team was encouraged.

Figure 3. The computed Match Quality (MQ) map (left). The MQ index (right) indicates regions where the 4D seismic response agrees or disagrees with the simulation model.

In conclusion, use of the CoViz 4D Assisted History Matching workflow in this offshore turbidite field helped the team achieve a much better matched reservoir model in far less time than a traditional approach would have taken and it augmented the business value of their existing 4D seismic data.

See the CoViz 4D Sim2Seis page for more information.

Data Sources/Credits:

Data in Figures 2 and 3 used with permission of owner.


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