A Volcanic Reservoir: Integrated Facies Distribution Modeling and History Matching of a Complex Pressure System
- Tomomi Yamada (Japan Petr. Explor. Co. Ltd.) | Yoshiyuki Okano (Japan Petr. Explor. Co. Ltd.)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- February 2007
- Document Type
- Journal Paper
- 77 - 85
- 2007. Society of Petroleum Engineers
- 5.6.9 Production Forecasting, 7.6.2 Data Integration, 1.6 Drilling Operations, 4.1.2 Separation and Treating, 3 Production and Well Operations, 1.6.9 Coring, Fishing, 5.1 Reservoir Characterisation, 4.3.4 Scale, 4.1.5 Processing Equipment, 5.5.8 History Matching, 5.1.5 Geologic Modeling, 2.2.2 Perforating, 6.1.5 Human Resources, Competence and Training, 5.1.1 Exploration, Development, Structural Geology, 4.1.6 Compressors, Engines and Turbines
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A Tcf-class gas field has been producing over several decades in Japan. The reservoir body comprises stacked rhyolite lava domes erupted in a submarine environment. A porous network developed in each dome and rapid chilling on contact with seawater caused hyaloclastite to be deposited over it. Although hyaloclastite is also porous in this field, its permeability has been reduced dramatically by the presence of clay minerals. Impermeable basaltic sheets and mudstone seams are also present. Each facies plays a specific role in the pressure system.
Stratigraphic correlation originally identified multiple reservoirs. Gas has been produced almost exclusively from the largest one. However, following 10 to 20 years of production, the pressures within unexploited reservoirs were noticed to have declined at a variety of rates. Unusual localized behavior has also been observed. Because seismic data were not proved particularly informative, we decided to remodel the entire system by specifically using pressure data.
We employed a combination of multipoint geostatistics and probability perturbation theories. This approach successfully captured the curved facies boundaries within stacked lava domes while accounting for pressure data by means of history matching to address nonstationarity in the real field. Building a suitable training image is commonly a difficult aspect of multipoint methods and poses particular problems for volcanic reservoirs. It was accomplished here by iteratively adjusting the prototype until satisfactory history matching was achieved with a reasonable number of perturbations. Ambiguous reservoir boundaries were represented stochastically by populating a predetermined model space with pay and nonpay pixels.
The modeling results closely simulate measured pressure histories and appear realistic in terms of both facies distributions and reservoir boundaries. They suggest that uneven pressure declines between different units are caused by the tortuous flow channels that connect them. The results also account for the unusual smaller-scale pressure performances observed. The final training image obtained here indicates more intensive spatial variations in facies than previously appreciated. Original gas in place (OGIP)estimates made with 20 equiprobable realizations are scattered within ±15% of the mean value. Estimates of incremental recovery made by drilling a step-out well reveal greater variation than those made by installing a booster compressor, which quantifies a higher associated geological risk.
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