Well Production Forecast in a Tight Gas Reservoir—Closing the Loop With Model-Based Predictions in Jonah Field, Wyoming
- Fabian Oritsebemigho Iwere (Schlumberger) | Hui Gao (Schlumberger) | Barbara Luneau (Schlumberger)
- Document ID
- Society of Petroleum Engineers
- SPE Rocky Mountain Petroleum Technology Conference, 14-16 April, Denver, Colorado
- Publication Date
- Document Type
- Conference Paper
- 2009. Society of Petroleum Engineers
- 1.6.9 Coring, Fishing, 3.3.1 Production Logging, 5.1 Reservoir Characterisation, 2.4.3 Sand/Solids Control, 5.5.8 History Matching, 1.6 Drilling Operations, 1.2.3 Rock properties, 5.8.1 Tight Gas, 4.3.4 Scale, 5.1.3 Sedimentology, 5.5.3 Scaling Methods, 3.2.3 Hydraulic Fracturing Design, Implementation and Optimisation, 5.1.5 Geologic Modeling, 5.6.9 Production Forecasting
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This paper presents a closed-loop reservoir study in tight gas fluvial sands of the giant Jonah gas field located in the northwestern part of the Greater Green River Basin, Wyoming. It produces gas from the micro-darcy fluvial channel sandstones of the Upper Cretaceous Lance Formation after multistage hydraulic fracturing. Single sand body pay zones would not be commercially attractive.
Rigorous reservoir modeling and simulation workflows were employed to build a 3D flow model from geology, geophysics, petrophysics and engineering data and interpretation. The stacked, multi-pay, tight gas sandstone reservoirs and their overpressured conditions were modeled and the hydraulic fractures properties were derived from matching initial well performance. The model was calibrated with well and field performance data through 2006. The calibrated model was used to forecast well performance, estimate reserves; investigate optimal well spacing and infill-well patterns.
Production for old wells and infill wells completed during 2007 and 2008 which was not included in the model calibration is compared with our previously forecasted results. The comparison shows that the actual well production of most of the wells is close to our forecasted results. The production-validated results of this closed-loop study clearly demonstrate that well production and field performance can be forecasted using reservoir modeling and simulation in a highly heterogeneous reservoir. Rigorously-constructed reservoir model(s) help us test and determine optimal production techniques to maximize field production goals. It can be confidently used to reduce field development risk and maximize profits.
Tight sand reservoirs account for most of the gas production in the US Rockies and their development is the core business of the US West Geomarket. Every well must be hydraulically fractured in multiple stages to obtain economic production. Field developments have been based on designs and forecasts using decline curve analysis and single well analytical methods, which assume no interference between wells. There were also lack of adequate reservoir characterization and little or no integration of the geoscience disciplines. This practice continued until recently when denser well spacing and consequent possible reservoir pressure depletion at future infill locations became subjects of investigation.
These investigations have been carried out with numerical simulation models constructed based on integration of results from multidisciplinary teams. The models comprise a 3-D geocellular model which captures the properties and heterogeneities of the reservoir that is subsequently upscaled into a dynamic simulation model. This flow model is calibrated against historical performance and used for forecasting wells and field performance for our clients. Since completion of the integrated studies, step-out and infill wells have been drilled and cores, logs, completion, pressure and production have been collected from them. This provides a unique opportunity for evaluating the quality of our model forecasts - the subject of this discussion. The reservoir characteristics of subject fields located in the Greater Green River and Piceance Basins, their static and dynamic modeling workflows and a comparison of the models' and actual results are presented in the following sections.
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