A rapid and an effective reservoir simulation model was built based on limited information. 3D seismic impedance, two exploratory wells' log interpretation, a core data, and a well test consisting of an isochronal test and, several months later, an extended flow followed by long build up test were basic available data for this field. The main objective of this study is to estimate recoverable reserve with or without hydraulic fracturing in Mulichinco formation at the Paso Del Indio Field.
Material balance and decline curve analyses have important limitations to estimate ultimate recoverable reserves in the tight gas reservoirs. Well types that are derived from the conceptual simulation models do not reflect the effective drainage area or permeability heterogeneity in the field. A representative permeability in well spacing area should be averaged harmonically or geometrically. In order to estimate the ultimate recoverable reserves in the tight gas reservoirs, permeability heterogeneity or the effective available drainage area to hydraulic fractures should be simulated effectively. Relatively small changes in permeability can results in unsuccessful fracture design and in uneconomical flow rates.
A very quick and effective simple reservoir simulation model was established to estimate recoverable reserves rather than using conventional volumetric, material balance, and decline curve analysis in tight gas reservoirs. Not having any production histories, well test information was used very successfully as history matching information to validate the geological, petrophysical, and PVT models.
The main objective of this study was to describe the nature, distribution, and physical characteristics of the reservoir, by integrating geophysical, geological, petrophysical, and production data in a three dimensional geological and simulation model that represents the behavior of the Hollin reservoir in Bermejo field. The Hollin reservoir required significantly higher effort due to the strong aquifer, the complex relationship between heterogeneity influences, the movement of the water from the aquifer into the reservoir, water and gas conning, stagnation of unproduced oil zones, and migration of oil towards gas zones.
When production data was analyzed, it was determined that even thin shales (on the order of 2-5 ft. or greater) played a role in enhancing reservoir production by delaying water and gas conning and water influx in the Hollin fluvial sandstone. Mapping the shale barriers was as important as mapping the sand bodies. It was decided to correlate the shales interpreted from well log data and introduce shale tops and bases in the geological model. Therefore, in the geological and simulation models shales have been modeled explicitly, down to a five foot resolution.
A Stratigraphic geocellular model was constructed to describe the 3D petrophysical properties, calculate hydrocarbons in place and to prepare reservoir simulation grids. Geological models incorporating shales were modeled. If shale was locally absent, the "shale zone?? was assigned the appropriate reservoir properties determined from well and/or seismically derived attributes. J-Function analysis was implemented successfully in assigning oil saturation. Calculated oil saturation profiles at initial and current times were compared with initial well log oil saturations.
History matching and initialization were conducted to validate geological, petrophysical, PVT, and reservoir models. Flooded and non-flooded regions of reservoir, current WOC and GOC were identified. Areal extent of localized thin shale lenses were modified during history, matching active water breakthrough well by well. The amount of oil invasion in the original gas zone, stagnated oil, and gas contraction volumes were calculated in the most productive marker, Naranja. Current GOC has moved from the original GOC position. Actually, the amount of oil invasion was not significant when it was compared to the volume of stagnated oil.
When geological and simulation models are built and data gathered according reservoir specific problems, successful history matching and predictions can be obtained.