Case Study: Economic Analysis Identifies Optimal Redevelopment Scenario for Complex Gas Field in Pakistan

Alternative approaches introduced to overcome scarcity of field data required for reservoir modeling

Challenge: Simulate four clastic and carbonate reservoirs in the absence of critical information and determine which, if any, of five potential field redevelopment scenarios would maximize NPV and ultimate recovery factor (URF).

Solution: Collaborate with the operator to build a digital database, devise ways to replace missing or unreliable data, construct 3D static and dynamic models, run history matching, identify possible fault compartments, forecast production, and analyze the economics of various scenarios.

Result: Identified the optimal redevelopment scenario based on NPV. Determined that, should the current market price of gas double, URF would be boosted from less than 60% to as high as 70%. NPV would be increased by a factor of three and field abandonment would be delayed six years.

Overcome scarcity or lack of critical field data

After producing a natural gas field in the structurally complex Sulaimon fold belt of Pakistan for several decades, an operator needed to generate an economically viable field redevelopment plan. Twelve wells were currently producing from a sequence of clastic and carbonate reservoirs.

To identify scenarios that could optimize NPV and ultimate recovery factor (URF), the operator engaged a multidisciplinary team of Schlumberger petrotechnical experts to conduct a comprehensive field study involving static 3D geological modeling, dynamic reservoir simulation, and economic analysis.

Initial data included 18 wells, core analyses from a few wells, bottomhole static pressure (BHSP) surveys from various zones, and 615 km of 2D seismic shot in 1982, 1987, and 1996. There were, however, no reliable wellhead flowing pressure (WHFP) measurements, no surface pipeline elevations, and no 3D seismic surveys.

Due to unreliable, scarce, and missing field data, Schlumberger devised innovative methods to obtain critical information. For example, to identify possible fault compartments indicated by history matching but not evident on 2D seismic, geologists built a sand box model of local structure and used a high-intensity depth contouring scheme. In lieu of flow rate data, engineers used plant inlet pressure to constrain surface network simulation. To accurately model pressure drops due to liquid holdup in surface pipelines, they estimated elevations from satellite imagery.

Perform modeling, simulation, and economic analysis

Working closely with the operator, consultants began by reprocessing 14 2D seismic lines from the latest survey, generated synthetics for three wells, and carried out seismic interpretation on six horizons, identifying at least 15 intrareservoir faults.

The 3D static field model consisted of four main formations, capturing vertical heterogeneities within clastic reservoirs, including 2-m channel sands. Carbonates appeared relatively homogeneous. Downhole tests in eight wells provided a representative permeability multiplier for the field development plan. Analysis of corrected BHSP data suggested hydraulic compartmentalization in part of the field, and provided average reservoir pressures for history matching. The history match covered 1989 through 2011. Initial runs assumed no sealing faults, but the dynamic model could not explain observed pressure data. Introducing two simulation faults in one flow unit based on sand box modeling achieved the best match.

Next, Schlumberger experts ran production forecasts on various combinations of five field redevelopment scenarios ranging from producing without any further intervention to drilling infill wells. Recovery factors associated with these scenarios ranged from 59% to 79%.

Identify optimal field redevelopment strategy

All scenarios were first rated on NPV. Analysis revealed that, despite the promising recovery factor associated with infill drilling, no such drilling scenario would be viable because NPV would be too low in every case. The optimal development scenario, in terms of NPV, turned out to be a combination of scenario 2 (recompleting new zones in existing wells that had watered out) and scenario 3 (adding perforations in the less-depleted zones of certain wells).

Sensitivity analysis of key economic factors—opex, discount rate, and gas price—showed that gas price had the single greatest impact on both NPV and URF. As a result, the operator learned that, if the current gas price were to double, the optimal redevelopment scenario identified would boost the URF from less than 60% to as high as 70%, increase NPV by a factor of three, and postpone field abandonment by six years.

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Identify Optimal Field Redevelopment Strategy

Illustration shows possible fault compartments.Charts show sensitivity analysis of three key economic factors.
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