Opportunities and Uncertainty Mitigation Base on Survivor Bias in a Mature Field: Cañadón León, San Jorge Basin, Argentina
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Published:2023-06-05
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Container-title:Day 4 Thu, June 08, 2023
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Legarreta Andres Esteban1, Barberis Rosina Cristina1, Schein Florencia Tercila1, Martino Luis ángel1, Gandi Silvana1
Abstract
Abstract
Survivorship bias is a well-known tendency to overweight available data and underestimate the missing information. Cañadón León in San Jorge basin, Argentina is a waterflooded field with a current water-cut of 95% where innovative recovery strategies such as Chemical Enhanced Oil Recovery (cEOR) become a condition for further development. Data acquisition is often biased towards the best reservoirs, leading to major uncertainty in assessing opportunities in mature fields.
After 70 years of primary oil production and water injection, the study aims to evaluate the remaining opportunity, which leads to a double challenge: Estimation of bypassed oil during the inefficient waterflooding process because of poor mobility ratio and the potential of marginal reservoirs. Initial stage field exploitation and data acquisition at early stages of development aimed mainly to characterize the higher oil-saturation zones with better petrophysical properties, leading to a lack of data on marginal reservoirs which become critical targets for mature reservoirs analysis. The data interpretation within a semi regional geological framework to build the static model, allowed a representative construction of poorly characterized reservoirs due to survivorship bias effect.
Several hypotheses were evaluated with dynamic simulation to avoid assuming recoverable oil based on survivorship bias due to missing information in secondary targets. Integration of what-if scenarios, both static and dynamic, and assessment of uncertainty provided a better understanding of critical constraints and optimum ranges of variability to analyze cEOR with polymer injection. A wide variety of fluid saturation scenarios, mobility ratios and reservoir properties were considered to quantify the field potential.
Sensitivity analysis helped to identify the most relevant uncertainties in history matching and reliability in forecast: Primary gas cap contact and its expansion, water-oil contact, the transition zone (oil-water system), fluid mobility ratios and polymer characteristics.
A major benefit from polymer injection is CO2 emissions reduction per barrel of oil by more than 40% compared to water injection, reducing project carbon footprint. Development strategy achieves a short-term incremental recovery factor of 10% with a total of 68 wells in 20 injection patterns (considering a period between 3 to 6 years due to oil production acceleration). This methodology allowed to establish the foundations for development strategies based on multi-modelling within conceptual geological frameworks reflecting the impact of the recognized uncertainties. This technique does not allow to determine the unknowns, but it does allow to estimate their impact.
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