Capacitance resistance modeling for primary recovery, waterflood and water-CO₂ flood
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Reservoir characterization is very important in reservoir management to plan, monitor, predict and optimize oil production. Reservoir simulation is well-accepted in reservoir management but it requires many inputs, needs months to set up and complete a set of simulation runs, and contains large uncertainty in physical and geological properties. Therefore, simpler methods that provide quick results to complement or substitute reservoir simulation are important in decision making. Capacitance resistance model (CRM) is one of the methods. CRM is an input-output model derived from a continuity equation to quantify producer-injector connection strength during waterflood using solely production data. This work improves the CRM application method for waterflood and develops CRM theories and application methods for other recovery periods such as primary recovery and water-CO2 flood. A West Texas field test was carried out to validate CRM for a waterflood. The CRM fit was evaluated and used to optimize the oil production by changing injection rates. Through this first field experiment, a CRM application procedure was developed. With the CRM optimized injection schedule, the field gained 5372 bbls of additional oil production increase after one year. This research also quantitatively validates the CRM gain and time constant using synthetic fields and compares them to parameters of the streamline model, a complex model with similar purposes to the CRM. The CRM provides similar results as the streamline model with fewer inputs. The CRM was extended to primary recovery and water-CO2 flood. A new CRM equation – the integrated CRM (ICRM) - for primary recovery was developed and validated on many synthetic fields and an Oman field. The model can estimate dynamic pore volume, productivity index and average reservoir pressure that compare closely to simulated values and field knowledge. Additionally, the ability of CRM to quantify injector-producer connection strength and predict fluid production was examined on a synthetic water-CO2 flood field. A new oil production model to be used with CRM application in water-CO2 flood was developed and validated on synthetic data. The model predicts oil production from injection rate and relative permeability. CRM has successfully optimized waterflood on a West Texas field by reallocating the water from ineffective to effective injectors. New interpretations of the CRM parameters enable quantitative validation and integration of the CRM results with other methods. In primary recovery, the ICRM can estimate reservoir properties without requiring well testing which can cause loss of production. The CRM and the new oil production model can quickly characterize water-CO2 flood for short term production monitoring.