Abstract
Interwell connectivity is an important parameter for reservoir characterization and is essential for making decisions on optimization of water injection and infill wells. Unlike ordinary reservoir, starting pressure gradient is an important characteristic for heavy oil reservoir. For better quantifying the interwell connectivity of heavy oil reservoir, a robust method to quantify interwell connectivity using performance data is proposed.
Considering the characteristics of the starting pressure of heavy oil flow, the production model between the yield and the pressure difference is established. And the production model is linear when the steady flow and the water content are relatively stable. And then, a time constant function is constructed to characterize the lag and attenuation of waterflood signals in formation propagation. By substituting the production model and the time constant function into the equation of material balance, the relationship model between cumulative liquid production and the cumulative water injection (CPIM) is obtained through two integrals. The cumulative relation overcomes the instability of instantaneous relations. The solution of the CPIM is transformed into an optimization problem by using the least squares principle. And the quantitative connectivity evaluation is obtained by using PSO algorithm.
Compared with the single-well dynamic analysis, the accuracy of the CPIM is over 90%, but the spent time is less than half of the single-well dynamic analysis. In addition, the paper presents a case study to compare findings from the results of the CPIM and the use of interwell tracer. The results obtained from the CPIM shows good agreement with the results obtained from interwell tracer. And the CPIM can be applied to some wells which can not be carried out tracer test because geological conditions of these wells are particularly complex. In summary, this CPIM is not only feasible, but also saves a lot of time and money.
The CPIM can be used to quickly estimate reservoir properties and infer interwell communication in primary and secondary recovery from available data with high confidence. The method was applied to Bohai oil field which is effective for establishing well interaction pattern. Recommendations were given to improve waterflood efficiency.
