Development scheme screening considering reservoir damage based on the AHP model

Abstract

AbstractThe development process of oil and gas fields is affected by engineering and geology. Reservoir damage is significant as a bridge connecting these two disciplines. The life cycle of oil and gas fields can be prolonged by making development plans that consider reservoir damage. Therefore, this study performed experiments and discusses a Cretaceous reservoir development in the Chun17 block of the Chunguang Oilfield. We have carried out five sensitivity experiments on typical cores from the block, and analyzed lithology, physical properties, and crude oil. A mathematical model based on the Analytic Hierarchy Process (AHP) was then established based on the core data.Overall, the reservoir in the study area has ultra-high porosity and high permeability. The reservoir has moderately strong water sensitivity (damage rate is 38 ~ 90%) and moderately strong alkali sensitivity (damage rate is 22 ~ 75%). The crude oil belongs to extra-heavy oil reservoirs (containing 2.43% wax, 0.96% sulfur, 20.25 m% gum, 7.35 m% asphalt, 38.26 m% saturated hydrocarbon, and 27.51 m%). The crude oil is sensitive to temperature changes. Based on the AHP model analysis, the development scheme chooses the third (weight 0.1757) of the conventional analytic results of AHP; the Thermal oil production C1 scheme has the most stable future trend and appears to be the best option. In the next step, using fire flooding technology to develop the reservoir will benefit the most economically. The workflow consisting of "conclusion of reservoir experiment → AHP mathematical modeling → verification of relative permeability of high-temperature oil and water → verification of trial production" is simple and effective. The findings of this study can help to better understand the idea and process of making development plans for sensitive oil and gas fields through reservoir evaluation. Combining experimental data with mathematical modeling can find a balanced combination point in qualitative and quantitative analysis. Whether this combination point is correct can be verified by field engineering practice.