Abstract
Fracture–cavity karst carbonate reservoirs have multiple storage space with irregular geometry and various scales, and this caused strong heterogeneity and complex flow characteristics. Accurately calculating the well-controlled dynamic reserves of this kind reservoir effectively is the basis to optimize oil field development plan and making the transformation measures of production well. In order to solve the problem that conventional well-controlled dynamic hydrocarbon reserves calculation method is not suitable for such type reservoirs, we applied a method based on production data analysis. Classification standard of oil well types is established based on the fracture–cavity reservoirs geological static and production dynamic characteristics. Conceptual characteristics of geological model and fluid flow pattern for different types of production wells are assumed. Calculation workflow for well-controlled reserves of fracture–cavity reservoir is established. In the process, some technical key points are proposed to improve accuracy of curve fitting, such as converting the bottom hole pressure from wellhead pressure, correcting the well control range and converting the PVT parameters at the pseudo-steady state. We verified correctness of this method by comparing the calculated results with numerical simulation results of actual production well. This method is well used to Tahe Oil field of Tarim Basin in China. The result shows that the well-controlled reserves quantitative calculation results through this method are in conformity with oil field actual understanding, and the remaining dynamic reserves mainly exist in the drainage area of the wells that drilled different reservoir bodies with good connectivity, especially at the top of large karst caves, and that is the target of further adjusting.
Highlights
Well-controlled dynamic reserves refer to the total reserves within the range of pressure transmission in the production process, and the size of dynamic reserves is the important basis to evaluate reservoir development level and remaining oil potential, for adjusting the direction of potential tapping, and is the material basis for single well measures to improve the development effect
We introduce the concept of material balance time and normalized pressure, where the normalized pressure is slope and intercept, including the well-controlled reserves, the permeability, the skin factor, the cross-flow parameter, the storativity ratio and the drainage radius of the well
In order to verify the correctness of the calculation and process method, we established the fine 3D geological model of fracture–cavity reservoir for a typical well, carried out reservoir numerical simulation research, matched the production historical characterization and evaluated well-controlled dynamic reserves based on numerical simulation results
Summary
Well-controlled dynamic reserves refer to the total reserves within the range of pressure transmission in the production process, and the size of dynamic reserves is the important basis to evaluate reservoir development level and remaining oil potential, for adjusting the direction of potential tapping, and is the material basis for single well measures to improve the development effect. We put single wells of fracture–cavity reservoir divided into three types, assumed conceptual characteristics of geological model for the drainage area of different types of wells and used different fluid flow conceptual models to describe fluid flow law around different types of wells On these bases, we established calculation workflow of single well-controlled reserves for fracture–cavity reservoir and proposed some methods to improve the precision of curve fitting, through converting bottom hole pressure from wellhead pressure, correcting the well control range and calculating the PVT at the pseudo-steady state. Depending on the types of production wells combined with characteristic of fracture–cavity karst reservoirs, we establish the reservoir’s geological concept and hypothesis of fluid flow model around the wells. After analyzing sensitivity of the flow concept model, we adopt triple-porosity singularpermeability model to describe the flowing of the fluid
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