A practical workflow for performance prediction of low permeability reservoirs
Golko, Steven J.
A practical workflow for performance prediction of low permeability reservoirs - 25 p.
The Society of Petroleum Evaluation Engineers (SPEE) recently released Monograph 4, "Estimating Ultimate Recovery of Developed Wells in Low-Permeability Reservoirs"(hereinafter called "Monograph 4". This paper outlines a practical engineering workflow enabling companies to evaluate unconventional plays developed with horizontal multi-stage fractured wells consistent with the principles summarized in Monograph 4. This workflow has many applications including assessing potential acquisitions, defining new plays, evaluating competitor results, corporate budget processes, long term business planning, portfolio management, or reserves certification. The workflow is based on the recognition that reservoir performance and reservoir behavior are two separate things. Reservoir behavior is driven by the rock and fluid properties (fluid type, permeability, relative permeability, compressibility, PVT data, etc), and can be largely characterized by the decline exponent, or shape of the curve. Within an area exhibiting similar reservoir behavior, we see variations in reservoir performance, which can be associated to many factors including completion type, completion effectiveness, and minor variations in reservoir quality within the area. The workflow begins with determining "geologic bins" within the study area (based on similar reservoir behavior), then assessing the production performance exhibited by wells within the bin. Standard empirical decline curve analysis (DCA), using a two-segment Arps equation, is employed to estimate (1) a representative decline exponent in the initial transient flow period, (2) the time to boundary dominated flow, and (3) a representative decline exponent in the boundary dominated flow period. This initial assessment of reservoir behavior is followed by further segregation of the wells into "performance bins" respecting local variations in reservoir quality affecting productivity and estimated ultimate recovery. Typical production performance profiles (type curves) are created for each of the performance bins. The type curves are used to forecast the future production for existing wells and future development. This workflow has been developed and refined over several years, and has been tested in large scale applications. Two case studies are presented demonstrating the capabilities of the process. A third example is referred to throughout the paper to illustrate the principles and procedures.
PD I116 3 0015570
A practical workflow for performance prediction of low permeability reservoirs - 25 p.
The Society of Petroleum Evaluation Engineers (SPEE) recently released Monograph 4, "Estimating Ultimate Recovery of Developed Wells in Low-Permeability Reservoirs"(hereinafter called "Monograph 4". This paper outlines a practical engineering workflow enabling companies to evaluate unconventional plays developed with horizontal multi-stage fractured wells consistent with the principles summarized in Monograph 4. This workflow has many applications including assessing potential acquisitions, defining new plays, evaluating competitor results, corporate budget processes, long term business planning, portfolio management, or reserves certification. The workflow is based on the recognition that reservoir performance and reservoir behavior are two separate things. Reservoir behavior is driven by the rock and fluid properties (fluid type, permeability, relative permeability, compressibility, PVT data, etc), and can be largely characterized by the decline exponent, or shape of the curve. Within an area exhibiting similar reservoir behavior, we see variations in reservoir performance, which can be associated to many factors including completion type, completion effectiveness, and minor variations in reservoir quality within the area. The workflow begins with determining "geologic bins" within the study area (based on similar reservoir behavior), then assessing the production performance exhibited by wells within the bin. Standard empirical decline curve analysis (DCA), using a two-segment Arps equation, is employed to estimate (1) a representative decline exponent in the initial transient flow period, (2) the time to boundary dominated flow, and (3) a representative decline exponent in the boundary dominated flow period. This initial assessment of reservoir behavior is followed by further segregation of the wells into "performance bins" respecting local variations in reservoir quality affecting productivity and estimated ultimate recovery. Typical production performance profiles (type curves) are created for each of the performance bins. The type curves are used to forecast the future production for existing wells and future development. This workflow has been developed and refined over several years, and has been tested in large scale applications. Two case studies are presented demonstrating the capabilities of the process. A third example is referred to throughout the paper to illustrate the principles and procedures.
PD I116 3 0015570
