Due process has been followed in launching this focused study, starting with integration and analysis of available static and dynamic data to characterize selected sectors of the subject reservoir. The objective of this initiative is to build 3D numerical models for characterization of the hydraulic connectivity within the sector models. These sectors have been originally taken out of the corresponding static geological models. Some of the wells in the sectors have data from prior transient tests, which have been utilized to condition the permeability around the corresponding wells. But this step has not been found enough to describe the dynamic behavior on a long term. Hence, data from a multi-well, interference test has been utilized to enhance the dynamic characteristics of fluid movement in the numerical models. This paper presents an integrated approach to characterize the hydraulic communication and heterogeneity in the reservoir. The results of this study have helped improve reservoir characterization in the corresponding part of the reservoir simulation model, providing a more refined input of dynamic pressure and permeability data within the area of interest. Best of all, the reservoir engineers have acquired a wealth of knowledge of reservoir connectivity to be utilized for their reservoir management practices.

The purpose of this paper is to demonstrate and explain the factors that can produce notable differences between permeability measured in a laboratory from core analysis and permeability estimated from pressure transient analysis (PTA) of build-up and fall-off tests. The paper presents several synthetic cases to show the variations in obtained permeability using each method, and the contributing factors affecting the outcomes. For calculating effective permeability from PTA, errors in input data such as static, dynamic or pressure/volume/temperature (PVT) fluid data can significantly increase discrepancies. Heterogeneity in reservoir permeability distribution such as vertical reservoir layering (variation in permeability vertically), large scale lateral variation or fractures will also add to the discrepancy between methods. Comparison between the permeability from both sources for the same subject wells will be used to illustrate these factors by interpretation of the data and characterization of reservoir. The primary factor contributing to the differences in permeability is that the one measured from core analysis represents absolute permeability to air or nitrogen in the lab and corresponds to only a small sample (few inches) of the reservoir. However, the calculated permeability from a PTA represents the average effective permeability of the reservoir fluid type within the radius of investigation for that particular test. Hence, each method provides a permeability based on different fluids and volumes of investigation. A methodology that can be utilized to estimate the effective permeability for uncored wells, which usually make out most of the wells in any field, using average effective permeability from PTA will be discussed. Such a method is beneficial for simulation studies that require sufficient knowledge of permeability in each area under study. This method should help in extrapolating the permeability all over the field to get more reliable predictions. Permeability plays a very important role in reservoir characterization as well as simulation. Knowing the permeability leads to the success in the placement of wells and therefore wells performance and ultimate hydrocarbon recovery. Thus, the most accurate determination of the permeability is of extreme importance because it affects the economy of the field development. The paper discusses the factors that can produce differences between measured permeability in a laboratory from core analysis and permeability estimated from PTA and the best practices for correcting and correlating between the permeability to achieve more reliable predictions for reservoir characterization and simulation studies which results in better field development.