For naturally fractured reservoirs of the double-porosity type, Warren and Root defined two parameters characterizing such systems, F ft, and epsilon. While F ft may be obtained easily from the straight lines of the buildup or drawdown plot, no explicit method for estimating epsilon was plot, no explicit method for estimating epsilon was suggested in the original paper.This paper presents a method whereby the coordinates of the inflection point on a buildup or drawdown plot may be used to estimate epsilon. We show that for pressure drawdown tests, epsilon can be estimated under certain conditions, while for pressure buildup tests, only the ratio of the interporosity flow parameter to the total system porosity/compressibility parameter to the total system porosity/compressibility product, epsilon/[(phi ct)f + (phi Ct)ma], is obtained. product, epsilon/[(phi ct)f + (phi Ct)ma], is obtained. By using the concept of inflection points, an equation is derived where F ft may be obtained from a pressure buildup or drawdown test when no early- or late-time data are available. Introduction Warren and Root presented a solution to the problem of radial flow of a slightly compressible problem of radial flow of a slightly compressible fluid in a naturally fractured reservoir. They assumed that flow occurs only in the fractures and that the matrix blocks, assembled as a uniformly distributed source, deliver the fluid to the fracture system. They characterized such a system by two parameters related to the properties of the reservoir. One of these parameters, the fluid capacitance coefficient, F ft, parameters, the fluid capacitance coefficient, F ft, is used to represent the ratio of the porosity/ compressibility product for the fractures to that for the entire system: (phi ct)f/[(phi ct)f + (phi ct)ma]. The second parameter, epsilon, is defined as the interporosity flow parameter, which indicates the degree of interporosity flow between the matrix blocks and the fracture system. As shown by Kazemi, the fluid capacitance coefficient may be obtained from the following equation: F ft = antilog (-delta p/m)...................(1) where, delta p = vertical separation of the two straight lines on a buildup or drawdown test plot, psi (kPa); and m = slope of the straight lines on a buildup or drawdown test plot, psi/cycle (kPa/cycle). While the computation of F ft from this equation is straight-forward, no clear method of finding epsilon has yet been proposed. In the original paper, Warren and Root did not elaborate on a suitable method for the determination of epsilon. Kazemi discussed the use of interference test data to find the total system porosity/compressibility product, (phi ct) f + (phi ct)ma. Using this information, a trial-and-error procedure may be applied to the pressure buildup equation procedure may be applied to the pressure buildup equation to obtain a satisfactory answer for epsilon. The optimum epsilon was defined as the value resulting in the best curve fit of the theoretical equations to the field data. SPEJ p. 324

An integrated asset modeling (IAM) approach has been implemented for the Alpine Field and eight associated satellite fields on the Western Alaskan North Slope (WNS) to maximize asset value and recovery. The IAM approach enables the investigation of reservoir and facilities management options under existing and future operating constraints. Oil, gas and water production from these fields are processed at the Alpine Central Facility (ACF). A number of local constraints exist for the asset, such as the requirement that all associated gas be used for facilities power generation, gas lift or re-injection. All produced water must be re-injected and, for pipeline integrity reasons, must be segregated from imported make-up sea water used for injection. Additionally, surface gas and water handling capacity is limited at the ACF. To further complicate matters, gas injected for EOR purposes is enriched such that it is miscible or near-miscible at reservoir conditions. These conditions create a unique and changing relationship between the oil, gas and water production, gas lift, miscible water alternating gas (MWAG) injection, lean gas injection, facilities constraints and injection availability.The IAM technology utilized for managing the WNS fields consists of full-field compositional reservoir simulation models for each reservoir integrated with a pipeline surface network model and a process facility model. Spreadsheet based allocation routines and advanced mathematical coupling algorithms complete the IAM model enabling not only the prediction of the assets' performance under the aforementioned constraints, capacities and operating conditions, but to optimize overall performance and analyze the impact of decisions. To the authors' knowledge, this is the first time integrated asset modeling has been applied to bring the entire production stream including reservoir, wellbore, surface network and process simulation together for planning and managing MWAG injection to optimize recovery from an existing development.

The Alpine field located on the North Slope of Alaska was developed using open-hole horizontal completions drilled along the maximum principle stress and dominant fault orientation (northwest/southeast). Open-hole completions were considered the best completion option based on rock mechanics, improved profile surveillance and cost. The original Alpine field development plan did not include hydraulic fracture stimulation based on the reservoir characterization. Well performance had proven to be economic in this Jurassic, marine sandstone without hydraulic fracturing, until drilling the CD2–37 well in 2003. The poor reservoir quality found in the southwestern edge of the field required stimulation to produce at economic rates. A hydraulic fracture treatment was performed resulting in a 200% production increase. Over the past three years, a stimulation program has evolved with improvements in candidate selection, performance and predictability. Future plans include continuing to stimulate candidate wells by incorporating horizontal completion technologies that are more conducive to multiple fracture technology. This paper presents the evolution of the candidate selection process and a review of reservoir characterization as a result of the significant production improvements gained from hydraulic fracturing. We will also present how the Alpine full field model predictions have impacted the candidate selection process and discuss the stimulation design history that includes fracture fluid changes resulting from core analyses. Introduction The reservoir mechanism impeding maximum well deliverability was initially considered to be dominated by reservoir damage from brine imbibition based on core work comparing brine-based and oil based drilling fluids.1 Based on the 2005 core study results, avoiding exposure to brine or any other water based fluids was the standard mode of operation. For this reason, diesel based fracture fluids were used to perform the first three fracture stimulations. The first fracture stimulation was performed in 2004 on the CD2–37 well in a poor quality area of the reservoir on the southwestern edge of the field. The next two stimulation candidates selected in late 2004 and performed in 2005 were based on the thickness, reservoir quality and "skin damage" assumed to be present from using brine-based drilling fluids. The initial stimulation results were encouraging. Logistics is a large obstacle at Alpine due to "ice road only" access for fracture stimulation equipment and diesel transport to location. These logistic issues along with the increasing diesel fuel costs led the team to consider reviewing alternative fracture fluid systems to determine the impact on well performance versus continued use of diesel based frac fluids. Various fracture fluid systems were reviewed and a borate cross-linked low polymer loading system was selected based on the high retained permeability results. The six fracture stimulations performed in early 2006 returned incremental rates in excess of 100% over the predictions at sanction. Post-frac production results suggest that vertical communication through the entire reservoir section, achieved through fracturing, is a dominant mechanism for improved production performance. Connecting the stimulated wells in the full field model (FFM) to all grid cells above and below the estimated fracture length improved the prediction compared to previous PI or skin adjustment techniques. Using this methodology, the number of potential fracture stimulation candidates has increased by 200%.

This paper was prepared for presentation at the 1999 SPE Western Regional Meeting held in Anchorage, Alaska, 26–28 May 1999.