Field Data Validation of a General Model for High-Performance Fractures in Deviated High-Rate Wells | SLB

Field Data Validation of a General Model for High-Performance Fractures in Deviated High-Rate Wells

已发表: 09/20/2010

Premium
Schlumberger Oilfield Services

The use of deviated trajectories in deepwater completions is legitimately advocated by drilling constraints. However, production considerations have not been given the attention they deserve. A recently developed comprehensive semi-analytical model, using distributed volumetric sources, offers a flexible and powerful computational tool that enables rigorous evaluation of a wide variety of possible flow patterns, including augmented wellbores due to “halo effects”, combined flow towards the fracture and towards the remaining flowing perforations not connected to the fracture, turbulent flow effects and possible different levels of damage within the fracture and gravel pack regions.

While the generalized high-performance fracture (HPF) model clearly indicates the well performance penalty for hydraulically fracturing a deviated well, for many operators, the main reason for the hydraulic fracture is sand-control. The high-performance fracturing (frac-pack) completion has been proven to last for a significantly longer period, and through much greater cumulative production than conventional (non-fractured) cased-hole gravel pack (GP) completions. A key reason for the success in deviated wells may be that even though much of the flow to the well may bypass the hydraulic fracture, as long as flow to the well is mostly uniform, the potential for failure is low.

This paper provides a broad-based validation of the model using field data from a key deepwater region. Production and pressure transient data, and open and cased-hole logs are used to evaluate the most likely flow geometry for each field case, and the results are compared to HPF model output. This provides a global assessment of the model versatility in modeling the production behavior of actual wells. This, in turn, enables use of the model to benchmark the performance of any given well against its predicted potential (if optimal drilling and completion practices had been employed).

Feature.PageContent.AbstractPremiumContent.Title
Feature.ModularContent.Login.SignInOrRegisterButtonText