Our industry has long searched for a means of evaluating the efficacy of acid stimulation of extended reach carbonate wells. Intelligent completion architectures and technologies have enabled the pre-compartmentalization of these wells, and delivered the means to selectively and remotely control zonal inflow/outflow along with the ability to make real-time measurements within these zones. This paper describes the development and in-well usage of a unique modeling technique combined with a Distributed Temperature Sensing (DTS)-enabled intelligent completion system to evaluate the coverage and effectiveness of intra-zonal acid stimulation.
This system leverages a proprietary thermal model that accounts for three in-well thermal effects occurring during compartmentalized bull-head treatments. The technique quantitatively evaluates the acid distribution and acid-rock interaction in each treated zone. The acid distribution measurement can be generated immediately following the acid treatment, enabling real-time determination of the acid volume and its distribution within the target completion interval(s). The operator can then decide if retreatment(s) is needed.
The paper focuses on the modeling technique for matrix acid stimulation in which acid is delivered by bull-heading down the tubing string to each pre-compartmentalized zone where sliding sleeves have been positioned at the lower end of each zone. The flow of acid into the tubing/perforated-casing annulus thus produces a counter-flow condition (within the annular space) to reach all perforations within that respective zone. A direct measurement of acid movement and placement is immediately generated based on a full-length DTS measurement within each zone during treatment. The paper also demonstrates the capability of the system in the generation of a type-curve. The operator can then qualitatively identify the under-treated or over-treated sections by comparing the DTS measurement results to the type-curve. A synthetic case study is used to demonstrate the technique. Full field applications using this model will be discussed in a future paper.