A distinct shift in wellbore fracture stimulation events has occurred within the Western Canadian Sedimentary Basin (WCSB) over the last 5 years. New designs, commonly referred to as "increased fracture intensity designs," are characterized by an increased number of fracture stages, decreased fracture spacing, and resulting increases in water and proppant required per stimulation. Existing technology applied in increased fracture intensity designs include: Open Hole Ball and Seat technology, Coil Activated sleeves, Plug and Perforating, as well as hybrid designs that combine several technologies.
Increased fracture intensity designs have contributed to improved production rates and increased reserves and, as a result, have quickly become the preferred approach to hydraulic fracture stimulation of the reservoir. Promising hydraulic fracture designs and decreased spacing designs run the risk of being applied broadly without discrimination.
Without proper retrospective or hindsight, there is a risk of over applying this new approach with false assurances of its success rates. It is therefore important to determine whether and at what point increasing fracture intensity generates diminishing returns.
This paper provides 3 retrospective case studies within the regions of the greater Montney and Cardium formations where increased fracture intensity designs have led to decreased well production as well as decreased reserve allocation. We further examine the various components of increased fracture intensity designs to pinpoint areas where design optimization may have prevented these outcomes.
We explore the implementation and development of information technology at Jackson Hewitt Tax Service, the second largest tax service in the nation. We discuss the problems the company faced over the period 1990‐1993, including a period of high growth and critical dependence on technology to operate its business. A number of systems had to be implemented to solve these problems and allow the company to continue its rapid growth without collapsing due to lack of technology infrastructure. The tight seasonal schedule the company was forced to operate within contributed to the difficulty of development, testing and operations.
The AIAA Artificial Intelligence Design Challenge is eccentric and intriguing, combining features from traveling salesman and stochastic optimization problems together with several side constraints thrown in for additional appeal. The challenge is to devise a solution algorithm that will reliably find optimal (or near optimal) solutions and can be extended to more general problems. We present our algorithm for this challenge in this paper. The fundamental algorithm for finding near-optimal solutions is disarmingly simple and can be made quite efficient through the introduction of several bounds on the problem. The reader will quickly discover that these bounds do not require a deep understanding of traveling salesman algorithms and should enjoy devising additional bounds to add to the potpourri.
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