This project was undertaken to evaluate well potential and completion effectiveness for hydraulically fractured horizontal Marcellus completions located in Susquehanna County, Pennsylvania. This paper summarizes a study of the response of the Marcellus shale to hydraulic fractures and identifies performance drivers. How effective are these completions? How would these wells produce if they were completed and fraced differently? What are the primary controllable production drivers? How significant is geology and reservoir characteristics on well production? This paper attempts to answer such questions. Identification of major performance drivers becomes important in the design and optimization of new completions. They are not just important in enhancing production response and ultimate recoverable reserves but also prove to be important economic factors in new completion design.This study employs neural network (ANN) modeling techniques to develop a predictive model to identify performance drivers and evaluate completion effectiveness. Sensitivities performed on the predictive ANN model developed for this project, indicate that well to well variation in reservoir quality and geology has a dominate effect on Marcellus production. Issues such as fracture spacing, frac volume, perforation distribution, proppant amount and fluid volume also affect well production. A summary of completion and frac methodology for wells in this database and a ranking of controllable (Completion and Frac) and non-controllable (Reservoir and Geology) parameters that effect Marcellus production are included. This information will be useful to stake holders interested in identifying reservoir, completion and frac parameters affecting production from the Marcellus and other analogous shale.

This paper will present results from a modeling effort to derive best practices for the completion of hydraulically fractured horizontal Eagle Ford wells. The well, reservoir, completion/frac and production information used in this evaluation were provided by an operator from a five-county area in Texas. Hydraulically fractured horizontal completions pose significant modeling and evaluation challenges. This is primarily due to two issues: 1) lack of well-specific data about the reservoir/rock properties, and 2) improper assumptions used in the modeling process. As shown in this paper, a data-driven approach to modeling these completions provides a much needed pragmatic perspective, identifies high-impact parameters and provides direction about how to improve the effectiveness of these complex completions. Sensitivities performed on the predictive data model indicate that well-to-well variation in reservoir quality and geology has a dominant effect on Eagle Ford production. In addition, issues such as fracture spacing, frac volume, perforation distribution, proppant selection and wellbore length also affect well production and economics. A summary of completion and frac methodology for the Eagle Ford, in addition to a ranking of controllable (completion and frac design) and non-controllable (reservoir and geology) parameters that affect Eagle Ford production, will be included in this paper. The information contained in this paper will be useful to those interested in reservoir, completion and frac parameters that affect production from shales analogous to the Eagle Ford. Reservoir quality, completion and frac methodology effects on production results will be quantified in this paper.

The subject of this paper is the results from a data driven modeling effort to derive best practices for the completion of hydraulically fractured horizontal Eagle Ford wells. The well, reservoir and production information used in this evaluation were provided by an operator, and are from a five county area in Texas consisting of Karnes, Gonzales, Atascosa, Dewitt and Live Oak. Hydraulically fractured horizontal completions pose significant modeling and evaluation challenges. This is primarily due to two issues; 1) lack of well specific data about the reservoir/rock properties and 2) unrealistic assumptions used in the modeling process. As shown in this paper, a data driven approach to modeling these completions provides a much needed pragmatic perspective, identifies high impact parameters and provides direction about how to improve the effectiveness of these complex completions. Sensitivities performed on the predictive model developed from Eagle Ford data indicate that well to well variation in reservoir quality and geology has a dominant effect on Eagle Ford production. In addition, issues such as fracture spacing, frac volume, perforation distribution, proppant selection and wellbore length also effect well production and economics. A ranking of controllable (Completion and Frac) and non-controllable (Reservoir and Geology) parameters that affect Eagle Ford production is included in this paper. This information can be used to derive best practices and is useful in explaining well to well variation in Eagle Ford production by quantifying the effect of reservoir quality, completion and frac methodology on results.

No abstract

Mud rock “shales” by their very nature can be problematic to fracture stimulate given the wide variation in geology, rock properties and reservoir characteristics. Quite often, a positive production response from a well may be incorrectly credited to the completion and frac design when in reality the production was dominated by favorable reservoir characteristics. Conversely a poor production response from a well may be blamed on the completion and frac design when in fact poor reservoir quality is the controlling factor. The subject of this paper is a revisit of the physics behind production increases from hydraulic fracturing and results from detailed evaluations performed by experienced engineers with reservoir knowledge for the purpose of evaluating completion effectiveness and frac efficiency for shale and other low permeability formations. The findings presented show that in many cases pumping large volume sand frac designs result in an inefficient hydraulic fracture. This inefficiency is due to minimal production contribution from a relatively large portion of the hydraulically exposed fracture face and/or frac length. These findings are supported by current hydraulic fracturing theory and understanding. The evaluation methods utilized in these evaluations are not new, however they currently are under-utilized by the industry for completion and frac analysis.