Developing a predictive reservoir model involves determination or estimation of key reservoir components, which can vary through the rock volume. Sophisticated, 3-D grid models usually require significant input data and are built for conventional reservoirs producing in Darcy flow. Production from the Barnett shale is not conventional. Shale-rock gas flow involves a complex mixture of free and adsorbed storage and production mechanisms. Free gas can be stored in the microporosity, natural fractures, or thin lamination existing or created during hydraulic fracturing. Adsorbed gas is contained in the organic material randomly distributed in the bulk rock. Horizontal, multistage-fractured wellbores add another level of complexity. Massive hydraulic fracturing of horizontal shale has shown complex fracture networks are created along the wellbore. Mapped data suggests multiple fracture planes are created during injection. These fracture planes can be irregular in length and are not always symmetrical. Conventional reservoir models cannot handle this level of complexity. A new, 3-D, four-phase, nonisothermal, multiwell black oil and "Pseudo-compositional" simulator that allows placement of multiple transverse fractures along the horizontal has been developed. Its ability to model horizontal, multiwing, transverse fractures and account for all three reservoir phases, including injected fluid, makes this model more predictive of production. This paper uses mapped fracture dimensions of horizontal wells in the north Texas Barnett (NTB) to build a reservoir model. Comparisons of model production to real production are made to demonstrate the model's predictive ability. Introduction Horizontal drilling and completion of the NTB began in 1991 and has more than 6,000 horizontal wellbores on production to date. Numerous well construction types and completion strategies that have been investigated in the NTB are listed below.Cemented and uncemented linersCemented production casingProduction casing with mechanical/swell packers and frac portsCemented and uncemented casing using jet-tool perforating and fracturing (East et al. 2004) The most common completion is the cased, cemented production string using the pump down perf-and-plug method of multistage completion (Smith and Starr 2008). Horizontal Completion Design The completion phase of the horizontal Barnett shale is thought to have the most effect on production outcome. Horizontal azimuth for the NTB is usually chosen so that hydraulic fractures created bisect the wellbore in a transverse manner. This option is preferred because it opens multiple fracture planes along the entire lateral length, maximizing the total surface area to flow. Some of the obvious design considerations are:• Lateral length• Fracture spacing or initiation points• Number of stages• gal/ft, lbm/ft• Total gallons and total lbm of proppant per wellbore

The north Texas Barnett shale illustrates the successful commercialization of an unconventional reservoir. However, it took 17 years to evolve from pumping crosslinked gel (XLG) carrying more than 1 million lbm of proppant per job to sand waterfracs (SWFs) consisting of large volumes of water with friction reducer and small quantities of sand. This transition to SWF stimulation opened the door for widespread development that has advanced the Newark East (Barnett shale) to the largest producing gas field in Texas.This paper investigates Barnett completion strategy from 1993 to 2002. The 393-well data set includes completion, reservoir, and production data. Unique data-evaluation tools and techniques were used to investigate various completion and reservoir parameters to determine their effects on production (Shelley and Stephenson 2000;Zangl and Hannerer 2003).We found that production results show a broad scattering when crossplotted with various completion and reservoir inputs. This result is not uncommon when analyzing field data. However, general trends were identified through comparisons of large numbers of wells. These trends were confirmed through the use of moreadvanced data-mining techniques, which included self-organizing mapping (SOM) of data. The results show that SWF-type stimulation of the Barnett outperformed to varying degrees XLG treatments for the five reservoir types used in this evaluation.

Copyrbht W9S, .%dely of Patmleum Enghmam, Inc TMi paper was pmparad fu~senfalfon at ffss i 998 SPE Perndan &sin Ofl and Gas Recovery Conkrarwa held in Mkfland, Tess% 2%27 Mad 199S. This paper was seiedad forpeeentstfon by an SW Program COmrnittes foflmvkg review of intmmatbn cantafnad in an abtract eufnnfnd by the author(s). Centenls of fhe pspsr, as mfd ha~nOt~n~w ffw sodety of i%tdeum EM"naars sw *e subject to cmrecfM by the author(a). The matariaf, as pmantad, does ml neceaestify reffact any gmsftion of the Saciefy of PaWdewn Enginaars. Rs ofilcars or members. Papers pmaentsd at SPE meetfv ara subjed to PubKoaiion dew by EdMal Committees of tha Society of Petroleum Er@eers. Ekfmn!c repmddcm, delTiMtfOm or steraga C4 any pert of ths paper for canmerdal pwpoaes wfthout the vnftten mnaent of the SOsisly of Petroleum Enginesrs Is fwohitited. permission to rapmduce in print is metrtcted to an abstract of not more than 300 words iffustrai%ns may not be cop+ed. Tha abatrad must mntain conspkwous adamwledgment of where and by whom the paper was presented Write Librshn, SPE, PO. SOS S33S36, Ffiihardson, TX 7S0S3-3S3S, U.S.A. iax 01-S72-952-94SS. AbstractThe quality and quantity of information available in the public domain is growing rapidly, and companies are generating inhouse databases to track this explosion of information to improve operating and service performances. The hardware and software used to obtain and manipulate massive amounts of information are constantly improving. All these events have created an opportunity to evaluate the complex interaction of variables and quanti& how they relate to a required result.The subject of this paper is an analysis of granite wash completions in the Red Deer Creek field, Roberts County, TX. The analysis uses an artificial neural network (ANN). Specific areas of interest include any controllablelquanti fiable aspect of a well's completion and stimulation procedure-including fluid selection, treatment volume, proppant type and volume, pump rates, and perforation distribution-that affects production outcome. Relevant conclusions are drawn that quanti~the effects of reservoir, well, and completion factors on production results. This paper will document a test of methodology on the completion of a new well that resulted in a two-fold gas production increase compared to four previous completions that used only conventional completion optimization techniques.

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.

Horizontal well drilling and hydraulic fracturing have become the enabling technologies for unconventional reservoir development. From tight gas, to oil and gas-producing shales and coal bed methane, all these resources rely on hydraulic fracturing for its commercial viability. The primary goal of the completion in these ultra-low permeability formations is to provide a conductive path to contact as much rock as possible, through the use of multistage hydraulic fractures along a horizontal lateral. Reservoir contact is optimized by defining the extent of the lateral length, the number of stages to be placed in the lateral, the fracture placement technique and job size. Fracture conductivity is determined by the proppant type and size, fracturing fluid system as well as the placement technique. While most parameters are considered in great detail in the completion design, the fracture conductivity receives lesser attention. On one side many feel that in extremely low permeability formations hydraulic fractures act as ‘infinitely conductive features’, even with minimal conductivity. On another side many factors that affect the effective conductivity acting in the hydraulic fracture are poorly understood or overlooked. This can lead to a disappointing outcome with wells producing below the reservoir potential. This paper presents a technique to assess the realistic fracture conductivity at downhole conditions, describe the relationship between conductivity and productivity and its economic implications in proppant selection. The effects of transverse fractures, low areal proppant concentration and flow dynamics, are also considered among other variables. Fracture modeling and actual field results will be presented to illustrate the optimization process. The case histories included in the paper show the successful implementation of this method in shale gas and liquids rich formations.