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This paper presents a study for plunger lift characteristics to dewater tight-gas wells operated in the Piceance basin of Rocky Mountains with multiple-well pads and surface pipeline network. The wells' TVDs are about 6000 ft with deviated paths, and the water-gas-ratio (WGR) is 40~80 stb/MMscf. The objective is to understand the optimal operating conditions for reasonably controlling deliquification without severe liquid surge while maintaining maximum gas production.The IPR and reservoir depletion are based on tight gas model, which considers the transient IPR due to very low matrix permeability, hydraulic-fractures and drainage radius. A transient dynamic multiphase flow analysis has been performed to investigate the plunger lift effectiveness, performance and optimization for different scenarios. Simulation runs were performed for early, middle and late field life which corresponds to different reservoir pressure and productivity index. It shows that liquid loading becomes severe and production becomes unstable (heading) with decreased reservoir pressure and increased water influx. Eventually the well production can stop due to liquid loading. Plunger lift helps to maintain the production and reduce the instability. A network model with 22 wells on a pad has been built to study the interaction of the system and the liquid surge control strategy.Plunger-lift process for tight gas wells with liquid loading problems needs integrated dynamic modeling for both reservoir and wellbore systems. The philosophy of optimization is that, the reservoir and wellbore system should be the "master" for production optimization, and surface control should serve as a "slave" system.
This paper presents a study for plunger lift characteristics to dewater tight-gas wells operated in the Piceance basin of Rocky Mountains with multiple-well pads and surface pipeline network. The wells' TVDs are about 6000 ft with deviated paths, and the water-gas-ratio (WGR) is 40~80 stb/MMscf. The objective is to understand the optimal operating conditions for reasonably controlling deliquification without severe liquid surge while maintaining maximum gas production.The IPR and reservoir depletion are based on tight gas model, which considers the transient IPR due to very low matrix permeability, hydraulic-fractures and drainage radius. A transient dynamic multiphase flow analysis has been performed to investigate the plunger lift effectiveness, performance and optimization for different scenarios. Simulation runs were performed for early, middle and late field life which corresponds to different reservoir pressure and productivity index. It shows that liquid loading becomes severe and production becomes unstable (heading) with decreased reservoir pressure and increased water influx. Eventually the well production can stop due to liquid loading. Plunger lift helps to maintain the production and reduce the instability. A network model with 22 wells on a pad has been built to study the interaction of the system and the liquid surge control strategy.Plunger-lift process for tight gas wells with liquid loading problems needs integrated dynamic modeling for both reservoir and wellbore systems. The philosophy of optimization is that, the reservoir and wellbore system should be the "master" for production optimization, and surface control should serve as a "slave" system.
The last decade has spotted a tremendous upsurge in casing failures. The aftermaths of casing failure can include the possibility of blowouts, environmental pollution, injuries/fatalities, and loss of the entire well to name a few. The motivation behind this work is to present findings from a predictive analytics investigation of casing failure data using supervised and unsupervised data mining algorithms. Scientists and researchers have speculated the potential underlying causes of failure but to date this type of work remains unpublished and unavailable in the public domain literature. The study assembled comprehensive data from eighty land-based wells during drilling, fracturing, workover, and production operations. Twenty wells suffered from casing failure while the remaining sixty offset wells were compiled from well reports, fracturing treatment data, drilling records, and recovered casing data. The failures were unsystemic but included fatigue failure, bending stresses from excessive dogleg, buckling, high hoop stress on connections, and split coupling. The failures were detected at various depths, both in cemented and uncemented hole sections. Failures were spotted at the upper and lower production casing. Using a predictive analytics software from SAS, twenty-six variables were evaluated through the application of various data mining techniques on the failed casing data points. The missing data was accounted for using multivariate normal imputation. The study outcome addressed common casing sizes and couplings involved with each failure, failure location, hydraulic fracturing stages, cement impairment, dogleg severity, thermal and tensile loads, production-induced shearing, and DLS. The predictive algorithms used in this study included Logistic Regression, supervised Hierarchal Clustering, and Decision Trees. While the descriptive analytics manifested in visual representations included Scatterplot Matrices and PivotTables. A combination of the causes of failure were identified. A total of five statistical techniques using the aforementioned algorithms were developed to evaluate the concurrent effect of the interplay of these variables. Nineteen variables were believed to possess a high contribution to failure. Scatterplot matrix suggested a complex correlation between the total base water used in fracturing simulation and casing thickness. Logistic Regression suggested nine variables were significant including: TVD, operator, frac start month, MD of most severe DL, heel TVD, hole size, BHT, total proppant mass, cumulative DLS in lateral and build sections variables as significant failure contributors. PivotTables showed that the rate of casing failure was highest during the winter season. This investigation is aimed to develop a thorough understanding of casing failures and the myriad of contributing factors to develop comprehensive predictive models for future failure prediction via the application of data mining algorithms. These models intend to provide a theoretical and statistical basis for cost-effective, safe, and better drilling practices.
Many tight gas wells produce at rates below their potential, due to water loading. Plunger lift is often applied to remove produced (or condensed) water, reduce bottomhole flowing pressure, and increase both gas production rate and ultimate recovery. Previous authors have discussed dynamic models of the plunger lift process. However, these previous models considered only stabilized reservoir production. Because of the assumption that reservoir production is stabilized, these older models have only limited applicability to tight gas wells. This paper presents a study of the application of plunger lift to the problem of water removal from tight gas wells. A numerical simulation model was developed which includes gas flow in the reservoir, wellbore/annulus effects, and dynamic plunger lift cycles. Transient reservoir performance is an important feature of the new model. Transient reservoir performance is a significant factor for tight gas reservoirs, especially as average reservoir pressure decreases during the life of the reservoir. Field data from tight gas wells with plunger lift for water removal can be more thoroughly analyzed using the new simulation model. Calibration of model parameters with field cases allows the plunger lift design to be optimized for a particular well. Improved understanding of the plunger lift process for tight gas wells with water loading problems may lead to more efficient water removal, increased gas production rates and recovery, and longer well life. Introduction As gas reservoirs are depleted, the removal of produced water from the wellbores becomes less efficient. The accumulation of produced water in the wellbore (called loading) can significantly reduce gas production rates by increasing bottomhole flowing pressures. Continued accumulation of water in the wellbore can eventually cause a well to die. Plunger lift has proven to be a successful method of removing produced water from the wellbore under a variety of operating conditions.1–4 Plunger lift is an artifical lift method characterized by the cyclic travel of a plunger up and down the tubing string. The plunger reduces the fallback of liquids as the plunger and slug of liquid above the plunger are pushed to the surface by pressure below the plunger. This pressure below the plunger is supplied by reservoir production, and by the expansion of gas stored in the tubing/casing annulus. Plunger lift results in more efficient use of reservoir energy to the removal of liquids from the wellbore. However, the plunger lift process is complex and can be difficult to design and analyze. Early methods of analysis and design utilized static models.5–6 In recent years, computer modeling has provided a tool allowing the development of more useful dynamic models of the plunger lift process. Several authors have discussed dynamic numerical models developed to allow analysis and optimization of plunger lift. The assumptions made in the development of these models and the level of detail included varies. Lea7 developed an early dynamic model of the plunger rise phase of the plunger lift process, showing that plunger velocity changes as the plunger travels up the wellbore. Lea's work indicated that annular gas requirements calculated using the earlier static model of Foss and Gaul5 were up to 16% too high. Reservoir performance was modeled using the Rawlins and Schellhardt8 deliverability equation for stabilized reservoir production (considering only Darcy flow). Marcano and Chacin9 developed a dynamic model of the entire plunger lift cycle. A major contribution of this work was modeling of fallback of liquid past the plunger. However, Marcano and Chacin used an IPR equation (for stabilized reservoir production) to describe reservoir performance. Baruzzi and Alhanati10 used dynamic modeling to analyze the operation of plunger lift for oil wells. Their study showed that the minimum length buildup period that will provide just enough energy for the slug of liquid above the plunger to be lifted results in the highest possible liquid production rate. Baruzzi and Alahanati also used an IPR equation (stabilized production) to describe reservoir performance.
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