Day 2 Wed, April 27, 2022最新文献

{"title":"First Successful LWD NMR T1 and T2 Measurements in Unconventional Source Rock with Harsh Drilling Environment: A Case Study from Kuwait","authors":"Anar Abdulkarim, A. Aki, R. Balliet, M. Al-Azmi, F.B. Al-Otaibi, G. Joshi","doi":"10.2118/209263-ms","DOIUrl":"https://doi.org/10.2118/209263-ms","url":null,"abstract":"\u0000 The thickness and thermal maturity of the Najmah formation presents a favorable prospect for commercial exploitation of unconventional shale gas. Estimating reservoir storage volume is one of many formation-evaluation objectives when assessing an unconventional reservoir.\u0000 The presence of kerogen has significant effects on several downhole logging sensor measurements. An operator used nuclear magnetic resonance (NMR) measurements to evaluate total fluid-filled porosity for a reliable estimate of the reservoir storage volume in source rock. While wireline NMR has historically provided a large segment of unconventional reservoir logging, logging-while-drilling (LWD) NMR provides an alternative method for assessing the total fluid-filled porosity within unconventional reservoirs.\u0000 This paper provides a case study in the Najmah Shale Formation, where an operator used an LWD penta-combo system (gamma ray, electromagnetic wave resistivity, azimuthal bulk density, thermal neutron porosity, high-frequency multipole azimuthal sonic, ultrasonic caliper, and NMR sensors) in real time. The system provided petrophysical and geomechanical evaluation with well inclinations greater than 50° in 16-ppg oil-based mud.\u0000 T1 and T2 measurements were acquired with an LWD NMR sensor while drilling and during wiping passes. These measurements provided an additional dimension to differentiate clay-bound water from organic hydrocarbons, with good correlation to existing core data in real time. Reservoir characterization of the Najmah Formation using LWD measurements is currently underway to provide a better understanding of reservoir quality, hydrocarbon potential, and reservoir storage capacity of this unconventional source rock. Acoustic velocities play an important role as input to geomechanical information, including the stress regime, principal stress orientation identification, and rock moduli estimation. An azimuthal acoustic tool measuring shear velocities at 360° around the borehole provides answers for the first two attributes. Estimation of formation rock moduli requires accurate acoustic properties and density log inputs, as provided by high-frequency sonic and azimuthal density measurements.\u0000 In wells above 60° inclination, it becomes almost impossible to run wireline logging, thus LWD quad-combo with a high-frequency azimuthal acoustic tool is a viable solution for this environment. Additionally, it is an advantage to run LWD while in drilling mode to save rig time and optimize well construction costs.","PeriodicalId":224766,"journal":{"name":"Day 2 Wed, April 27, 2022","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123312272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient Reservoir Management with a Reservoir Graph Network Model","authors":"Zhenyu Guo, Wenyue Sun, S. Sankaran","doi":"10.2118/209337-ms","DOIUrl":"https://doi.org/10.2118/209337-ms","url":null,"abstract":"\u0000 Efficient reservoir models are more desirable for fast-paced reservoir management. Moreover, due to the complexity of flow underground, it is also essential to capture the most fundamental physics for model reliability. Though running fast, pure data-driven models often suffer from the issues associated with interpretability, physical consistency, and ability to forecast. On the other hand, we have used full-physics simulation models to mimic and investigate hydrocarbon systems for over several decades. However, considering its infrequent model updates related to high model complexity, it is a big challenge to manage reservoirs using full-physics models in short cycles. The objective here is to propose an approach that blends reservoir physics with data-driven models to fit in the framework of dynamic reservoir management.\u0000 We propose to use a reservoir graph network (RGNet) modeling approach based on diffusive time-offlight (DTOF) concept to simulate reservoir behaviors. By assimilating field observation data (such as pressure and rates), an RGNet model can be used for future predictions, scenario studies and well-control optimizations. By discretizing DTOF of a three-dimensional system with multiple wells, RGNet simplifies the system into a graph network represented by a set of one-dimensional grid blocks that significantly reduces the system complexity and run time. RGNet can also handle multiple flow problems with various types of physics. In this work, we investigate multiple grid connectivity methods to develop reliable and parsimonious models for large scale systems. In addition, we propose a more robust method to assimilate static pressure data, when available.\u0000 We applied the proposed approach to a synthetic example. Two different history matching algorithms, the ensemble smoother with multiple data assimilation (ES-MDA) and an adjoint-based method, are compared. While ES-MDA provides the capability for uncertainty analysis, an adjoint-based method generally requires fewer simulation runs to generate a posterior model. With the proposed gridding methods, RGNet model calibration can be achieved without system redundancy and spurious longdistance well-connectivity. Also, by using a more stable pressure matching technique, we show that pressure data are better matched and reservoir volume is accurately characterized.\u0000 RGNet provides a novel hybrid physics and data-driven reservoir modeling method to fit in closed-loop reservoir management. As RGNet models are combined with fundamental flowing physics, the calibrated model parameters are easy to interpret and understand. An RGNet model runs with far less computational cost than required by a full-physics model, which allows it to be a more practical solution to history match, predict and optimize real assets.","PeriodicalId":224766,"journal":{"name":"Day 2 Wed, April 27, 2022","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124316277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Employing Regression Analysis to Demonstrate the Impact of Hyperbolic Decline Curve Parameters on Long-Term Production Forecast Accuracy for Unconventional Oil and Gas Production in the Bakken and Barnett","authors":"Nathaniel Younk, B. T. Hoffman","doi":"10.2118/209332-ms","DOIUrl":"https://doi.org/10.2118/209332-ms","url":null,"abstract":"\u0000 Forecasting production from unconventional reservoirs is challenging because of the uncertainty that arises from intricate fracture networks, complex transport mechanisms, and convoluted flow configurations. The accuracy of decline curve analysis for such reservoirs has been questioned due to the limited amount of long-term production data available. That being so, some unconventional reservoirs, such as the Bakken and the Barnett, have produced for 15-20 years, providing an adequate amount of data to validate the accuracy of the hyperbolic decline curve method, shed light on proper parameters – b and Di, and determine the amount of production history necessary to trust regression techniques.\u0000 To test this, an extensive and versatile regression analysis model was built in Python using least squares optimization to match specific durations of production data – first 6 months, first year, first two years, etc. The model outputs the optimal parameters – b and Di –to match the specific duration. Additionally, fixed b values from 0.5 to 1.5 are tested where only Di is optimized through the model. To understand how accurately the models predict production, they are validated against the most recent 5 years of data, which was not included in the matching period. For a statistically significant sample size, around 700 wells in the Bakken and 1800 wells in the Barnett with start dates between 2005 and 2010 were used.\u0000 The results show that in order to have confidence in the model's ability to predict production, more than 3 years of production data must be available. If 3 years of data is not available, the hyperbolic exponent, b, should be set close to 1.0 for Bakken wells (and likely other unconventional liquid rich wells) and between 1.0 and 1.2 for Barnett wells (and likely other unconventional gas wells). Additionally, the initial nominal decline rate, Di, should be chosen in accordance with the hyperbolic exponent. Not only do these guidelines result in satisfactory, long-term predictions, but they mitigate any significant error influenced by the underlying relationships between b and Di. These curve-altering relationships induce both positive and negative impacts on the predictions. If b is improperly chosen, overestimation in late-life production profiles may ensue. Alternatively, if Di is improperly chosen, early-life production may be too high.\u0000 Since production forecasting is a necessity for a company to determine its present value, this paper provides knowledge and guidance regarding forecasting procedures and parameter settings for North American unconventional operators. Using decline curve analysis to accurately predict oil and gas rates is pertinent to the longevity of these unconventional reservoirs.","PeriodicalId":224766,"journal":{"name":"Day 2 Wed, April 27, 2022","volume":"262 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115877219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comprehensive Review of RTA/DCA Methods in Unconventional Reservoirs","authors":"Hakki Aydin, Narendra Boppano, M. Yurukcu, Shuhao Liu, C. Yegin, C. Temizel","doi":"10.2118/209321-ms","DOIUrl":"https://doi.org/10.2118/209321-ms","url":null,"abstract":"\u0000 Rate Transient Analysis (RTA) and Decline Curve Analysis (DCA) have been utilized as critical tools in calculation of oil production for unconventional reservoirs. Due to the ultra-low permeability of these wells, time scales of flow regimes are different than those of conventional reservoirs, where transient regimes last longer, and the decline behaviors change, factors that make forecasts more challenging. There are several RTA/DCA methods for originally developed conventional and unconventional reservoirs including recent techniques. However, petroleum engineers require a single comprehensive reference where RTA/DCA methods are covered with detailed explanations, as well as an outline of their assumptions, limitations, strengths, and appropriate applications. This study tackles the lack of such a resource, delivering a comparative work that includes theory, practice, and examples.\u0000 A comprehensive literature review has been carried out to investigate the RTA/DCA methods for unconventional reservoirs in detail, explore the newest techniques and the different methods repurposed from existing conventional approaches with a longer history of use, robustness, and applicability. We also provide a detailed account of the limitations and the advantages of different methods when applied to different types of fields. We achieve this by developing real field applications in different parts of the world and discussing the challenges and opportunities of each RTA/DCA method for a particular type of well.\u0000 RTA/DCA methods have shown to be a practical tool for both conventional and unconventional reservoirs, and can be applied across many types of oil and gas wells throughout the world. This work shows the parameters best suited for a successful application of these recovery methods in unconventional sites. Moreover, the evidence collected here will serve as a resource for engineers looking for a summary of the most important criteria to be followed in order to apply oil recovery methods in new wells. We expect that future oil production in unconventional reservoirs can be boosted by the results provided in this work.\u0000 The novelty of this study centers on the lessons drawn from the real-world applications of RTA/DCA methods like Duong's, or stretched exponential decline, to recover oil from unconventional reservoirs. We expect these lessons to define the proper utilization of distinct methods for different reservoirs in future studies and the field.","PeriodicalId":224766,"journal":{"name":"Day 2 Wed, April 27, 2022","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115210867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Case Study on InSAR as a High Frequency Decision Making Tool for SAGD Operations","authors":"Courtney D Lucente, Ajinkya V Koleshwar, G. Falorni","doi":"10.2118/209251-ms","DOIUrl":"https://doi.org/10.2118/209251-ms","url":null,"abstract":"\u0000 Reservoir surveillance is a key component of SAGD operations. There are several widely used surveillance techniques which vary in spatial and temporal coverage, resolution, and cost. The most common of which include pressure and temperature observation wells and 4D seismic. This study aims to demonstrate the value of InSAR as a decision-making tool over operating SAGD pads when used in a coordinated surveillance program alongside existing techniques.\u0000 Results acquired from conventional surveillance techniques such as 4D seismic are often compared to those from InSAR at the scale of one of the data sets. A frequent challenge when making these comparisons is different acquisition frequency and coverage. This study compares the relative results from each data set to determine if the same conclusions could be drawn from InSAR as from seismic at varying scales. To do this, SAGD wells are divided into segments at various scales (half, third and quarter well). Results from InSAR and 4D seismic are extracted for each segment and statistics analyzed to determine if InSAR and 4D seismic lead to the same relative outcome and thus might lead to the same operational decisions.\u0000 Results will focus on the ability of InSAR to provide decision making information to SAGD operators like that of other surveillance techniques, but at higher temporal frequency. In particular, the scale at which InSAR provides comparable results to 4D seismic will be investigated and how using InSAR in coordination with seismic may result in more frequent well production optimization.\u0000 Previous attempts to correlate InSAR to existing SAGD surveillance techniques have shown mixed, though often promising results. Difficulties have arisen from attempts to directly compare discrete InSAR values to those of other techniques, often resulting in poor regression coefficients and a lack of confidence. Qualitative comparisons of gridded surfaces provide little insight on how to utilize the InSAR data. This study will demonstrate the scale at which InSAR can provide information to make operational SAGD decisions.","PeriodicalId":224766,"journal":{"name":"Day 2 Wed, April 27, 2022","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124751072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time Series Analysis as an Alternative for Decline Curve Analysis in Unconventional Plays","authors":"M. Malaieri, R. Matoorian, R. Shor","doi":"10.2118/209261-ms","DOIUrl":"https://doi.org/10.2118/209261-ms","url":null,"abstract":"\u0000 Quick and reliable forecasting of production data is still challenging in unconventional plays, even with the variety of modifications proposed to Arps decline curve analysis (DCA). Machine learning revealed promising results when enough samples were accessible to train and validate the predictive model. However, this black-box model is inaccurate for unseen samples, challenging to generalize, and requires too much data. We attempted to present an alternative procedure to solve this problem —a fast and reliable method outperforming current approaches.\u0000 In this study, we implemented univariate and multivariate times series analysis (TSA) to forecast production rate in the different scales (wellbore, field, and pad scales) where DCA failed to provide an appropriate fit beforehand. TSA is straightforward and enables recognition of the pattern in observation samples. Cyclic fluctuation due to seasonal changes in price and operational hours can be detected and indirectly considered in time series models like ETS (Exponential Smoothing) and ARIMA (Auto-Regressive Integration Moving Average). However, for the direct considerations of these critical parameters, Vector Auto-Regressive (VAR) models have the flexibility and ability to be configured with multiple variables and can capture more complexities.\u0000 This simple and quick procedure applies on any scale from the wellbore to the field scales. To evaluate the performance, the TSA method has been applied and tested on data from the Duvernay shale in Western Canada. On the wellbore scale, modified DCA models forecast production rate with over/underestimation, even where enough observations are available, and if the well has shown a declining trend in the production. In the same wells, TSA provides a better fit and outperforms the DCA. In the field and pad scales, DCA could not draw a fitting model as production had a growing trend due to ongoing field developments. In contrast, TSA could realize the trend in the production data and successfully create the forecasting model. Price and production hours were added to the time series model as influential features on production. The model could forecast all the parameters simultaneously. In sum, TSA is a reliable and flexible alternative for DCA and can be implemented on production data in any scale.","PeriodicalId":224766,"journal":{"name":"Day 2 Wed, April 27, 2022","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128556088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Correlations of the Unconventional Reservoirs Properties and the Huff-n-Puff Gas EOR Potential Performance","authors":"Adi Junira, Reza Ganjdanesh, R. Williams, J. Nohavitza, K. Sepehrnoori, Wei Yu","doi":"10.2118/209301-ms","DOIUrl":"https://doi.org/10.2118/209301-ms","url":null,"abstract":"\u0000 Cyclic (huff-n-puff) gas injection as a method of increasing oil recovery from unconventional reservoirs with low permeability has shown sufficiently positive results to justify its implementation in a number of fields. Nonetheless, not all of such injection results in encouraging results. Some field implementations of huff-n-puff results in marginal oil recovery increase from that of primary production case. The characteristics of an unconventional reservoir may have something to do with the appropriate choice of injection gas for use in that reservoir. For instance, a reservoir with oil that is low in heavy components (C7+) from molar fraction standpoint might not a proper candidate for a huff-n-puff field gas injection. In other words, for such type of injection gas to perform well in increasing oil recovery, the in situ oil should have a certain level of C7+ molar fraction. This study aims at finding out what types of gas are the proper choices for huff-n-puff injection gases in unconventional reservoirs with specific characteristics. In a sense, it can be considered as an attempt to create a kind of screening criteria related to the injection gas suitable for huff-n-puff EOR in such an unconventional reservoir. In achieving that, a number of models which are based on real field data of a number of producing oil fields in continental United States are used in numerical simulations. The analysis on the results provided insights on the proper injection gas selections as tabulated in this writing.","PeriodicalId":224766,"journal":{"name":"Day 2 Wed, April 27, 2022","volume":"515 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123080551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the Pressure-Dependent Equivalent Permeability Evolutions for Shale Matrix: Experiments and Modeling","authors":"Yun Yang, Shimin Liu, An Liu","doi":"10.2118/209291-ms","DOIUrl":"https://doi.org/10.2118/209291-ms","url":null,"abstract":"\u0000 The ability to model and predict matrix permeability changes during reservoir depletion is critical for accurate analysis of long-term production performance in unconventional gas reservoirs (UGRs), including shale gas and coalbed methane reservoirs. Yet, flow quantification in the nanoporous matrix is still challenging due to the complex pore structure and morphology. To understand the pressure-dependent matrix permeability evolution, this study conducted laboratory permeability measurements using pulverized samples. Equivalent permeability was estimated from the pressure decay profile for the Devonian shale sample. A novel experimental system, a differential volumetric unit, has been established and applied to capture the accurate transient gas flows for the shale sample. The measured permeability of shale exhibited overall decreasing trends with pressure depletion. Due to the presence of slip flow and Knudsen diffusion, low-pore-pressure data did not follow the same decline trend fitted by high-pore-pressure data as observed in the shale sample. This study also utilized methane as the invasion fluid to examine the adsorption effect on matrix permeability, whose value could be up to 40% lower than permeability without correction for adsorption because of the condensation of adsorbed phase at pore surface occupying available pore space. Since these tight rock matrixes are composed of micro- and nanopores, matrix permeability is primarily related to pore structure (e.g., the pore size distribution, porosity and tortuosity). Low-pressure N2 adsorption was conducted to characterize the complex pore structure of the Marcellus shale sample. A multimechanic model was proposed to predict the pressure-dependent matrix permeability based on pore structure information and investigate the effect of gas adsorption on apparent permeability. This model has successfully linked the realistic, complex pore structure with the pressure-dependent matrix permeability of shale and coal. The proposed model could be coupled into the commercially available simulator to forecast long-term production profiles for UGRs wells.","PeriodicalId":224766,"journal":{"name":"Day 2 Wed, April 27, 2022","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132839205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"State of Art Fracturing Optimization Reduces Water Blockage in Unconventional Gas/Condensate Wells","authors":"M. Ibrahim, M. Sinkey, T. Johnston","doi":"10.2118/209309-ms","DOIUrl":"https://doi.org/10.2118/209309-ms","url":null,"abstract":"\u0000 Hydraulic fracturing (fracing) is the most effective technique for improving the productivity of gas condensate reservoirs. The water used during fracing creates the conductivity needed for production, however, it will also create water blockage in the path of gas flow. The pressure and flow rate behavior of a gas condensate reservoir is distinctly different from the behavior of a solution gas drive reservoir. The producing rate is not only affected by the pressure gradient but is also a more complex function of the actual value of the flowing bottomhole pressure. Initially, the additional pressure required during flowback is needed to produce the water used during fracturing. The reservoir energy to lift this water to the surface requires more pressure drop around the wellbore. Additionally, unnecessary water used during fracing operations incrementally increases the pressure drop near the wellbore. Increased pressure drop leads the formation to reach the dew point sooner and condensate banking start to build in the fracture system. Increased condensate banking leaves valuable liquid hydrocarbon in the reservoir. Water blockages reduce well productivity and speed up the condensate damage due to the high-pressure drop required.\u0000 An innovative pattern recognition and machine learning technology was applied in real-time during fracture treatment to increase fracture complexity, improve fracture conductivity, increase diffusion surface area, and improve stage productivity index. This technology focuses on creating the most stimulated fracture surface area per volume of water injected, resulting in the same fracture surface area but with a large reduction in water injected. The reduction of the water leads to an improved well productivity index by minimizing water blockage around the wellbore.\u0000 Increasing fracture surface area per volume of frac water injected has a positive impact on the post-frac productivity of treated wells by increasing condensate production rates with less drawdown compared with traditional frac designs. In addition, using the optimum water volume has reduced the cost of fracturing operations and the cost of water flow back disposal leading to significant increases in well Net Present Value (NPV). A field case will be presented with condensate performance.\u0000 The use of real-time fracture optimization technology with the integration of rock and reservoir fluid properties leads to better well performance. Production benefits of increased condensate production result in no reserves being lost-in-place to condensate blockage. Added ESG benefits are reduced superfluous water use, pump time, and water disposal costs.","PeriodicalId":224766,"journal":{"name":"Day 2 Wed, April 27, 2022","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116750215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Use of Localized Well-Drainage Reservoir Pressure Model in Optimum Fracture Design","authors":"M. P. Ekeregbe","doi":"10.2118/209343-ms","DOIUrl":"https://doi.org/10.2118/209343-ms","url":null,"abstract":"\u0000 This study is to determine the effective use of localized reservoir pressure of each well drainage area in a multi-well reservoir system model to determine optimum fracturing design for production improvement.\u0000 A static bottom-hole pressure (BHP) survey may present different values for each well draining from the same reservoir but these different pressure values have not been incorporated into determining the performance of each individual well based on the pressure as seen by each well, rather an indeterminate average reservoir pressure is used. Fracturing as a concept of increasing reservoir permeability will further expose the well to reservoir pressure as seen by the individual well than the assumed single-value reservoir-wide pressure. This is so except when the fracture half-length is equal to the drainage length of the reservoir, connecting the whole reservoir to justify the single reservoir pressure effect if it is a single-well reservoir system. In reality, many reservoirs are multi-well reservoir systems and this simplified assumption may pose some drawbacks. The damaged wellbore area may truly be more exposed to the localized reservoir pressure as seen by the well than the apparent reservoir single value pressure assumed to determine drawdown and damage. In a multi-well reservoir system with each well-drainage area subjected to different reservoir pressures than the single reservoir pressure, fracturing and stimulation candidates screening may not present the actual effect of each well-drainage area static reservoir pressure.\u0000 This paper is to present a new model that incorporates the average reservoir pressure for whole reservoir system and the reservoir pressure as seen by individual wells in the determination of the drawdown and damage. The knowledge of the different pressures in different well locations in the reservoir system will be utilized to present a linear flow model in well fracturing to enhance better well performance.\u0000 With this new model, the actual and more realistic damage estimation and ways to achieve a linear flow for optimum performance through fracturing will be better understood. The effect of other flowing wells on the skin of the candidate well will enhance a better planning than is done now because the existing formulations are done with a single-well reservoir system in mind; no account for contributing skin of other flowing wells in the industry applied model approaches.","PeriodicalId":224766,"journal":{"name":"Day 2 Wed, April 27, 2022","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123787899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}