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ABSTRACT The industry is facing significant challenges due to the recent downturn in oil prices, particularly for the development of tight reservoirs. It is more critical than ever to 1) identify the sweet spots with less uncertainty and 2) optimize the completion-design parameters. The overall objective of this study is to quantify and compare the effects of reservoir quality and completion intensity on well productivity. We developed a supervised fuzzy clustering (SFC) algorithm to rank reservoir quality and completion intensity, and analyze their relative impacts on wells' productivity. We collected reservoir properties and completion-design parameters of 1,784 horizontal oil and gas wells completed in the Western Canadian Sedimentary Basin. Then, we used SFC to classify 1) reservoir quality represented by porosity, hydrocarbon saturation, net pay thickness and initial reservoir pressure; and 2) completion-design intensity represented by proppant concentration, number of stages and injected water volume per stage. Finally, we investigated the relative impacts of reservoir quality and completion intensity on wells' productivity in terms of first year cumulative barrel of oil equivalent (BOE). The results show that in low-quality reservoirs, wells' productivity follows reservoir quality. However, in high-quality reservoirs, the role of completion-design becomes significant, and the productivity can be deterred by inefficient completion design. The results suggest that in low-quality reservoirs, the productivity can be enhanced with less intense completion design, while in high-quality reservoirs, a more intense completion significantly enhances the productivity. Keywords Reservoir quality; completion intensity; supervised fuzzy clustering, approximate reasoning,tight reservoirs development
Wu, Yinghui (Silixa LLC) | Hull, Robert (Silixa LLC) | Tucker, Andrew (Apache Corp.) | Rice, Craig (Apache Corp.) | Richter, Peter (Silixa LLC) | Wygal, Ben (Silixa LLC) | Farhadiroushan, Mahmoud (Silixa Ltd.) | Trujillo, Kirk (Silixa LLC) | Woerpel, Craig (Silixa LLC)
Abstract Distributed fiber-optic sensing (DFOS) has been utilized in unconventional reservoirs for hydraulic fracture efficiency diagnostics for many years. Downhole fiber cables can be permanently installed external to the casing to monitor and measure the uniformity and efficiency of individual clusters and stages during the completion in the near-field wellbore environment. Ideally, a second fiber or multiple fibers can be deployed in offset well(s) to monitor and characterize fracture geometries recorded by fracture-driven interactions or frac-hits in the far-field. Fracture opening and closing, stress shadow creation and relaxation, along with stage isolation can be clearly identified. Most importantly, fracture propagation from the near to far-field can be better understood and correlated. With our current technology, we can deploy cost effective retrievable fibers to record these far-field data. Our objective here is to highlight key data that can be gathered with multiple fibers in a carefully planned well-spacing study and to evaluate and understand the correspondence between far-field and near-field Distributed Acoustic Sensing (DAS) data. In this paper, we present a case study of three adjacent horizontal wells equipped with fiber in the Permian basin. We can correlate the near-field fluid allocation across a stage down to the cluster level to far-field fracture driven interactions (FDIs) with their frac-hit strain intensity. With multiple fibers we can evaluate fracture geometry, the propagation of the hydraulic fractures, changes in the deformation related to completion designs, fracture complexity characterization and then integrate the results with other data to better understand the geomechanical processes between wells. Novel frac-hit corridor (FHC) is introduced to evaluate stage isolation, azimuth, and frac-hit intensity (FHI), which is measured in far-field. Frac design can be evaluated with the correlation from near-field allocation to far-field FHC and FHI. By analyzing multiple treatment and monitor wells, the correspondence can be further calibrated and examined. We observe the far-field FHC and FHI are directly related to the activities of near-field clusters and stages. A leaking plug may directly result in FHC overlapping, gaps and variations in FHI, which also can be correlated to cluster uniformity. A near-far field correspondence can be established to evaluate FHC and FHI behaviors. By utilizing various completion designs and related measurements (e.g. Distributed Temperature Sensing (DTS), gauges, microseismic etc.), optimization can be performed to change the frac design based on far-field and near-field DFOS data based on the Decision Tree Method (DTM). In summary, hydraulic fracture propagation can be better characterized, measured, and understood by deploying multiple fibers across a lease. The correspondence between the far-field measured FHC and FHI can be utilized for completion evaluation and diagnostics. As the observed strain is directly measured, completion engineering and geoscience teams can confidently optimize their understanding of the fracture designs in real-time.
Frantz, J. H. (Deep Well Services, Matador Resources Company, Completion Team) | Tourigny, M. L. (Deep Well Services, Matador Resources Company, Completion Team) | Griffith, J. M. (Deep Well Services, Matador Resources Company, Completion Team)
Abstract In conjunction with the industry and basin-wide paradigm shift to drilling and completing extended laterals, Matador Resources Company (the operator) made significant plans in 2018 that would focus activity toward wells with laterals greater than one-mile. One operational hurdle to overcome in this shift change was the effective execution of removing frac plugs and sand at increased depths during a post-stimulation frac plug millout. Utilization of coiled-tubing units (CTUs) had been proven to be a successful millout method in one-mile laterals, but not without risk. Rig-assisted snubbing units coupled with workover rigs (WORs) provided for less risk with higher pulling strength capabilities and the ability to rotate tubing, but would often require operational time of up to twice that of typical coiled-tubing unit millouts. The stand-alone, rigless Hydraulic Completion Unit (HCU) was ultimately tested as a solution and proved to alleviate risks in extended lateral millouts while providing operational time and cost comparable to coiled-tubing units. The operator has since performed post-stimulation frac plug millouts on ~45 horizontal wells in the Delaware Basin using HCUs. The majority of these wells carried lateral lengths of over 1.5 miles. Results and benefits observed by the operator include but are not limited to the list below: 1.) Ability to safely and consistently reach total depth (TD) on extended laterals through increased snubbing/pickup force and the HCU's pipe rotating ability 2.) Ability to pump at higher circulation rates in high-pressured wells (>3,500 psi wellhead pressure) to assist in effective wellbore cleaning 3.) Smaller footprint which allows for the utilization of two units simultaneously on multi-well pads 4.) Time and cost comparable to a standard coiled-tubing millout, particularly on multi-well pads.
Abstract Fracture treatments and stage designs for new wells have evolved considerably over the past decade contributingto significant production growth. For example, in the acreage discussed hererecently used higher intensity fracturing methods provided an ~80% increase in recovery rates compared with legacy wells. Older wells completed originally with less efficient techniques can also benefit from these more up-to-date designs and treatments using re-fracturing methods. These offer the prospect of economically boosting production in appropriately selected wells. While adding in-fill wells has often been favored by Operators as a lowerrisk option the number of wells being re-fractured has grown every year for the last decade. In this case study two adjacent Eagle Ford wells, comprising a newly completed and a re-fractured well, allow both methods to be considered and compared. Completion design and fracture treatment effectiveness are evaluated using the uniformity of proppant distribution at cluster and stage level as the primary measure. Perforation erosion measurements from downhole video footage is used as the main diagnostic. Novel data acquisition methods combined with successful well preparation provided comprehensive and high-quality datasets. The subsequent proppant distribution analysis for the two wells provides the highest confidence results presented to date. Clear, repeatable trends in distribution are observed and these are compared across multiple stage designs for both the newly completed and re-fractured well. Variations in design parameters and how these effects distribution and ultimately recovery are discussed. These include changes to perforation count per cluster, cluster spacing, cluster count per stage, stage length, perforation charge size and treatment rates and volumes. As a final consideration production records for the evaluated wells are also discussed. Historical industry data shows that the number of wells being re-fractured increases relative to the number of newly drilled wells being completed during periods of low oil and gas prices. With the industry again facing harsh economic realities an increasing number of decisions will be made on whether new or refractured wells, or a combination of both, provide the best solution to replace otherwise inevitable production decline. This paper attempts to provide a detailed understanding of how proppant distribution, as a significant factor in production for hydraulically fractured wells, can be evaluated and considered in these decisions.
Abstract In this paper, the authors examine the impacts of natural fractures on the distribution of slurry in a well with a permanent fiber installation and drill bit geomechanics data. Additionally, they propose a framework for further investigation of natural fractures on slurry distribution. As part of the Marcellus Shale Energy and Environmental Laboratory (MSEEL), the operator monitored the drilling of a horizontal Marcellus Formation well with drill bit geomechanics, and subsequent stimulation phase with a DAS/DTS permanent fiber installation. Prior to the completion, the authors used an analytical model to examine the theoretical distribution of slurry between perforation clusters from a geomechanics framework. A perforation placement scheme was then developed to minimize the stress difference between clusters and to segment stages by the intensity of natural fractures while conforming to standard operating procedures for the operator's other completions. The operator initially began completing the well with the geomechanics-informed perforation placement plan while monitoring the treatment distribution with DAS/DTS in real time. The operator observed several anomalous stages with treating pressures high enough to cause operational concerns. The operator, fiber provider, and drill bit geomechanics provider reviewed the anomalous stages’ treatment data, DAS/DTS data, and geomechanics data and developed a working hypothesis. They believed that perforation clusters placed in naturally fractured rock were preferentially taking the treatment slurry. This phenomenon appeared to cause other clusters within the stage to sand-off or become dormant prematurely, resulting in elevated friction pressure. This working hypothesis was used to predict upcoming stages within the well that would be difficult to treat. Another perforation placement plan was developed for the second half of the well to avoid perforating natural fractures as an attempt to mitigate operational issues due to natural fracture dominated distribution. Over the past several years, the industry's growing understanding of geomechanical and well construction variability has created new limited-entry design considerations to optimize completion economics and reduce the variability in cluster slurry volumes. Completion engineers working in naturally fractured fields, such as the Marcellus, should consider the impact the natural fractures have on slurry distribution when optimizing their limited-entry designs and stage plan.
Abstract This paper explores a holistic approach to characterize trouble stages by applying automated event recognition of abnormal pressure increases and associating those events to formation and operational causes. This analysis of pressure increases provides insight into the potential causes of operational difficulties, and the related diagnostics can suggest improvements to future pump schedules. Improving how stages are pumped is profitable both in the short-term (reducing wasted fluid and chemicals, and other remediation measures) and in the long-term (increased well productivity). Quantifying how design decisions ultimately affect operations can help decrease the frequency of operational problems and help realize these gains. In this study, the identification of problematic frac stages was initially performed manually (stage-by-stage) using a cloud-based hydraulic fracture data application. During this process, the team recognized that the problem stages had their own characteristic pressure signature - a sudden unexplained pressure increase in the absence of rate changes. A machine learning algorithm was then developed to automatically identify this type of signature. Additionally, previously published machine learning algorithms were used to recognize other operational events of interest, e.g., when proppant reaches the perforations. Then by combining the various events and creating short search windows around each abnormal pressure increase, it is possible to find concurrent operations that may be associated with the observed pressure behavior. A subsequent statistical analysis revealed that abnormal pressure increases often coincided with changes in proppant concentration in problem stages (stages with abnormal treating pressure behavior). This behavior may be due to near-wellbore effects caused by the changing fluid flow dynamics. Furthermore, it was observed that treating pressures that behaved contrary to hydrostatic pressure effects may be useful in identifying when injectivity is lost and provide an early signal for screen outs. Through this holistic approach, we were able to identify trouble stages and discern some diagnostics for automated detection of abnormal treating pressure increases. The team was able to identify areas within the stages that were inefficiently pumped, resulting in cost-savings through optimization of proppant and friction reducer (FR) loadings while maintaining a level of caution to prevent screen outs. Finally, the automated detection of pressure anomalies offers a pathway to the real-time prediction and avoidance of operational difficulties such as pressure outs and screen outs.
Abstract Well spacing and stimulation design are amongst the highest impact design variables which can dictate the economics of an unconventional development. The objective of this paper is to showcase a numerical simulation workflow, with emphasis on the hydraulic fracture simulation methodology, which optimizes well spacing and completion design simultaneously. The workflow is deployed using Cloud Computing functionality, a step-change over past simulation methods. Workflow showcased in this paper covers the whole cycle of 1) petrophysical and geomechanical modeling, 2) hydraulic fracture simulations and 3) reservoir simulation modeling, followed by 4) design optimization using advanced non-linear methods. The focus of this paper is to discuss the hydraulic fracture simulation methods which are an integral part of this workflow. The workflow is deployed on a dataset from a multi-well pad completed in late 2018 targeting two landing zones in the Vaca Muerta shale play. On calibrated petrophysical and geomechanical model, hydraulic fracture simulations are conducted to map the stimulated rock around the wellbores. Finely gridded base model is utilized to capture the property variation between layers to estimate fracture height. The 3d discrete fracture network (DFN) built for the acreage is utilized to pick the natural fracture characteristics of the layers intersected by the wellbores. The methodology highlights advances over the past modeling approaches by including the variation of discrete fracture network between layers. The hydraulic fracture model in conjunction with reservoir flow simulation is used for history matching the production data. On the history matched model, a design of experiments (DOE) simulation study is conducted to quantify the impact of a wide range of well spacing and stimulation design variables. These simulations are facilitated by the recent deployments of cloud computing. Cloud computing allows parallel running of hundreds of hydraulic fracturing and reservoir simulations, thereby allowing testing of many combinations of stimulation deigns and well spacing and reducing the effective run time from 3 months on a local machine to 1 week on the cloud. Output from the parallel simulations are fitted with a proxy model to finally select the well spacing and stimulation design variables that offer the minimum unit development cost i.e. capital cost-$ per EUR-bbl. The workflow illustrates that stimulation design and well spacing are interlinked to each other and need to be optimized simultaneously to maximize the economics of an unconventional asset. Using the workflow, the team identified development designs which increase EUR of a development area by 50-100% and reduce the unit development cost ($/bbl-EUR) by 10-30%.
Abstract The objective of this study was to perform an integrated analysis to gain insight for optimizing fracturing treatment and gas recovery from Marcellus shale. The analysis involved all the available data from a Marcellus Shale horizontal well which included vertical and lateral well logs, hydraulic fracture treatment design, microseismic, production logging, and production data. A commercial fracturing software was utilized to predict the hydraulic fracture properties based on the available vertical and lateral well logs data, diagnostic fracture injection test (DFIT), fracture stimulation treatment data, and microseismic recordings during the fracturing treatment. The predicted hydraulic fracture properties were then used in a reservoir simulation model developed based on the Marcellus Shale properties to predict the production performance. In this study, the rock mechanical properties were estimated from the well log data. The minimum horizontal stress, instantaneous shut-in pressure (ISIP), process zone stress (PZS), and leak-off mechanism were determined from DFIT analysis. The stress conditions were then adjusted based on the results of microseismic interpretations. Subsequently, the results of the analyses were used in the fracturing software to predict the hydraulic fracture properties. Marcellus Shale properties and the predicted hydraulic fracture properties were used to develop a reservoir simulation model. Porosity, permeability, and the adsorption characteristics were estimated from the core plugs measurements and the well log data. The image logs were utilized to estimate the distribution of natural fractures (fissures). The relation between the formation permeability and the fracture conductivity and the net stress (geomechanical factors) were obtained from the core plugs measurements and published data. The predicted production performance was then compared against production history. The analysis of core data, image logs, and DFIT confirmed the presence of natural fractures in the reservoir. The formation properties and in-situ stress conditions were found to influence the hydraulic fracturing geometry. The hydraulic fracture properties are also impacted by stress shadowing and the net stress changes. The production logging tool results could not be directly related to the hydraulic fracture properties or natural fracture distribution. The inclusion of the stress shadowing, microseismic interpretations, and geomechanical factors provided a close agreement between the predicted production performance and the actual production performance of the well under study.
Abstract Shale wells are often shut-in after hydraulic fracturing is finished. Shut-in often lasts for an extended period in the perceived hope to improve the ultimate oil recovery. However, current literature does not show a strong consensus on whether shut-in will improve the ultimate oil recovery. Because of the delayed production, evaluating the benefits of shut-in in improving the ultimate oil recovery is crucial. Otherwise, shut-in would merely delay the production and harm the economic performance. This paper uses a numerical flow-geomechanical modeling approach to investigate the effect of imbibition on shut-in potentials to improve the ultimate oil recovery. This paper proposes that imbibition is one of the strongly confounding variables that cause the mixed conclusions in the related literature. The investigation methodology involves probabilistic forecasting of three reservoir realization models validated based on the same field production data. Each of the models represents different primary recovery driving mechanism, such as imbibition-dominant and compaction-dominant recovery. A parametric study is conducted to explore and identify the specific reservoir conditions in which shut-in tends to improve the shale oil recovery. Ten reservoir parameters which affect the imbibition strength are studied under different shut-in durations. Comparison among the three models quantitatively demonstrates that shut-in tends to improve the ultimate oil recovery only if the shale reservoir demonstrates imbibition-dominant recovery. A first-pass economic analysis also suggests that when the shale oil reservoirs demonstrate such an imbibition-dominant recovery, shut-in tends to not only improve the ultimate oil recovery, but also the NPV. A correlation among ultimate oil recovery, flowback efficiency, and NPV also shows that there is no strong relationship between flowback efficiency and ultimate oil recovery. This study is one of the first to emphasize the importance of quantifying the imbibition strength and its contribution in helping recover the shale oil for optimum flowback framework and shale well shut-in design after hydraulic fracturing.
Soroush, Mohammad (RGL Reservoir Management, University of Alberta) | Mohammadtabar, Mohammad (RGL Reservoir Management, University of Alberta) | Roostaei, Morteza (RGL Reservoir Management) | Hosseini, Seyed Abolhassan (RGL Reservoir Management, University of Alberta) | Mahmoudi, Mahdi (RGL Reservoir Management) | Keough, Daniel (Precise Downhole Services Ltd) | Cheng, Li (University of Alberta) | Moez, Kambiz (University of Alberta) | Fattahpour, Vahidoddin (RGL Reservoir Management)
Abstract Distributed Temperature Sensing (DTS) system using optical fiber has been deployed for downhole monitoring over two-decades. Several technological advancements led to a wide acceptance of this technology as a reliable surveillance technique. This paper presents a comprehensive technical review of all the applications of the DTS, with focus on oil and gas industrial deployments. The paper starts with the advantages of the DTS over other methods and an overview of the DTS basics, including theory, the DTS components, deployment types, fiber types, design and limitations. Then, it is followed by the oil and gas applications of the DTS including hydraulic fracturing (during and after fracturing), well treatment/stimulation (acid injection, fluid distribution, diversion monitoring), inorganic (scaling) and organic (wax/asphaltene/hydrate) deposition detection, leak detection (in well and pipeline), flow monitoring (rate monitoring, water/steam injection and SAGD monitoring, CO2 storage monitoring, zonal contribution determination, gas lift optimization) and reservoir/fluid characterization (facies, porosity, permeability and fluid composition determination). This study reviews the historical development, applications and limitations of the DTS systems. The paper mainly focusses on deployment techniques, the application of the DTS for the prediction and surveillance of the non-thermal and thermal producer/injector wells, hydraulically fractured wells and those wells with treatments. The paper provides a concise review using several field cases from over two hundred published papers of Society of Petroleum Engineering (SPE) and journal databases. The application of the DTS in downhole monitoring can be divided into the qualitative and quantitative applications. In quantitative approaches, numerical models should be combined with the DTS data. This study discusses case by case worldwide field applications of DTS along with proposed modeling methods and interpretations. It also summarizes main challenges, including the fiber reliability, longevity, and operational limitations such as the installation and the complexity of quantitative approaches. This study is the foundation for an ongoing study on wellbore and reservoir surveillance through real-time distributed fiber optic sensing recordings along the wellbore. It summarizes the historical development and limitations to identify the existing gaps and reviews the lessons learned through the two decades of the application of the DTS in production performance.