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The complete paper discuses a well with a history of sand production that exhibits long cyclic slugging behavior. In the complete paper, the authors reduce nonuniqueness and ensure physically feasible results in multiwell deconvolution by incorporating constraints and knowledge to methodology already established in the literature. In the complete paper, a novel hybrid approach is presented in which a physics-based nonlocal modeling framework is coupled with data-driven clustering techniques to provide a fast and accurate multiscale modeling of compartmentalized reservoirs. Fit-for-purpose tactics likely will be of ever-increasing focus going forward. If it is not adding value, it should not be done.
This paper presents the basic concepts and architecture of the Eni Reservoir Electromagnetic Mapping borehole electromagnetic mapping system that integrates borehole EM methodology with surface EM methods to provide real-time mapping of reservoir-fluid distribution during production or injection. An intelligent drilling optimization application performs as an adaptive autodriller. In the Marcellus Shale, ROP improved 61% and 39% and drilling performance, measured as hours on bottom, improved 25%. With their gee-whiz—albeit artificial—intelligence, robots may be the industry’s answer to jobs deemed dangerous, dirty, distant, or dull. A test showing that it’s possible to automate the billing process for produced water hauling has opened the door for tracking a wide range of field activities.
One of the frustrating aspects of well-productivity analysis is identifying the causes of lower-than-expected production/injection during initial well lifetime. Our task is to evaluate the multivariate aspects of well design. Wells in deepwater reservoirs show significant rate decline with time as the result of various causes. A diagnostic tool for quantification of factors influencing well-productivity decline is presented in this paper. The success of water-conformance operations often depends on clear identification of the water-production mechanism.
This paper shares the results from the first successful deployment of a real-time, multiphase inflow profiling technology applied to BP operated Clair Ridge asset. Uncertainty around distribution and the dynamic behaviour of the fractured reservoir required the deployment of Distributed Fibre Optic Sensing (DFOS) capabilities as part of the well completions across a selection of the well stock, to enable in-depth real-time flow surveillance and maximize recovery from the field. Unlike conventional wireline conveyed sensors and logs that provide static measurements of flow conditions, the DFO data will be used to provide a more comprehensive, dynamic inflow distribution across multizone completion uniquely including flow in the annular space behind blank sections.
This paper summarizes key findings from the first deployment of a new real-time technology solution that employs novel signal processing techniques using the DFO data as key sensor inputs to detect relative inflow rates of different fluid types along the wellbore during production. The solution presents inflow logs for each fluid phase in near real-time through proprietary streaming analytics capabilities embedded in a cloud-based software solution. This facilitates 24×7, real-time flow surveillance across wells equipped with fibre in the field. This paper also presents early results from the use of the technology on the first platform drilled production well and discusses how these real-time insights have been effectively applied to provide significant business value, including but not limited to new well start-up optimization, well management and zonal fluid inflow allocation. The paper also detail the use of the technology for water inflow detection and quantification and discusses the implementation of drawdown optimization strategies based on the insight to control water inflow that have already resulted in significant production benefits.
Sawadogo, Jordan (Biota Technology) | Haggerty, Matthew (Biota Technology) | Mallory, CharLee (Chaparral Energy LLC) | Huchton, Jake (Chaparral Energy LLC) | DeAngelis, Whitney (Chaparral Energy LLC) | Price, Courtney (Chaparral Energy LLC)
The STACK (Sooner Trend Anadarko Canadian and Kingfisher counties) is a prolific multi-target stacked play in Oklahoma. Development challenges in the STACK are underpinned by fieldwide geological heterogeneities, including variable reservoir quality throughout the Sycamore-Meramec and Woodford formations and the presence of natural fractures and dense laminations. This case study examines the operator's first fully co-developed section in Canadian County, which comprised of 11 wells across 4 targets. This project was undertaken after de-risking much of the geological uncertainty in several offset pads.
The data acquisition program was designed to assess the impact of total completion design including: interwell spacing, targeting, and wine-rack configuration on well-to-well connectivity and well performance in full section development. Within the section, half of the wells were drilled with the same spacing as offset pads and the other half were downspaced. On both sides of the section, similar targets received the same hydraulic fracturing design. Given it was the operator's first full section development in the county, the operator utilized an advanced data acquisition program that included downhole pressure gauges, chemical tracers, and DNA based diagnostics. DNA diagnostics proved especially useful in measuring the relative contribution from the multiple strata between landing zones, which would not have otherwise been possible. Although the previous offset pilot pads were developed with similar spacing and completion parameters, there were significant differences between average production profiles, with higher initial production (IP-180) observed in the full section.
This paper evaluates these production differences by examining the impact of well spacing/targeting, completion design, and interwell communication on well performance in full section development. Well performance was assessed by integrating production, pressure, and tracer data, along with DNA based diagnostics. DNA diagnostics played a key role in assessing and monitoring the duration of interwell communication between offset wells across the section. Results from this integrated approach demonstrated that full section well performance was impacted by completion design and interwell communication in three notable ways: 1) interbench co-development significantly increased communication across perceived deterrents to fracture growth, 2) well-to-well communication was influenced by completion order, and 3) aggregate interwell communication was higher in full section development than in pilot pads, which may have contributed to the full section initially outperforming pre-drill expectations.
The differences in well performance and well-to-well connectivity carry important implications for operators who plan to use partial spacing tests to develop multi-target full sections. Specifically, these observations underscore the potential for similar completion designs to yield materially different well performances between full section and 1 to 3 well pad development. These results also demonstrate the ability of DNA based diagnostics to accelerate learnings in full section development, which may have otherwise required additional CAPEX to test via heuristic techniques.
In recent years, well performance from tight reservoirs in the Delaware Basin has been improving due to enhanced completion practices, better reservoir targeting and improved well designs in the region. One of the key components to the enhanced completion practices has been the implementation of progressively longer laterals. The rate of increase in lateral lengths have slightly slowed in recent years, as operators approach the point of no additional value creation as the well costs supersede the production gained from longer wells. This paper presents a tool created to evaluate the performance and economics of a given well given different reservoir, fluid, well design and completion parameters. The tool is also a probabilistic model that can quantify the impact of input parameters that the user feels uncertain about. As a result, it can provide management teams with an approach to make capital decisions under uncertainty. The proposed methodology presented in this paper is repeatable for different tight rock formations across different basins. An example of the tool's capability is demonstrated in this paper using an asset profile typical of the Delaware Basin's Wolfcamp A.
This paper presents a method for identifying the optimum soaking time between the cessation of pumping, and the flowback of hydraulic fracturing fluids after a hydraulic fracture stimulation job, to increase productivity of shale gas and oil wells. Multiple cracks were observed at the surfaces of cores from a shale oil reservoir under simulated water-soaking conditions. The observation proposes a hypothesis that the formation of cracks should increase well productivity. Well shut-in pressure data recorded in a watersoaking process in a shale gas reservoir were employed to derive a mathematical model to describe the process of crack propagation in shale gas/oil formations. This crack model was incorporated in a well productivity model to form an objective function for selection of the water soaking time. A field case was studied with the mathematical model to proof the hypothesis and explore factors affecting the optimum water-soaking time. Analysis of the model shows a quick increase of well productivity with water-soaking time in the beginning followed by a trend of leveling-off. The water-soaking process is mainly controlled by the number of cracks along the bedding plane. High viscosity of fracturing fluid corresponds to longer soaking time, while increasing water-shale interfacial tension reduces the optimum soaking time. The effect of different initial water saturations on optimum soaking time was found to be insignificant. If real time shut-in pressure data are used, this technique can translate the pressure data to dynamic crack propagation data and "monitor" the potential well productivity as a function of water-soaking time.
This paper explores the results of Repsol Bolivia's successful implementation of a workflow-based solution for real-time production surveillance as part of a digital oilfield initiative on Margarita Field. We will examine the fundamental aspects of data integration across multiple disciplines in the asset and the impact generated when having all the needed information available to rule-based processes in the same environment. This project successfully incorporated the main aspects of the operations. The implementation complements Repsol's Digital Oilfield initiative, started in 2013, with hardware installations for automation of wells, plants and other operational equipment. This paper will discuss the value of an integrated platform (data-processes-people) and the impact on the decision-making process.
Margarita Field produces from ten high-volume gas wells that yield 30% of the gas production in Bolivia. This project targeted real-time well integrity, and operational monitoring to ensure stable production levels while automating a broad suite of best practices to improve efficiency for engineers, avoid production deferments, and enhance safety. This paper details how to leverage data in real-time and fully benefit from it by applying smart engineering workflows designed to integrate modeling tools, data, and engineering best practices.
Prior to this implementation, it was demonstrated that a significant portion of the asset engineers’ time was spent simply gathering data from multiple sources. The previously installed, field data automation and real-time feeds, generated significant analytical benefits. However, the increase in useful data was underutilized and limited by the existing spreadsheets. These activities were manual and error-prone, and routinely led to: data duplications, data inaccuracies, and, most importantly, to delayed or suboptimal decisions based on incomplete or inaccurate information.
The new solution addresses these challenges by providing an integrated environment where engineers have all the information and workflows readily available and automatically executed. To ensure the workflow automation did not mask problems or simply automate error-prone outcomes, validation gates were established to help ensure the engineers that the results were robust and sufficiently checked for quality. Automated, system-based reporting, helped to eliminate weekly manual reporting efforts, support the QC, and eliminate man time previously required to support operational meetings and decisions. The workflows are designed to maintain evergreen models to support the asset surveillance process. "Live links" to all sources ensures data duplication is no longer an issue and helps to establish "one source of the truth". The workflow-based automation has brought the various, pre-existing, well, production network, and reservoir modeling tools "Online" so they can be incorporated into daily operational surveillance activities and decision-making.
Extensive literature has been published concerning Fracture Driven Interactions (FDIs). Many of these works describe FDI anatomy, physics and impact on existing wells including the success or failure of various mitigation techniques. In this paper, time synchronized FDI surface pressure data from existing offsetting wells is used to study fracture wing growth. This includes timing, fracture half-length estimation and observing the movement of injected fluid sequentially from well-to-well during fracturing operations.
In 2019, an in-fill Eagle Ford well development consisting of two newly drilled wells and seven offsetting existing wells was performed. The new wells were located such that each treatment well was bounded on both sides by existing wells. Further, there were first order wells (closest well to treatment well) and second order wells (next well over from the first order well) bounding one of the treatment wells and FDIs generated pressure communication were seen in both the first order well and the second order well. Six of the existing wells were preloaded. This was done to test the efficacy of preloading to protect the existing wells from FDI damage.
The workflow was organized into first deriving detailed data from all FDIs that occurred in individually monitored wells. This was followed by examining well pairs bounding the two treatment wells to study fracture wing development in each stage. Lastly, first order and second order wells that had sequential FDIs from the treatment wells were examined to study fluid volumes and timing between wells as well as FDI magnitude dampening in second order wells. All monitored wells were left shut-in during the completion operations. The wireless surface pressure monitoring sensors were time-synchronized to internet time and the data was viewed in real-time.
The authors’ found that preloading dampened FDIs but did not completely stop them. The degree of the success of preloading was graded by determining a reduction of recovery time (if any) and how well production rates were protected. At the time of this writing, flowback operations are ongoing and one primary well recovered to pre-frac rates within one week. We anticipate a corresponding reduction of recovery time in the other wells.
This paper presents methods and processes that offer a solution to identify candidate stages for FDI mitigation and potential optimization of project economics. The time synchronization with internet time eliminated all uncertainty with regards to timing. As will be shown, for this type of study, there cannot be uncertainty with timing. No inconsistencies in timing were found. It was also determined that FDI data must be viewable in real-time for it to be used to make on-the-fly mitigation decisions. In this project, a "passive well defense" technique was utilized; preload but take no other actions.