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Abstract Distributed Fiber Optics (DFO) technology has been the new face for unconventional well diagnostics. This technology focuses on measuring Distributed Acoustic Sensing (DAS) and Distrusted Temperature Sensing (DTS) to give an in-depth understanding of well productivity pre and post stimulation. Many different completion design strategies, both on surface and downhole, are used to obtain the best fracture network outcome; however, with complex geological features, different fracture designs, and fracture driven interactions (FDIs) effecting nearby wells, it is difficult to grasp a full understanding on completion design performance for each well. Validating completion designs and improving on the learnings found in each data set should be the foundation in developing each field. Capturing a data set with strong evidence of what works and what doesn't, can help the operator make better engineering decisions to make more efficient wells as well as help gauge the spacing between each well. The focus of this paper will be on a few case studies in the Bakken which vividly show how infill wells greatly interfered with production output. A DFO deployed with a 0.6" OD, 23,000-foot-long carbon fiber rod to acquire DAS and DTS for post frac flow, completion, and interference evaluation. This paper will dive into the DFO measurements taken post frac to further explain what effects are seen on completion designs caused by interferences with infill wells; the learnings taken from the DFO post frac were applied to further escalate the understanding and awareness of how infill wells will preform on future pad sites. A showcase of three separate data sets from the Bakken will identify how effective DFO technology can be in evaluating and making informed decisions on future frac completions. In this paper we will also show and discuss how DFO can measure real time FDI events and what measures can be taken to lessen the impact on negative interference caused by infill wells.
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.
Guo, Yifei (The University of Texas at Austin) | Ashok, Pradeepkumar (The University of Texas at Austin) | van Oort, Eric (The University of Texas at Austin) | Patterson, Ross (Hess Corporation) | Zheng, Dandan (Hess Corporation) | Isbell, Matthew (Hess Corporation) | Riopelle, Austin (Marathon Oil Corporation)
Abstract Well interference, which is commonly referred to as frac hits, has become a significant factor affecting production in fractured horizontal shale wells with the increase in infill drilling in recent years. Today, there is still no clear understanding on how frac hits affect production. This paper aims to develop a process to automatically identify the different types of frac hits and to determine the effect of stage-to-well distance and frac hit intensity on long-term parent well production. First, child well completions data and parent well pressure data are processed by a frac hit detection algorithm to automatically identify different frac hit intensities and duration within each stage. This algorithm classifies frac hits based on the magnitude of the differential pressure spikes. The frac stage to parent well distance is also calculated. Then, we compare the daily production trend before and after the frac hits to determine the severity of its influence on production. Finally, any evident correlations between the stage-to-well distance, frac hit intensity and production change are identified and investigated. This work utilizes 3 datasets covering 22 horizontal wells in the Bakken Formation and 37 horizontal wells in the Eagle Ford Shale Formation. These sets included well trajectories, child well completions data, parent well pressure data and parent well production data. The frac hit detection algorithm developed can accurately detect frac hits in the available dataset with minimal false alerts. The data analysis results show that frac hit severity (production response) and intensity (pressure response) are not only affected by the distance between parent and child wells, but also affected by the directionality of the wells. Parent wells tend to experience more frac hits from the child frac stages with smaller direction angles and shorter stage-to-parent distances. Formation stress change with time is another factor that affects frac hit intensity. Depleted wells are more susceptible to frac hits even if they are further from the child wells. Also, we observe frac hits in parent wells due to a stimulation of a child well in a different shale formation. This paper presents a novel automated frac hit detection algorithm to quickly identify different types of frac hits. This paper also presents a novel way of carrying out production analysis to determine whether frac hits in a well have positive or negative influence long-term production. Additionally, the paper introduces the concept of the stage-to-well distance as a more accurate metric for analyzing the influence of frac hits on production.
Abstract The Walloons coal measures located in Surat Basin (eastern Australia) is a well-known coal seam gas play that has been under production for several years. The well completion in this play is primarily driven by coal permeability which varies from 1 Darcy or more in regions with significant natural fractures to less than 1md in areas with underdeveloped cleat networks. For an economic development of the latter, fracturing treatment designs that effectively stimulate numerous and often thin coals seams, and enhance inter-seam connectivity, are a clear choice. Fracture stimulation of Surat basin coals however has its own challenges given their unique geologic and geomechanical features that include (a) low net to gross ratio of ~0.1 in nearly 300 m (984.3 ft) of gross interval, (b) on average 60 seams per well ranging from 0.4 m to 3 m in thickness, (c) non-gas bearing and reactive interburden, and (d) stress regimes that vary as a function of depth. To address these challenges, low rate, low viscosity, and high proppant concentration coiled tubing (CT) conveyed pinpoint stimulation methods were introduced basin-wide after successful technology pilots in 2015 (Pandey and Flottmann 2015). This novel stimulation technique led to noticeable improvements in the well performance, but also highlighted the areas that could be improved – especially stage spacing and standoff, perforation strategy, and number of stages, all aimed at maximizing coal coverage during well stimulation. This paper summarizes the findings from a 6-well multi-stage stimulation pilot aimed at studying fracture geometries to improve standoff efficiency and maximizing coal connectivity amongst various coal seams of Walloons coal package. In the design matrix that targeted shallow (300 to 600 m) gas-bearing coal seams, the stimulation treatments varied in volume, injection rate, proppant concentration, fluid type, perforation spacing, and standoff between adjacent stages. Treatment designs were simulated using a field-data calibrated, log-based stress model. After necessary adjustments in the field, the treatments were pumped down the CT at injection rates ranging from 12 to 16 bbl/min (0.032 to 0.042 m/s). Post-stimulation modeling and history-matching using numerical simulators showed the dependence of fracture growth not only on pumping parameters, but also on depth. Shallower stages showed a strong propensity of limited growth which was corroborated by additional field measurements and previous work in the field (Kirk-Burnnand et al. 2015). These and other such observations led to revision of early guidelines on standoff and was considered a major step that now enabled a cost-effective inclusion of additional coal seams in the stimulation program. The learnings from the pilot study were implemented on development wells and can potentially also serve as a template for similar pinpoint completions worldwide.
Abstract In the present cost-constrained environment, it is critical that operators effectively complete their wells while minimizing capital expenditure. Optimization efforts focus on increasing recovery factor by managing landing zone, increasing the number of effective fractures, increasing the size of the fractures, and increasing the length of the lateral, while reducing the total number of stages and job size, without sacrificing efficient proppant and fluid delivery. The same pressure to reduce expenditure also impacts decision making on diagnostic evaluation, reducing operators to ‘free’ or low-cost feedback, like surface production rates and decline curves. Operators are responding to these challenges by utilizing a combination of lower cost, post-completion diagnostics like deployed fiber optics, downhole camera evaluation of perforations and radioactive tracers. These less expensive options allow for a broader scope and number of diagnostic inquiries, whereas a permanent fiber may prove to be cost-prohibitive, reducing diagnostic focus to one well, in one part of a play. Combining differing diagnostic technologies enhances the overall description of the well and reservoir behaviors and improves confidence in their interpretation of stimulation and production efficiency; furthermore, where a single diagnostic measurement may be unlikely to justify dramatic change in a completion strategy, a combination of data points from different domains can and does support design change that leads to rapid, real world performance improvements. Care is needed in the conclusions drawn when utilizing complimentary diagnostics due to the differences in depth of investigation and the non-unique interpretation of some data types. This paper discusses three post-completion diagnostic technologies, perforation evaluation by downhole camera, radioactive tracers, and distributed acoustic and temperature sensing (DAS+DTS) data and their respective physical measurements, strengths and weaknesses and how they can be combined to better understand well and reservoir behavior. It concludes with a review of completion optimization efforts from the Rockies area, where these post-completion diagnostic technologies were applied in the evaluation of eXtreme Limited Entry (XLE) trials. A statistical analysis of the RA tracer, downhole camera measurement of perforation area and deployed fiber optic acquisition of DAS+DTS reveals no correlation between diagnostic answers, indicating no one diagnostic measurement can accurately predict the other, such that it could substitute for that diagnostic and provide the same answer. Asking the right question can often enhance the value of diagnostic descriptions of the system in question. Those answers often lead to the next question and clear the path forward in advancing completion optimization. Complimentary diagnostics facilitate a more complete understanding of stimulation and production performance when compared, increasing confidence when they agree. When one or more appear to disagree, the different respective physical measurements and depths of investigation often reveal a more complete and complex understanding of stimulation and production efficiency. As an aggregate they provide clarity on the effect of efforts to create conductive pathways into the reservoir, allowing operators increased control over the resulting production.
Mondal, Somnath (Shell Exploration & Production Co.) | Zhang, Min (University of Texas at Austin) | Huckabee, Paul (Shell Exploration & Production Co.) | Ugueto, Gustavo (Shell Exploration & Production Co.) | Jones, Raymond (Shell Exploration & Production Co.) | Vitthal, Sanjay (Shell Exploration & Production Co.) | Nasse, David (Shell Exploration & Production Co.) | Sharma, Mukul (University of Texas at Austin)
Abstract This paper presents advancements in step-down-test (SDT) interpretation to better design perforation clusters. The methods provided here allow us to better estimate the pressure drop in perforations and near-wellbore tortuosity in hydraulic fracturing treatments. Data is presented from field tests from fracturing stages with different completion architectures across multiple basins including Permian Delaware, Vaca Muerta, Montney, and Utica. The sensitivity of near-wellbore pressure drops and perforation size on stimulation distribution effectiveness in plug-and-perf (PnP) treatments is modeled using a coupled hydraulic fracturing simulator. This advanced analysis of SDT data enables us to improve stimulation distribution effectiveness in multi-cluster or multiple entry completions. This analysis goes much further than the methodology presented in URTeC2019-1141 and additional examples are presented to illustrate its advantages. In a typical SDT, the injection flowrate is reduced in four or five abrupt decrements or "steps", each with a duration long enough for the rate and pressure to stabilize. The pressure-rate response is used to estimate the magnitude of perforation efficiency and near-wellbore tortuosity. In this paper, two SDTs with clean fluids were conducted in each stage - one before and another after proppant slurry was injected. SDTs were conducted in cemented single-point entry (cSPE) sleeves, which present a unique opportunity to measure only near-wellbore tortuosity using bottom-hole pressure gauge at sleeve depth, negligible perforation pressure drops, and less uncertainty in interpretation. SDTs were conducted in PnP stages in multiple unconventional basins. The results from one set of PnP stages with optic fiber distributed sensing were modeled with a hydraulic fracturing simulator that combines wellbore proppant transport, perforation size growth, near-wellbore pressure drop, and hydraulic fracture propagation. Past SDT analysis assumed that the pressure drop due to near-wellbore tortuosity is proportional to the flow rate raised to an exponent, β = 0.5, which typically overestimates perforation friction from SDTs. Theoretical derivations show that β is related to the geometry and flow type in the near-wellbore region. Results show that initial β (before proppant slurry) is typically around 0.5, but the final value of β (after proppant slurry) is approximately 1, likely due to the erosion of near-wellbore tortuosity by the proppant slurry. The new methodology incorporates the increase in β due proppant slurry erosion. Hydraulic fracturing modeling, calibrated with optic fiber data, demonstrates that the stimulation distribution effectiveness must consider the interdependence of proppant segregation in the wellbore, perforation erosion, and near-wellbore tortuosity. An improved methodology is presented to quantify the magnitude of perforation and near-wellbore tortuosity related pressure drops before and after pumping of proppant slurry in typical PnP hydraulic fracture stimulations. The workflow presented here shows how the uncertainties in the magnitude of near-wellbore complexity and perforation size, along with uncertainties in hydraulic fracture propagation parameters, can be incorporated in perforation cluster design.
Hui, Gang (University of Calgary, Alberta, Canada) | Chen, Shengnan (University of Calgary, Alberta, Canada) | Gu, Fei (PetroChina Research Institute of Petroleum Exploration and Development, Beijing, China)
Abstract The recent seismicity rate increase in Fox Creek is believed to be linked to the hydraulic fracturing operations near the region. However, the spatiotemporal evolution of hydraulic fracturing-induced seismicity is not well understood. Here, a coupled approach of geology, geomechanics, and hydrology is proposed to characterize the spatiotemporal evolution of hydraulic fracturing-induced seismicity. The seismogenic faults in the vicinity of stimulated wells are derived from the focal mechanisms of mainshock event and lineament features of induced events. In addition, the propagation of hydraulic fractures is simulated by using the PKN model, in combination with inferred fault, to characterize the possible well-fault hydrological communication. The original stress state of inferred fault is determined based on the geomechanics analysis. Based on the poroelasticity theory, the coupled flow-geomechanics simulation is finally conducted to quantitatively understand the fluid diffusion and poroelastic stress perturbation in response to hydraulic fracturing. A case study of a moment-magnitude-3.4 earthquake near Fox Creek is utilized to demonstrate the applicability of the coupled approach. It is shown that hydraulic fractures propagated along NE45° and connected with one North-south trending fault, causing the activation of fault and triggered the large magnitude event during fracturing operations. The barrier property of inferred fault under the strike-slip faulting regime constrains the nucleation position of induced seismicity within the injection layer. The combined changes of pore pressure and poroelastic stress caused the inferred fault to move towards the failure state and triggered the earthquake swarms. The associated spatiotemporal changes of Coulomb Failure Stress along the fault plane is well in line with the spatiotemporal pattern of induced seismicity in the studied case. Risks of seismic hazards could be reduced by decreasing fracturing job size during fracturing stimulations.
Rodríguez-Pradilla, Germán (School of Earth Sciences, University of Bristol, UK.) | Eaton, David (Department of Geoscience, University of Calgary, Canada.) | Popp, Melanie (geoLOGIC Systems Ltd., Calgary, Canada.)
Abstract The goal of this work is to calibrate a regional predictive model for maximum magnitude of seismic activity associated with hydraulic-fracturing in low-permeability formations in the Western Canada Sedimentary Basin (WCSB). Hydraulic fracturing data (i.e. total injected volume, injection rate, and pressure) were compiled from more than 40,000 hydraulic-fractured wells in the WCSB. These wells were drilled into more than 100 different formations over a 20-year period (January 1st, 2000 and January 1st, 2020). The total injected volume per unit area was calculated utilizing an area of 0.2° in longitude by 0.1° in latitude (or approximately 13x11km, somewhat larger than a standard township of 6x6 miles). This volume was then used to correlate with reported seismicity in the same unit areas. Collectively, within the 143 km area considered in this study, a correlation between the total injected volume and the maximum magnitude of seismic events was observed. Results are similar to the maximum-magnitude forecasting model proposed by A. McGarr (JGR, 2014) for seismic events induced by wastewater injection wells in central US. The McGarr method is also based on the total injected fluid per well (or per multiple nearby wells located in the same unit area). However, in some areas in the WCSB, lower injected fluid volumes than the McGarr model predicts were needed to induce seismic events of magnitude 3.0 or higher, although with a similar linear relation. The result of this work is the calculation of a calibration parameter for the McGarr model to better predict the magnitudes of seismic events associated with the injected volumes of hydraulic fracturing. This model can be used to predict induced seismicity in future unconventional hydraulic fracturing treatments and prevent large-magnitude seismic events from occurring. The rich dataset available from the WCSB allowed us to carry out a robust analysis of the influence of critical parameters (such as the total injected fluid) in the maximum magnitude of seismic events associated with the hydraulic-fracturing stimulation of unconventional wells. This analysis could be replicated for any other sedimentary basin with unconventional wells by compiling similar stimulation and earthquake data as in this study.
Abstract In multi-stage plug-and-perf horizontal well completions, there are a multitude of moving parts and variables to consider when evaluating performance drivers. Properly identifying performance drivers allows an operator to focus their efforts to maximize the rate of return of resource development. Typically, well-to-well comparisons are made to help identify performance drivers, but in many cases the differences are not clear. Identifying these drivers may require a better understanding of performance variability along a single lateral. Data analytics can help to identify performance drivers using existing data from development activities. In the case study below, multiple diagnostics are utilized to identify performance drivers. A combination of completion diagnostics including oil and water tracers, stimulation data, reservoir data, 3D seismic, and borehole image logs were collected on a set of wells in the early appraisal phase of a field. Using oil tracers as the best indication of stage level performance along the laterals, data analytics is applied to uncover the relationships between the tracers and the numerous diagnostics. After smoothing was applied to the dataset, trends between oil tracer recovery, several independent variables and features seen in image logs and 3D seismic were identified. All the analyses pointed to decreasing tracer recovery, and likely decreased oil production, near faulted areas along each lateral. A random forest model showed a moderate prediction power, where the model's predicted tracer recovery on blind stages was able to explain 54% of the variance seen in the tracer response (r=0.54). This analysis suggests the identification of certain faulted areas along the wellbore could lead to ways of improving individual well economics by adjusting completion design in these areas.