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Se, Yegor (Chevron ETC) | Sullivan, Michael (Chevron Canada) | Tohidi, Vahid (Chevron Canada) | Lazorek, Michael (Chevron Canada) | Attia, Ahmed (Ziebel US) | Chen, Phillip (Ziebel US) | Abbassi, Linda (Openfield Technology) | Schoepf, Virginie (Openfield Technology)
Abstract The well design with long lateral section and multistage frac completion has been proven effective for development of the unconventional reservoirs. Top-tier well production in unconventional reservoir can be achieved by optimizing hydraulic completion and stimulation design, which necessitates an understanding of flow behavior and hydrocarbon contribution allocation. Historically, conventional production logging (PL) surveys were scarcely used in unconventional reservoirs due to limited and often expensive conveyance options, as well as complicated and non-unique inflow interpretations caused by intricate and changing multiphase flow behavior (Prakash et al., 2008). The assessment of the cluster performance gradually shifted towards distributed acoustic (DAS) and temperature (DTS) sensing methods using fiber optics cable, which continuously gained popularity in the industry. Fiber optics measurements were anticipated to generate production profiles along the lateral with sub-cluster resolution to assist with optimal completions design selection. Encapsulation of the fiber in the carbon rod provided alternative conveyance method for retrievable DFO measurements, which gained popularity due to cost-efficiency and operational convenience (Gardner et al., 2015). Recent utilization of micro-sensor technology in PL tools, (Abbassi et al, 2018, Donovan et al, 2019) allowed dramatic reduction of the size and the weight of the PL toolstring without compromising wellbore coverage by sensor array. Such ultra-compact PL toolstring could utilize the carbon rod as a taxi and provide mutually beneficial and innovative surveillance combination to evaluate production profile in the unconventional reservoirs. Array holdup and velocity measurements across wellbore from PL would reveal more details regarding multi-phase flow behavior, which could be used for cross-validation and constraining of production inflow interpretation based on DFO measurements. This paper summarizes the lessons learned, key observations and best practices from the unique 4 well program, where such innovative combination was tested in gas rich Duvernay shale reservoir.
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.
Abstract Low-frequency distributed acoustic sensing (LF-DAS) has been used for hydraulic fracture monitoring and characterization. Large amounts of DAS data have been acquired across different formations. The low-frequency components of DAS data are highly sensitive to mechanical strain changes. Forward geomechanical modeling has been the focus of current research efforts to better understand the LF-DAS signals. Moreover, LF-DAS provides the opportunity to quantify fracture geometry. Recently, Liu et al. (2020a;2020b) proposed an inversion algorithm to estimate hydraulic fracture width using LF-DAS data measured during multifracture propagation. The LF-DAS strain data is linked to the fracture widths through a forward model developed based on the Displacement Discontinuity Method (DDM). In this study, we firstly investigated the impacts of fracture height on the inversion results through a numerical case with a four-cluster completion design. Then we discussed how to estimate the fracture height based on the inversion results. Finally, we applied the inversion algorithm to two field examples. The inverted widths are not sensitive to the fracture height. In the synthetic case, the maximum relative error is less than 10% even when the fracture height is two times of the true value. After obtaining the fracture width, the fracture height can be estimated by matching the true strain data under various heights with a strong smooth weight. The error between the calculated strain and true strain decreases as the height is getting close to the true value. In the two field examples, the temporal evolutions of both width summation of all fractures and the width of each fracture show consistent behaviors with the field LF-DAS measurements. The calculated strain data from the forward model matches well with the field LF-DAS strain data. The results demonstrate the robustness and accuracy of the proposed inversion algorithm.
Shahri, Mojtaba (Apache Corp.) | Tucker, Andrew (Apache Corp.) | Rice, Craig (Apache Corp.) | Lathrop, Zach (Apache Corp.) | Ratcliff, Dave (ResFrac) | McClure, Mark (ResFrac) | Fowler, Garrett (ResFrac)
Abstract In the last decade, we have observed major advancements in different modeling techniques for hydraulic fracturing propagation. Direct monitoring techniques such as fibre-optics can be used to calibrate these models and significantly enhance our understanding of subsurface processes. In this study, we present field monitoring observations indicating consistently oriented, planar fractures in an offset-well at different landing zones in the Permian basin. Frac hit counts, location, and timing statistics can be compiled from the data using offset wells at different distances and depths. The statistics can be used to calibrate a detailed three-dimensional fully coupled hydraulic fracturing and reservoir simulator. In addition to these high-level observations, detailed fibre signatures such as strain response during frac arrival to the monitoring well, post shut-in frac propagation and frac speed degradation with length can be modeled using the simulator for further calibration purposes. Application to frac modeling calibration is presented through different case studies. The simulator was used to directly generate the ‘waterfall plot’ output from the fibre-optic under a variety of scenarios. The history match to the large, detailed synthetic fibre dataset provided exceptional model calibration, enabling a detailed description of the fracture geometry, and a high-confidence estimation of key model parameters. The detailed synthetic fibre data generated by the simulator were remarkably consistent with the actual data. This indicates a good consistency with classical analytical fracture mechanics predictions and further confirm the interpretation of planar fracture propagation. This study shows how careful integration of offset-well fibre-optic measurements can provide detailed characterization of fracture geometry, growth rate, and physics. The result is a detailed picture of hydraulic fracture propagation in the Midland Basin. The comparison of the waterfall plot simulations and data indicate that hydraulic fractures can, in fact, be very well modeled as nearly-linear cracks (the ‘planar fracture modeling’ approach).
Erofeev, A. S. (Skolkovo Institute of Science and Technology/Digital Petroleum (Corresponding author) | Orlov, D. M. (email: email@example.com)) | Perets, D. S. (Skolkovo Institute of Science and Technology/Digital Petroleum) | Koroteev, D. A. (Gazprom Neft, Science and Technology Center)
Summary We studied the applicability of a gradient-boostingmachine-learning (ML) algorithm for forecasting of oil and total liquid production after hydraulic fracturing (HF). A thorough raw data study with data preprocessing algorithms was provided. The data set included 10 oil fields with more than 2,000 HF events. Each event has been characterized by well coordinates, geology, transport and storage properties, depths, and oil/liquid rates before fracturing for target and neighboring wells. Each ML model has been trained to predict monthly production rates right after fracturing and when the flows are stabilized. The gradient-boosting method justified its choice with R being approximately 0.7 to 0.8 on the test set for oil/total liquid production after HF. The developed ML prediction model does not require preliminary numerical simulations of a future HF design. The applied algorithm could be used as a new approach for HF candidate selection based on the real-time state of the field.
Summary Low-frequency distributed-acoustic-sensing (LF-DAS) strain data are direct measurements of in-situ rock deformation during hydraulic-fracturing treatments. In addition to monitoring fracture propagation and identifying fracture hits, quantitative strain measurements of LF-DAS provide opportunities to quantify fracture geometries. Recently, we proposed a Green’s function–based algorithm for the inversion of LF-DAS strain data (Liu et al. 2020b) that shows an accurate estimation of fracture width near the monitor well with single-cluster completions. However, multicluster completions with tighter cluster spacings are more commonly adopted in recent completion designs. One main challenge in the inversion of LF-DAS strain data under such circumstances is that strain measurements at fracture-hit locations by LF-DAS are not reliable, which makes the individual contribution of each fracture to the measured strain data indistinguishable. In this study, we first extended the inversion algorithm to handle multiple fractures, investigated the uncertainties of the inversion results, and proposed possible mitigation to the challenges raised by completion designs and field data acquisition through a synthetic case study. Ideally, there are available data on both sides of each fracture so that the inverted width of each fracture can be obtained with a negligible error. In reality, the strain data are usually limited, providing less constraint on the width of individual fracture. Nevertheless, the inversion results provide an accurate estimation of the width summation of all fractures. To evaluate the individual fracture width, a time-dependent constraint is added to the inversion algorithm. We assume that the width at the current timestep is dependent on the width at the previous step and the width variation between the two timesteps. The width variation can be roughly estimated from LF-DASstrain-rate data at the fracture-hit location. This extra constraint helps to improve the inversion performance. Finally, a field example is presented. We show the width summation of all fractures and the width of each individual fracture as a function of treatment time. The time-dependent width profiles show consistent trends with the LF-DASstrain-rate data. The calculated strains from the inverted model match well with the LF-DAS measured strain data. The findings demonstrate the potential of LF-DAS data for quantitative hydraulic-fracture characterization and provide insights on better use of LF-DAS data. The direct information on fracture width helps to calibrate fracturing models and optimize the completion designs.
Jin, Ge (Colorado School of Mines (Corresponding author) | Ugueto, Gustavo (email: firstname.lastname@example.org)) | Wojtaszek, Magdalena (Shell Exploration and Production Company) | Guzik, Artur (Shell International) | Jurick, Dana (Neubrex Co., Ltd.) | Kishida, Kinzo (Neubrex Energy Services)
Summary The characteristics of hydraulic fractures in the near-wellbore region contain critical information related to the production performance of unconventional wells. We demonstrate a novel application of a fiber-optic-based distributed strain sensing (DSS) technology to measure and characterize near-wellbore fractures and perforation cluster efficiency during production. Distributed fiber-optic-based strain measurements are made based on the frequency shift of the Rayleigh scatter spectrum, which is linearly dependent on strain and temperature changes of the sensing fiber. Strain changes along the wellbore are continuously measured during the shut-in and reopening operations of a well. After removing temperature effects, extensional strain changes can be observed at locations around the perforation cluster during a shut-in period. We interpret that the observed strain changes are caused by near-wellbore fracture aperture changes caused by pressure increases within the near-wellbore fracture network. The depth locations of the measured strain changes correlate well with distributed acoustic sensing (DAS) acoustic intensity measurements that were measured during the stimulation of the well. The shape and magnitude of the strain changes differ significantly between two completion designs in the same well. Different dependencies between strain and borehole pressure can be observed at most of the perforation clusters between the shut-in and reopening periods. We assess that this new type of distributed fiber-optic measurement method can significantly improve understanding of near-wellbore hydraulic fracture characteristics and the relationships between stimulation and production from unconventional oil and gas wells.
Filev, Maksim (JSC NK Kondaneft) | Soldatov, Vadim (JSC NK Kondaneft) | Novikov, Igor (GeoSplit LLC) | Xu, Jianhua (GeoSplit LLC) | Ovchinnikov, Kirill (GeoSplit LLC) | Belova, Anna (GeoSplit LLC) | Drobot, Albina (GeoSplit LLC)
Abstract The tracer-based production logging technology can be used to obtain the well production data continuously for several years without the need for risky well interventions and expensive equipment. The paper examines the case of placing polymer-coated tracers dopped proppant in a horizontal well with ten multi-stage frac intervals and using two different tracers dopped proppant codes for two frac ports (the first and the last ones) to identify the performance of the far and near zones of a hydraulic fracture. Upon the completion of the hydraulic fracturing operations, the collected reservoir fluid samples were studied in the laboratory. Chemical tracers contained in the samples were detected by flow cytofluorometry using custom-tailored machine learning-based software. The studies helped identify the productivity of each frac port, calculate the contribution of each port in percentage points, and also evaluate the productivity of the near and far hydraulic fracture zones in the first and the last intervals. The analysis provided data on the exact content of oil and water in the production profile for each frac interval. The results of tracer-based logging in the well in question revealed that the interval productivity is changing in the course of several months of surveillance. The most productive ports and those showing increasing oil flow rate were identified during quantitative analysis. The use of tracer dopped proppant with different codes within one multi-stage frac interval enabled detecting a peak release of chemical tracers from the far fracture zone in the initial periods of well operation followed by a consistent smoothing of the far and near zones’ production profiles. Laboratory analysis of reservoir fluid samples and hydraulic fracturing simulations proved the uniform distribution of proppant across the entire reservoir pay zone and laid the foundation for further research required to better understand the fracture geometry and reduce uncertainties in production optimization operations.
As with most technology, proper candidate selection is key to success. The economics are often determined by the number of and locations of the wells and by the overall geographical development plan. It is important to recognize that downhole processing is not a substitute for prudent profile control of wells through workovers, gel polymer treatments, cement squeezes, and so on. The following discussion applies to both gas/liquid and water/oil processing, followed by sections that discuss screening criteria specific to each. From an equipment standpoint, gas/liquid separation is much easier than oil/water separation. This generally means that it is a more robust application. All separation and pump equipment has an expected lifetime that is typically much shorter than the lifetime of the well. The cost of replacing or repairing the equipment must be considered as well as the initial capital cost.