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Abstract In this case study, we apply a novel fracture imaging and interpretation workflow to take a systematic look at hydraulic fractures captured during thorugh fracture coring at the Hydraulic Fracturing Test Site (HFTS) in Midland Basin. Digital fracture maps rendered using high resolution 3D laser scans are analyzed for fracture morphology and roughness. Analysis of hydraulic fracture faces show that the roughness varies systematically in clusters with average cluster separation of approximately 20' along the core. While isolated smooth hydraulic fractures are observed in the dataset, very rough fractures are found to be accompanied by proximal smoother fractures. Roughness distribution also helps understand the effect of stresses on fracture distribution. Locally, fracture roughness seems to vary with fracture orientations indicating possible inter-fracture stress effects. At the scale of stage lengths however, we see evidence of inter-stage stress effects. We also observe fracture morphology being strongly driven by rock properties and changes in lithology. Identified proppant distribution along the cored interval is also correlated with roughness variations and we observe strong positive correlation between proppant concentrations and fracture roughness at the local scale. Finally, based on the observed distribution of hydraulic fracture properties, we propose a conceptual spatio-temporal model of fracture propagation which can help explain the hydraulic fracture roughness distribution and ties in other observations as well.
Abstract In previous frac designs, proppant tracer logs revealed poor proppant distribution between clusters. In this study, various technologies were utilized to improve cluster efficiency, primarily focusing on selecting perforations in like-rock, adjusting perforation designs and the use of diverters. Effectiveness of the changes were analyzed using proppant tracer. This study consisted of a group of four wells completed sequentially. Sections of each well were divided into completion design groups characterized by different perforating methodologies. Perforation placement was primarily driven by RockMSE (Mechanical Specific Energy), a calculation derived from drilling data that relates to a rock's compressive strength. Additionally, the RockMSE values were compared alongside three different datasets: gamma ray collected while drilling, a calculation of stresses from accelerometer data placed at the bit, and Pulsed Neutron Cross Dipole Sonic log data. The results of this study showed strong indications that fluid flow is greatly affected by rock strength as mapped with the RockMSE, with fluid preferentially entering areas with low RockMSE. It was found that placing clusters in similar rock types yielded an improved fluid distribution. Additional improved fluid distribution was observed by adjusting hole diameter, number of perforations and pump rate.
Abstract Uniformity of proppant distribution among multiple perforation clusters affects treatment efficiency in multistage fractured wells stimulated using the plug-and-perf technique. Multiple physical phenomena taking place in the well and perforation tunnels can cause uneven proppant distribution among multiple clusters. The problem has been studied in the recent years with experimental and computational fluid dynamics (CFD) methods, which provide useful insights but are impractical for routine designs. Simplified models that incorporated the proppant transport efficiency (PTE) correlation derived from the CFD results in a hydraulic fracture model have been also presented in literature. In this paper, we present a numerical model that simulates the transient proppant slurry flow in the wellbore, considering proppant transport and settling including bed formation, rate- and concentration-dependent pressure drop, PTE, and dynamic pressure coupling with the hydraulic fractures. The model is efficient and is designed to be an independent wellbore transport model so it can be integrated with any fracture models, including fully 3D and/or complex fracture network models, for practical design optimization. The model predictions are compared and found to agree with previously published studies. Parametric studies demonstrate sensitivity of proppant distribution to grain size, fluid viscosity, and pumping rate for fixed perforation designs. Analysis of the simulation results shows that the dominant cause of uneven proppant distribution is proppant inertia. Possible slurry stratification is less important, except for the cases with relatively low flow rates and near toe clusters. Accordingly, proppant distribution is less sensitive to perforation phasing than to the number of perforations in clusters. Alterations of the number of perforations per cluster within a stage enable achieving more even proppant distribution.
Kebert, Brent (Colorado School of Mines) | Almulhim, Abdulraof (Colorado School of Mines) | Miskimins, Jennifer (Colorado School of Mines) | Hunter, William (Ovintiv Inc) | Soehner, Gage (Ovintiv Inc)
Abstract Successfully treating each cluster within a hydraulic fracturing stage is a key objective for "plug-n-perf" well completions. Most operating companies would agree that the main underlying desire for a successful completion is related to future production capability. In unconventional reservoirs, propped and conductive hydraulic fractures are the primary completion result that drives production and reserve recovery. When designing a treatment, the spacing of clusters is critical to optimizing production and reserve recovery parameters, and therefore, even proppant distribution across a single stage delivers a well the greatest potential for optimized production performance. Diverting the fracturing fluid and proppant evenly across the clusters in a stage allows the greatest opportunity for each cluster to produce equally and drain the associated reservoir volume. Generating equal, producing fractures across a horizontal wellbore is a difficult problem that operators are still trying to solve. This work models the fluid and proppant distribution across a field-scale, 250-ft long, horizontal hydraulic fracturing stage, replicating realistic field conditions. By utilizing computational fluid dynamics (CFD), this paper investigates the effected proppant distribution results from a fracturing stage mimicking the presence of both a leaking plug and the impacts of stress shadowing. The proppant concentration throughout the wellbore, along with internal wellbore pressure and velocity, are also reviewed to gain an understanding of the effect of the field conditions. Additionally, this paper illustrates the effect of different proppant "ramping" conditions during the fracturing stage. Proppant ramping schedules can be smooth or sharp when increasing proppant concentration, which alters the proppant concentrations throughout the wellbore and associated perforation clusters. Unanticipated alterations of the proppant concentration within the wellbore can lead to early screenouts. Gaining a better understanding of the proppant distribution and concentration inside the wellbore can lead to improved designs of hydraulic fracturing completions.
Liu, Xinghui (Chevron Corporation) | Wang, Jiehao (Chevron Corporation) | Singh, Amit (Chevron Corporation) | Rijken, Margaretha (Chevron Corporation) | Chrusch, Larry (Chevron Corporation) | Wehunt, Dean (Chevron Corporation) | Ahmad, Faraj (Colorado School of Mines) | Miskimins, Jennifer (Colorado School of Mines)
Abstract Multi-stage plug-n-perf fracturing of horizontal wells has proven to be an effective method to develop unconventional reservoirs. Various studies have shown uneven fluid and proppant distributions across all perforation clusters. It is commonly believed that both fracturing fluid and proppant contribute to unconventional well performance. Achieving uniform fluid and proppant placement is an important step toward optimal stimulation. This paper discusses how to achieve such uniform placement in each stage via a CFD (Computational Fluid Dynamics) modeling approach. CFD models in several lab scales were built and calibrated using experimental data of proppant transport through horizontal pipes in several laboratory configurations. A field-scale model was then built and validated using perforation erosion data from downhole camera observations and the same model parameters calibrated in the lab-scale model. With the field-scale model validated, CFD simulations were performed to evaluate the impact of key parameters on fluid and proppant placement in individual perforations and clusters. Some key parameters investigated in this study included perforation parameters (size, orientation, number), cluster spacing, cluster count per stage, fluid properties, proppant properties, pumping rates, casing sizes, and stress shadow effects, etc. Both lab and CFD results show that bottom-side perforations receive significantly more proppant than top-side perforations due to gravitational effects. Lab and CFD results also show that proppant distribution is increasingly toe-biased at higher rates. Proppant concentration along the wellbore from heel to toe generally varies significantly. Gravity, momentum, viscous drag, and turbulent dispersion are key factors affecting proppant transport in horizontal wellbores. This study demonstrates that near-uniform fluid and proppant placement across all clusters in each stage is achievable by optimizing perforation, cluster, and other treatment design factors. Validated CFD modeling plays an important role in this design optimization process.
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.
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.
Abstract Proppant transport in horizontal wellbores has received significant industry focus over the past decade. One of the most challenging tasks in the hydraulic fracturing of a horizontal well is to predict the proppant concentration that enters each perforation cluster within the same stage. The main objective of this research is to investigate the effect of different limited-entry perforation configurations on proppant transport, settling, and distribution across different perforation clusters in multistage horizontal wells. To simulate a fracturing stage in a horizontal wellbore, a laboratory-based 30-foot horizontal clear apparatus with three perforation clusters is used. Fresh water (~1 cp) is utilized as the carrier fluid to transport the proppant. This research incorporates the effect of testing three different injection rates each at four different proppant concentrations on proppant transport. Different limited-entry perforation configurations are also used to test the perforation effect on proppant transport using similar injection rates and proppant concentrations for the same proppant size. The proppant is mixed with fresh water in a 200-gallon tank for at least 10 minutes to ensure the consistency of the slurry mixture. The mixture is then injected into the transparent horizontal wellbore through a slurry pump. This laboratory apparatus also includes a variable frequency drive, a flow meter, and two pressure transducers located right before the first two perforation clusters. Sieve analysis is conducted to understand the ability of fresh water to carry bigger particles of the mixture at different injection rates, proppant concentrations, and perforation configurations. The results show different fluid and proppant distributions occur when altering the perforation configurations, injection rates, and proppant concentrations. The effect of gravity is extreme when using a limited entry configuration at each cluster (1 SPF) located at the bottom of the pipe, especially at low injection rates, resulting in uneven proppant distribution with a heal-biased distribution. However, even proppant distribution is observed by changing the limited entry perforation configuration to the top of the horizontal pipe at similar injection rates and low proppant concentration. Increasing the proppant concentration reduces the void spaces between the particles and pushes them away toward the toe cluster. Even proppant distribution is also observed across the three perforation clusters when using high flow rates and a 2 SPF perforation configuration located at both the top and the bottom of the pipe. The results of the sieve analyses show different size distributions of the settled and exited proppant through different perforations and clusters. This illustrates the ability of fresh water to transport different percentages of different proppant sizes to different perforations and clusters within a single stage. Frequently, the injected proppant is assumed to be distributed evenly across the perforation clusters and that the distribution of fluid and proppant is identical. However, this research adds data to the portfolio that this assumption is generally not valid. Additionally, the distribution of the transported proppant is observed to be different across individual clusters and different perforations within each cluster. Such information is beneficial to understanding transport in horizontal, multi-stage completions and how such impacts the overall treatment efficiency, especially when employing limited-entry perforation techniques.
Mao, Shaowen (Texas A&M University) | Siddhamshetty, Prashanth (Texas A&M University) | Zhang, Zhuo (Texas A&M University) | Yu, Wei (University of Texas at Austin) | Chun, Troy (Texas A&M University) | Kwon, Joseph Sang-Il (Texas A&M University) | Wu, Kan (Texas A&M University)
Summary Slickwater fracturing has become one of the most leveraging completion technologies in unlocking hydrocarbon in unconventional reservoirs. In slickwater treatments, proppant transport becomes a big concern because of the inefficiency of low-viscosity fluids to suspend the particles. Many studies have been devoted to proppant transport experimentally and numerically. However, only a few focused on the proppant pumping schedules in slickwater fracturing. The impact of proppant schedules on well production remains unclear. The goal of our work is to simulate the proppant transport under real pumping schedules (multisize proppants and varying concentration) at the field scale and quantitatively evaluate the effects of proppant schedules on well production for slickwater fracturing. The workflow consists of three steps. First, a validated 3D multiphase particle-in-cell (MP-PIC) model has been used to simulate the proppant transport at real pumping schedules in a field-scale fracture (180-m length, 30-m height). Second, we applied a propped fracture conductivity model to calculate the distribution of propped fracture width, permeability, and fracture conductivity. In the last step, we incorporated the fracture geometry, propped fracture conductivity, and the estimated unpropped fracture conductivity into a reservoir simulation model to predict gas production. Based on the field designs of pumping schedules in slickwater treatments, we have generated four proppant schedules, in which 100-mesh and 40/70-mesh proppants were loaded successively with stair-stepped and incremental stages. The first three were used to study the effects of the mass percentages of the multisize proppants. From Schedules 1 through 3, the mass percentage of 100-mesh proppants is 30, 50, and 70%, respectively. Schedule 4 has the same proppant percentage as Schedule 2 but has a flush stage after slurry injection. The comparison between Schedules 2 and 4 enables us to evaluate the effect of the flush stage on well production. The results indicate that the proppant schedule has a significant influence on treatment performance. The schedule with a higher percentage of 100-mesh proppants has a longer proppant transport distance, a larger propped fracture area, but a lower propped fracture conductivity. Then, the reservoir simulation results show that both the small and large percentages of 100-mesh proppants cannot maximize well production because of the corresponding small propped area and low propped fracture conductivity. Schedule 2, with a median percentage (50%) of 100-mesh proppants, has the highest 1,000-day cumulative gas production. For Schedule 4, the flush stage significantly benefits the gas production by 8.2% because of a longer and more uniform proppant bed along the fracture. In this paper, for the first time, we provide both the qualitative explanation and quantitative evaluation for the impact of proppant pumping schedules on the performance of slickwater treatments at the field scale by using an integrated numerical simulation workflow, providing crucial insights for the design of proppant schedules in the field slickwater treatments.
Summary Plug-and-perforation (P-n-P) completion has been widely used in horizontal wells for the development of unconventional reservoirs. In the field, uneven proppant distribution among different fractures within a fracturing stage has been frequently observed in P-n-P treatments, leaving a large portion of reservoir volume understimulated. In this paper, an efficient 3D multiphase particle-in-cell (MP-PIC) method has been used to simulate proppant transport among multiple fractures (fracture near the heel, middle fracture, fracture near the toe) at the field scale. This work studies the fundamental physics of the proppant transport process and reveals the mechanisms of uneven proppant placement, giving strategies to improve the proppant placement. Before applying the MP-PIC method to field-scale problems, we conducted indoor experiments to validate the model. The simulation results show an excellent agreement with the vertical slot experimental results. After model validation, we used the MP-PIC method to directly simulate the field process of proppant transport, involving slurry transport from the wellbore through perforation holes and finally into fractures. A base case with three fractures in a stage was first established to calculate the percentage of proppant mass distribution in each fracture. Then, we performed the sensitivity analysis of both proppant size and injection rate to investigate their effects on proppant placement. The results reveal that all the cases tend to have a heel-biased proppant distribution among three fractures, which agrees with the field observations. There are two reasons for the heel-biased proppant distribution. First, at the very beginning of the injection, more proppants tend to flow toward the toe side because of large momentum. As more and more proppants move to the toe side, the concentration near the toe side gradually increases, which adds flow resistance to the newly injected proppants. Therefore, most newly injected proppants will go to the first fracture. The second reason comes from the fracture geometry. Because the first fracture has the largest fracture width among three fractures, it has the smallest flow resistance for proppant transport. More slurry will flow into the first fracture. Apart from giving explanations for the heel-biased distribution, we also suggest some strategies to improve the proppant distribution. The sensitivity analysis shows that the strong heel-biased proppant distribution can be mitigated by optimizing the proppant size and injection rate. Our study for the first time conducts a field-scale numerical investigation of proppant transport in the wellbore-fracture system during P-n-P treatments. The results can provide us with more insights into the optimization of fracture design in field practice.