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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.
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 The main functions of hydraulic fracturing fluids are to create a fracture network and to carry and place the proppant into the created fractures networks, thus, adding to fracture conductivity. Significant research has been performed to develop ideal fracturing fluid systems. The development focus has mainly been on optimization of a fluid rheology that can transport and place the proppant into the primary and any subsidiary fractures with less damage to the formation and at a lower cost. The main goal of this work is to add to the understanding and optimization of proppant transport in complex hydraulic fracture networks. Specifically for this study, focus is placed on two different fluids, water-glycerin solution and water-sodium chloride solution, representing varying fluid densities and viscosities. The effects of changing fluid viscosities, densities, proppant densities, proppant sizes, proppant concentrations, and slurry injection rates on proppant transport were then experimentally investigated. This experimental work shows that viscosity has a greater impact on the proppant transport than fluid density does, thus implying a larger impact on the resulting fracture conductivity. The results of this work show that a water-glycerin solution, with a viscosity of 4.3 cp, has significant proppant carrying capacity with proppants delivered uniformly to greater distances. On the other hand, the results show that a water-sodium chloride solution of 9.24 ppg density has less capability to carry the proppant deep into the fractures indicating that viscosity has a greater impact on the proppant transport than fluid density does. The lab results also showed that increasing proppant concentrations and injection rates has a positive impact on proppant transport.
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.
Tian, Ye (Southwest Petroleum University and Colorado School of Mines) | Zhang, Chi (Colorado School of Mines) | Lei, Zhengdong (Research Institute of Petroleum Exploration and Development) | Yin, Xiaolong (Colorado School of Mines) | Kazemi, Hossein (Colorado School of Mines) | Wu, Yu-Shu (Colorado School of Mines (Corresponding author)
Summary Most simulators currently use the advection/diffusion model (ADM), where the total flux comprises Darcian advection and Fickian diffusion. However, significant errors can arise, especially for modeling diffusion processes in fractured unconventional reservoirs, if diffusion is modeled by the conventional Fick’s law using molar concentration. Hence, we propose an improved multicomponent diffusion model for fractured reservoirs to better quantify the multiphase multicomponent transport across the fracture/matrix interface. We first give a modified formulation of the Maxwell-Stefan (MS) equation to model the multicomponent diffusion driven by the chemical potential gradients. A physics-based modification is proposed for the ADM in fractured reservoirs, where fracture, matrix, and their interface are represented by three different yet interconnected flow domains to honor the flux continuity at the fracture/matrix interface. The added interface using a more representative fluid saturation and composition of the interface can hence better capture the transient mass fluxes between fracture and matrix. The proposed approach is also implemented in an in-house compositional simulator. The multicomponent diffusion model is validated with both intraphase and interphase diffusion experiments. Then, the improved model for fracture/matrix interaction is compared with a fine-grid model. The proposed multiple interacting continua (MINC) model with three continua (MINC3) can better match the fine-grid model’s result than the double-porosity (DP) model, which only obtains a fair match at an early time. Then, we simulate a gas huff ‘n’ puff (HnP) well in the Permian Basin to investigate the effect of diffusion within the fractured tight oil reservoir. The simulation reveals that diffusion has a minor effect on the performance of depletion when oil is the dominant phase. For gas HnP, the simulation neglecting diffusion will underestimate the oil recovery factor (RF) but overestimate the gas rate. The DP approach tends to overestimate the RF of heavy components but leads to a similar cumulative oil RF compared with MINC3. With the diffusion included in the simulation, gas HnP performance becomes more sensitive to the soaking time than the model without diffusion. Although increasing the soaking time will lead to a higher RF after considering diffusion, the incremental oil is not sufficiently large to justify a prolonged soaking time.
Abstract Pressure-transient analysis (PTA) is widely used in the industry to estimate fracture half-length, height, and skin due to hydraulic fracturing as well as reservoir parameters. PTA studies focus on pressure data from long shut-in periods and diagnostic fracture injection tests (DFITs), while analyzing the pressure data recorded during the hydraulic fracture treatment has been overlooked. This paper details the state-of-the-art in applying pressure transient analysis to better estimate hydraulic fracture conductivity and dimensions and improve treatment designs stage by stage. The initial portion of this paper describes the application of a novel and low-cost diagnostic method for post-fracture analysis. The bulk of the paper is dedicated to present case histories that illustrate the PTA of the recorded pressure data during treatment to obtain estimates of fracture dimensions and conductivity. The pressure recorded during each stage is processed to ensure the proper data quality and the pressure falloff at the end of the stage is filtered out. The pressure is then analyzed for multi-cluster, finite-conductivity fractures, to obtain the fracture half-length, conductivity, and leakoff. Calculated parameters from each stage are compared to provide insights into the hydraulic fracture design and confirm the adequacy of the treatment design along the well. The results from stage leakoff pressure analysis are very valuable in confirming relative fracture conductivity and providing a qualitative measure of fracture length and height. The total stimulated reservoir area (SRA) calculated using the proposed method yields comparable values to SRA obtained from buildup analysis. The information provided is as valuable and comparable as that from direct near-wellbore diagnostics, such as radioactive traces, temperature logging, real-time micro-seismic monitoring, and production logging. The paper proposes a novel, low-cost analytical PTA method for estimating fracture dimensions, skin, and leakoff coefficient. We illustrate – with several field cases – that conventional post-fracture techniques can be integrated with the stage by stage PTA analysis to provide not only a more consistent and systematic analysis but also a more accurate assessment of treatment effectiveness. The findings of this paper help improve the efficiency of multistage hydraulic fracturing stimulation of horizontal wells.
Abstract Determining the closure pressure is crucial for optimal hydraulic fracturing design and successful execution of fracturing treatment. Historically, the use of diagnostic tests before the main fracturing treatment has significantly advanced to gain more information about the pattern of fracture propagation and fluid performance to optimize the designs. The goal is to inject a small volume of fracturing fluid to breakdown the formation and create small fracture geometry, then once pumping is stopped the pressure decline is analyzed to observe the fracture closure. Many analytical methods such as G-Function, square root of time, etc. have been developed to determine the fracture closure pressure. There are cases in which there is difficulty in determining the fracture closure pressure, as well as personal bias and field experiences make it challenging to interpret the changes in the pressure derivative slope and identify fracture closure. These conditions include: High permeability reservoirs where fracture closure occurs very fast due to the quick fluid leakoff. Extremely low permeability reservoir, which requires a long shut-in time for the fluid to leak off and determine the fracture closure pressure. The non-ideal fluid leak-off behavior under complex conditions. The objective of this study is to apply machine learning methods to implement a predesigned algorithm to execute the required tasks and predict the fracture closure pressure while minimizing the shortcomings in determining the closure pressure for non-ideal or subjective conditions. This paper demonstrates training different supervised machine learning algorithms to help predict fracture closure pressure. The workflow involves using the datasets to train and optimize the models, which subsequently are used to predict the closure pressure of testing data. The output results are then compared with actual results from more than 120 DFIT data points. We further propose an integrated approach to feature selection and dataset processing and study the effects of data processing on the success of the model prediction. The results from this study limit the subjectivity and the need for the experience of personal interpreting the data. We speculate that a linear regression and MLP neural network algorithms can yield high scores in the prediction of fracture closure pressure.
Wang, Shihao (Colorado School of Mines) | Di, Yuan (Peking University) | Winterfeld, Philip H. (Colorado School of Mines) | Li, Jun (King Fahd University of Petroleum and Minerals) | Zhou, Xianmin (King Fahd University of Petroleum and Minerals) | Wu, Yu-Shu (Colorado School of Mines) | Yao, Bowen (Colorado School of Mines)
Summary In this paper, we aim to enhance our understanding of the multiphysical processes in carbon dioxide (CO2)-enhanced-oil-recovery (EOR) (CO2-EOR) operations using a modeling approach. We present the development of a comprehensive mathematical model for thermal/hydraulic/mechanical (THM) simulation of CO2-EOR processes. We adopt the integrated-finite-difference method to simulate coupled THM processes during CO2-EOR in conventional and unconventional reservoirs. In our method, the governing equations of the multiphysical THM processes are solved fully coupled on the same unstructured grid. To rigorously simulate the phase behavior of a three-phase, nonisothermal system, a three-phase flash-calculation module, dependent on the minimization of Gibbs energy, is implemented in the simulator. The simulator is thus applicable to both miscible and immiscible flooding simulations under isothermal and nonisothermal conditions. We have investigated the effect of cold-CO2 injection on injectivity as well as on phase behavior. We conclude that cold-CO2 injection is an effective way to increase injectivity in tight oil reservoirs and reduces overriding effect in high-water-bearing reservoirs. Using the developed general simulation framework, we have discovered and studied several intriguing multiphysical phenomena that cannot be captured by commonly used reservoir simulators, including the temperature-decreasing phenomenon near the production well and the permeability-enhancement effect induced by the thermal unloading process. These phenomena can be captured only by the fully coupled multiphysical model. The novelty of this paper lies in its integration of multiple physical simulation modules to form a general simulation framework to capture realistic flow and transport processes during CO2 flooding, and in revealing the behavior of cold-CO2 injection under THM effects.
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.