Hydraulic Fracturing Treatment Research Articles

Implication of Fast Shear Wave Azimuth and Critically Stressed Fractures in Coalbed Methane Reservoir

The orientation of fractures and stresses within coal seams plays a critical role in gas production from coalbed methane reservoirs. In this study, we utilized resistivity images and sonic logs to investigate these parameters, aiming to (i) establish the relationship between fracture orientations and the polarization angles of fast shear waves, and (ii) detect active fractures in the coal seam. Shear waves in anisotropic formations split into fast and slow components, with Alford’s rotation method used to determine the polarization angles of the fast shear wave. We found that the fast shear wave aligns with the direction of higher fracture intensity. Subsequently, we incorporated the poroelastic strain model to estimate vertical (Sv), maximum horizontal (SH), and minimum horizontal (Sh) stresses in the wellbore. These stress magnitudes aided in identifying the faulting regime and were corroborated by vertical opening mode fractures. Validation of SH and Sh involved comparison with breakout width in image logs and closure pressure observed during hydraulic fracturing treatments. Applying Mohr’s Coulomb criteria, the stress model discerned the state of fractures, transforming stress magnitudes into shear and effective normal stress on each fracture plane. Our observations indicated that identified fractures existed in a non-critically stressed condition, suggesting a lack of interconnectivity among them. These findings correspond to the absence of gas production to date, providing insights into the dynamics of fractures and their impact on production behavior.

Identifying perforation locations for hydraulic fracturing treatment in deep and tight sandstone gas reservoirs

Fracture initiation has been a challenging issue for fracturing deep and tight gas reservoirs, which generally requires a high breakdown pressure for hydraulic fracturing treatment. In this situation, fluid injections frequently have to terminate at the very beginning. Toward predicting and solving this issue, a novel fracturing system for deep and tight sandstone gas reservoirs was developed. The key components of the fracturing system and some criterion will be introduced, which can be used to optimize the ideal perforation locations along the landing part and select the right perforation strategy accordingly. The main components of the fracturing system include: (1) evaluating the log-based diagenetic rock typing and flow index; (2) 1D mechanical earth model; (3) calculating the breakdown pressure envelope along the well trajectory of the landing part; (4) calculating the optimal perforation directions along the landing part; (5) select the first set of perforation locations based on the log-based diagenetic rock typing and flow index; (6) narrowing down the first set of perforation locations to a second set of perforation locations based on the breakdown pressure envelope; (7) determining a perforation strategy based on breakdown pressure envelope and wellhead pressure safety limit in the second set of perforation locations. The computational framework to calculate the breakdown pressure envelope and optimal perforation directions is applicable to arbitrary well trajectory. The fracturing system has been used to provide pre-fracturing suggestions for wells landed in deep and tight sandstone reservoirs, which is very efficient for identifying locations with good rock typing and relatively low breakdown pressure. Also, it can indicate whether oriented perforation should be used further for alleviating breakdown issue. By taking these efforts and procedures, the fracturing success rate for deep and tight sandstone gas reservoirs can be improved, which has been verified in practice. Example studies from the field will be provided to demonstrate the fracturing system's performance and applicability.

Quantitative characterization of imbibition in fractured porous media based on fractal theory

In low-permeability reservoirs, such as shale and tight sandstone, imbibition is an important mechanism for enhancing oil recovery. After hydraulic fracturing treatment, these reservoirs create a network of fracture pathways for fluid flow. Therefore, understanding the imbibition mechanisms in fractured porous media and quantitatively characterizing oil–water distribution are crucial for the development of low-permeability reservoirs. In this study, a mathematical model of two-phase flow in porous media with branching fractures was established. The phase-field method was employed to track the oil–water interface, and quantitative characterization of imbibition was conducted based on fractal theory, and the effects of wetting phase injection rate, the number of disconnected fractures, fracture spacing, and fracture morphology on imbibition in branched fracture porous media were discussed. The research findings indicate that in branched fracture porous media, both co-current and countercurrent imbibition processes occur simultaneously, and there exists a diffusion interface layer with a certain thickness at the oil–water interface. The hydraulic pressure generated by the wetting phase injection rate provides the driving force for imbibition oil recovery, but it also affects the contact time between the wetting and non-wetting phases. The presence of disconnected fractures hinders the propagation of hydraulic pressure, reducing the effectiveness of imbibition. The imbibition displacement zone is limited and occurs only within a certain range near the fractures. As the number of branching fractures increases, the channels for the wetting phase to enter matrix pores are enhanced, resulting in higher efficiency of imbibition displacement of the oil phase. The results of this research can provide guidance for the design of fracturing programs and recovery prediction in low-permeability reservoirs.

Advanced Deep Learning for microseismic events prediction for hydraulic fracture treatment via Continuous Wavelet Transform

Understanding hydraulic fracture propagation events would enable operators to estimate the fracture geometry, understand formation/fracture interactions, and estimate the total microseismic events cloud. This paper introduces a new method for understanding the dynamic fracture propagation events using a signal processing technique. Detection of the dynamic fracture event using continuous wavelet transform (CWT) is used to train a deep learning model with microseismic events to predict this cloud for every hydraulic fracture job. The deep learning model is used for the same formation. The CWT for treatment pressure is a convolution process that involves the application of a wavelet signal to the acquired pressure signal in a continuous manner. The wavelet is stretched, or compressed, and is moved along the acquired pressure signal, acting as a generic microscope to highlight small changes in the treating pressure signal. Using CWT as a mathematical microscope to discern diverse signals has been adopted by numerous engineering and medical applications since the 1990s.A normalized CWT scalogram for fracture-treating pressure is thus created as a unique representation of each fracture propagation mode in the hydraulic fracturing job. The new technique is calibrated with several fracture simulation runs and real field data using the previous techniques like moving reference point (MRP). That previous technique which has been previously validated through fracture simulation, is used as a calibration for the new normalized CWT scalogram technique. The technique was finally calibrated by comparing it with micro-seismic events recorded by the Marcellus Shale Energy and Environment Laboratory (MSEEL).The results of this comparison were exceptionally accurate. It can be used to train a deep learning model that can be used to estimate the cloud of microseismic events for hydraulic fracture jobs in Marcellus shale. The new deep learning framework uses CWT to convert the treating pressure during hydraulic fracture propagation to dimensionless representation (normalized CWT scalogram) which acts as a mathematical microscope for the fracture treating pressure on different wavelet stretch or compressions, enabling the detection of the major changes in the treating pressure then train the deep learning model to estimate microseismic events cloud.

Numerical investigation of mechanical responses and failure features of coal measure strata using combined finite-discrete element method

Investigating the mechanical responses and failure features of the deep coal measure strata (CMS) is essential for designing hydraulic fracturing treatments and preventing geological dynamic hazards in underground engineering. In this paper, a three-dimensional CMS model is established by the combined finite-discrete element method (FDEM). The mechanical properties, stress evolutions and failure features of the CMS with different lithological combinations (sandstone-coal-sandstone (SCS), sandstone-coal-mudstone (SCM) and mudstone-coal-mudstone (MCM)) and thickness ratios are investigated under the uniaxial compressive condition. Results indicate that the SCS combination exhibits the highest uniaxial compressive strength (UCS) and elastic modulus, followed by the SCM and MCM combinations. The mechanical properties of the CMS are predominantly determined by the softer coal layer. The mechanical contrasts in elastic modulus and Poisson’s ratio between adjacent layers cause the generation of additional compressive stress in the softer layer and additional tensile stress in the stiffer layer. Therefore, the softer coal layer exhibits the shear-dominated failure pattern while the stiffer sandstone/mudstone layer displays the tensile-dominated failure pattern in the CMS. Furthermore, as the thickness ratio of the coal layer increases, the UCS, elastic modulus, and interfacial constraint stress decrease in the CMS. Additionally, the UCS and stress–strain relationship in the post-peak stage exhibit the noticeable size effect, whereas the mechanical behaviors in the pre-peak stage and the ultimate fracture patterns show the opposite. The elastic modulus and interfacial constraint stress obtained by the FDEM simulation match well with those calculated by theoretical models. The key findings of this paper can provide fundamental understanding and reliable parameters for multi-scale geomechanical modeling in petroleum and mining engineering.

Analysis of Fluid-Injection-Induced Seismicity Using a Dynamic Sliding Model Incorporating the Rate- and State-Dependent Friction Law

Summary Earthquakes can be triggered by fluid injection into underground formations. Fluid injection can cause large changes in the underground volume that exert stresses on nearby preexisting faults, leading to seismic activity. Assuming an increase in underground development activities in the future, our understanding of the mechanism underlying induced seismicity must be improved, and methods must be developed to properly assess the risk of seismic events. The objective of this study is to develop a seismicity prediction model that calculates the magnitude and timing of triggered earthquakes or seismic events occurring during various subsurface fluid injection activities. We developed an injection-induced seismicity analysis model that predicts the dynamic earthquake nucleation caused by changes in stress and pore pressure that occur during various subsurface activities. The governing equations consisting of the dynamic motion of the poroelastic spring-slider system, rate and state friction laws and pore pressure diffusion equation were solved using the embedded semi-implicit Runge-Kutta (SIRK) method. The dynamic sliding model was also incorporated into the finite element method (FEM) model, considering the variations in the stresses and pore pressures in the formation. A field case study was also conducted to compare the model results with typical microseismicity responses observed from hydraulic fracturing treatments in shale fields. Contrary to the popular understanding derived from Amonton’s law, the dynamic friction model revealed that a large normal stress on the fault leads to rapid sliding. A larger normal stress accumulates a large amount of elastic energy until it slips owing to fluid injection, nucleating large seismic waves. The poroelastic spring-slider model estimated reasonable microseismic magnitudes for hydraulic fracturing treatment but overestimated the time required to trigger a microseismic event under field conditions. To improve the analysis results, the poroelastic spring-slider model was coupled with a linear elastic FEM that considered the complex interplay of stress changes from hydraulic fracturing and the associated pore pressure variation in the formation. Compared with the field data, the coupled simulation model estimated a reasonable timing for the induced microseismic events when the increasing pore pressure during hydraulic fracturing penetrated deep into the formation. These findings suggest the existence of permeable natural fractures in the formation, which intensify early frictional sliding during treatment. The seismicity prediction model presented in this study simulates the magnitude and timing of seismic nucleation, helping to manage and mitigate the environmental impacts of induced seismicity during various subsurface development activities, such as oil and gas extraction, hydraulic fracturing, geothermal, and carbon dioxide sequestration. Moreover, the case study results imply that the time series of seismic events predicted by the model can be used to understand the possible fracture geometry and extent of fluid invasion for field applications. Key Terms and Phrases induced seismicity, subsurface fluid injection, rate- and state-dependent friction law, embedded semi-implicit Runge-Kutta method, finite element analysis

Cyclical hydraulic pressure pulses reduce breakdown pressure and initiate staged fracture growth in PMMA

Using unique experimental equipment on large bench-scale samples of Polymethylmethacrylate, used in the literature as an analogue for shale, we investigate the potential benefits of applying cyclical hydraulic pressure pulses to enhance the near-well connectivity through hydraulic fracturing treatment. Under unconfined and confined stresses, equivalent to a depth of up to 530 m, we use dynamic high-resolution strain measurements from fibre optic cables, complemented by optical recordings of fracture development, and investigate the impact of cyclical hydraulic pressure pulses on the number of cycles to failure in Polymethylmethacrylate at different temperatures. Our results indicate that a significant reduction in breakdown pressure can be achieved. This suggests that cyclic pressure pulses could require lower power consumption, as well as reduced fluid injection volumes and injection rates during stimulation, which could minimise the occurrence of the largest induced seismic events. Our results show that fractures develop in stages under repeated pressure cycles. This suggests that Cyclic Fluid Pressurization Systems could be effective in managing damage build-up and increasing permeability. This is achieved by forming numerous small fractures and reducing the size and occurrence of large fracturing events that produce large seismic events. Our results offer new insight into cyclical hydraulic fracturing treatments and provide a unique data set for benchmarking numerical models of fracture initiation and propagation.

Numerical study of hydraulic fractures propagation in deep fracture-cavity reservoir based on continuous damage theory

Natural fractures and cavities are the primary spaces for oil and gas accumulation in fracture-cavity carbonate reservoirs. Establishing the connection between these spaces and the wellbore through hydraulic fracturing treatment is important for oil and gas extraction from such reservoirs. Due to the discontinuity and heterogeneity of the existing natural fracture-cavity system, anticipating the viability of hydraulic fracturing treatment is troublesome. A new method to simulate the hydraulic fracturing propagation in fracture-cavity reservoirs is proposed based on the continuous damage theory. The method considers the random spatial distribution of fractures and cavities and can simulate the arbitrary expansion of hydraulic fractures in the three-dimensional direction. Based on this method, the influence of different geological and engineering factors on the propagation patterns of hydraulic fractures in the fracture-cavity reservoirs is investigated. It is found that the increase of reservoir burial depth significantly limits the propagation ranges of hydraulic fractures. The propagation modes of hydraulic fractures encountering natural fractures change with increasing burial depth, undergoing a transition from “penetrate and deflect” to ”defect” and then to ”penetrate”. The reduction of horizontal stress difference increases the complexity of hydraulic fractures, but it is not conducive for hydraulic fractures to connect more natural fractures and cavities. The increase in fracturing pump rate is significantly beneficial for hydraulic fractures to connect more natural fractures and cavities. The viscosity of fracturing fluid has a significant impact on the morphology of hydraulic fracture propagation, which undergoes a transition from simple to complex, and then to simple with the change of the fracturing fluid viscosity from low to high. either too high or too low viscosity of the fracturing fluid is not conducive to the connection of more natural fractures and cavities by hydraulic fractures. The obtained conclusions can provide a reference for the design of hydraulic fracturing treatment for fracture-cavity carbonate reservoirs.

Fracture Height Quantification from Vertical and Horizontal Section Fiber Measurements: A Comprehensive Study Using LF-DAS Measurements from HFTS-2 Data Set

Summary Understanding fracture height growth is critical for optimizing hydraulic fracture treatments and field development. In recent years, low-frequency distributed acoustic sensing (LF-DAS) has become a popular tool for monitoring strain changes during hydraulic fracturing. While LF-DAS data from vertical monitoring wells (VMWs) can be used to determine fracture height, measurements from the vertical section of horizontal wells may have the potential to capture fracture height growth. The objectives of this study are (1) to apply three methods—(a) using the vertical section of horizontal fiber measurements, (b) using the vertical fiber measurements, and (c) using the horizontal section of horizontal fiber measurements—to determine the fracture height using the Hydraulic Fracturing Test Site 2 (HFTS-2) data set and (2) to demonstrate the reliability of using LF-DAS measurements from the vertical section of horizontal fibers for fracture height determination. In an effort to determine the fracture height from the HFTS-2 data set using the three methods, we demonstrate the reliability of the height prediction using strain measurements in the vertical section of the horizontal monitoring well (VS-HMW). First, we analyze the measurements from the vertical section of the horizontal fiber (B3H) during the stimulation of the heel-most stages of the horizontal wells (B1H, B2H, and B4H). Second, we analyze the measurements from the VMW (B5PH) during the stimulations of B1H, B2H, and B4H. Third, we use a geomechanical inversion algorithm to obtain height estimates from the horizontal section of the LF-DAS measurements at B3H during B1H, B2H, and B4H stimulations. The fracture height is determined based on the transition of the extension-compression zone in the LF-DAS measurements from the vertical sections. The height estimates obtained using the three methods are compared and found to be consistent in the six well pairs we analyzed. The LF-DAS measurements from the vertical well B5PH provide a complete height profile, while measurements from the vertical section capture fracture growth from the upper tip of the fracture to the landing depth of the horizontal well. The fracture height estimates obtained from our inversion algorithm represent the average height value of all fracture hits at the chosen stage. This study demonstrates the potential to determine fracture height growth using LF-DAS measurements in the vertical section of a horizontal well, thus avoiding the cost associated with drilling VMWs to obtain fracture heights.

Numerical Simulation Study on the Effect of Preinjected CO2 on the Hydraulic Fracturing Behavior of Shale Oil Reservoirs.

Due to the low permeability and apparent mechanical anisotropy of shale reservoirs, shale oil production highly depends on the performance of hydraulic fracturing of the tight reservoir. Pre-injection of CO2 before hydraulic fracturing treatment has been proven beneficial to enhance shale oil production. A comprehensive understanding of the effect of changes in the properties of shale reservoirs after preinjected CO2 on the hydraulic fracturing behavior of shale reservoirs is essential to improve the stimulated reservoir volume (SRV) of shale oil reservoirs. In this study, comprehensive evaluating parameters were proposed to specify the variation of mechanical properties of shale rock at different soaking times of CO2 based on published testing parameters of shale. Accordingly, a three-dimensional (3D) numerical model was established and three groups of horizontal well fracturing cases with different cluster spacings were conducted based on the adaptive FE-DE method to simulate and compare the hydraulic fracturing behavior in the reservoirs with different mechanical properties. We established a quantitative relationship between the alterations in reservoir properties and the stimulated reservoir volume. The results indicate that both the brittleness and conductivity properties of shale rock are dramatically improved as the increment of soaking time of CO2. It is beneficial to improve the SRV, and the initiation pressure is reduced with the increment of soaking time of CO2. However, as the stress shadow effect is involved in the horizontal well fracturing, the complexity of the hydrofracturing crack is significantly enhanced to restrain the development of hydrofracturing crack. When the cluster spacing is larger, the stress shadow effect is weakened, and the weakening effect of CO2 soaking on reservoir is more obvious.

Natural fractures at depth in shale reservoirs: new insights from the southern Sichuan Basin marine shales

Natural fractures are pervasive in southern Sichuan Basin marine shales, China, and provide a useful opportunity to try to understand subsurface fracture networks in shale reservoirs. Based on cores and electrical imaging logs from vertical and horizontal petroleum wells in the southern Sichuan Basin, four types of natural fractures were identified in terms of orientation, size, filling properties and spatial distribution. Uncemented bed-parallel shear fractures develop at or in the vicinity of mechanical interfaces and are inclined to present in shale layers with a dip angle greater than 12°. Cemented bed-parallel fractures are characterized by a crack-seal texture marked by multiple bands of fibrous cement, and their intensity decreases upwards and shows a positive relationship with total organic carbon (TOC) values. Uncemented bed-oblique fractures are a type of fracture that rarely develops, and accommodate limited open space. Cemented bed-oblique/perpendicular fractures are the most developed fracture type and are distributed on a regional scale and are subdivided into two types. The results imply that these shale fractures could be formed sequentially by local and regional tectonic deformation, and by abnormally high pressure. Most natural fractures cannot contribute to reservoir storage or efficiently enhance its permeability, yet can act as planes of weakness and be potentially reactivated during hydraulic fracture treatments.

Advances in hydraulic fracture characterization via borehole microseismic and strain monitoring

We analyze the impact and challenges associated with microseismic monitoring in the development of unconventional reservoirs. We detail advanced methods that address some of these challenges and discuss emerging data analysis and acquisition technologies such as those provided by fiber-optic monitoring. During the development of unconventional resources, it is important to understand the stimulated rock volume obtained from the hydraulic fracturing treatment. Microseismic monitoring is one of the sources of information for estimating stimulated rock volume in which accurate hypocenter calculations provide the horizontal and vertical fracture geometry and extent. We developed hypocenter waveform-based relocation and collapsing techniques and demonstrated these on synthetic and field data to obtain an enhanced description of the fracture geometry. We further provide the initial analysis of a recently acquired data set composed of multiple monitoring wells instrumented with geophones and fiber optics operating simultaneously. Microseismic events recorded by the multiwell dual geophone/fiber setup show meaningful signal-to-noise ratio to enable a joint interpretation. Additional strain and temperature data provided by dynamic fiber-optic measurements extend the interpretation capabilities of the hydraulic fracturing phenomenon while providing an avenue for advanced research on fracture characterization.

Quantitative Analysis of Hydraulic Fracturing Test Site 2 Completion Designs Using Crosswell Strain Measurement

Summary The implementation of effective completion design configurations during hydraulic stimulation is critical for the economic development of unconventional reservoirs. Low-frequency distributed acoustic sensing (LF-DAS)-based crosswell strain measurement is an advanced monitoring technique used to diagnose completion design efficiency but has been primarily restricted to qualitative analysis. In this study, we apply our novel Green-function based inversion algorithm to calculate fracture geometry (i.e., width) using the Department of Energy sponsored Hydraulic Fracturing Test Site 2 (HFTS-2) data set. The adopted algorithm relies on a 3D displacement discontinuity method to construct geomechanical models inverting linear elastic strain to hydraulic fracture widths. We use the inversion algorithm to calculate dynamic fracture widths using LF-DAS data recorded at two horizontal monitoring wells with permanent optical fiber installations. The inverted fracture widths at the monitoring wells from more than 100 hydraulic fracturing stages are used to diagnose the efficiency of eight unique completion designs implemented across three fracturing wells. We develop several metrics to evaluate completion design efficiency including the evenness of fracture widths at the monitoring wells, fracture density (i.e., number of fracture hits per foot), and fracture-width-density (i.e., fracture width/stage length). We observe a significant impact on completion efficiency with varying degrees of limited entry, tapered configurations, and stage length designs. Results indicate improved hydraulic stimulation is achieved with the implementation of limited-entry designs for extended stage lengths (ESLs), but no observable trend for normal stage lengths (NSLs). Tapered configurations significantly improve efficiency for ESLs but indicate little impact on normal-length designs. Reducing the space between perforation clusters (PCs) is determined to negatively impact design performance. Additionally, our quantitative analysis describes the impact of the nearby depletion zone on completion design efficiency. The methodology developed in this study provides operators with another level of quantitative information to optimize hydraulic fracturing treatments and reduce costs associated with the development of unconventional wells.

Analysis of dynamic thermal behaviors for multi-stage hydraulic fracturing treatments in horizontal shale oil and shale gas wells

Accurate prediction of dynamic thermal behaviors during multi-stage hydraulic fracturing is profound which can avoid performance deterioration of fracturing fluids or failure of fracturing tools caused by severe temperature variation. This paper establishes a transient heat transfer model for multi-stage hydraulic fracturing in horizontal shale oil and shale gas wells (MFHWM), considering the real construction process of multi-stage hydraulic fracturing, the turbulent flow state, the heat source of viscous dissipation and the complex wellbore structure, which enables the accurate simulation of thermal behaviors in the early time of multi-stage hydraulic fracturing with large flow rate. The verification results of measured temperature data and simulation data prove the MFHWM has good precision. Numerical simulations indicate that the temperature distribution exhibits the characteristics of cyclic “cool-down” and “warm-back” and “stair-step” during the multi-stage hydraulic fracturing. In the “cool-down” period, the temperature drops sharply within the first hour and then the deceleration slows down. In the “warm-back” period, the temperature recovers exponentially relying on the shut-in time. The “stair-step” is caused by changing of heat transfer mechanism from convection to conduction. Moreover, the cyclic cooling has little effect on the total temperature drop and subsequent stages are not significantly cooler than previous stages. Besides, primary factors affecting temperature distributions of wellbore-formation system are discussed thoroughly. Results indicate that the viscous heat source cannot be ignored for multi-stage hydraulic fracturing and the temperature difference exhibits cyclic variation when considering and without considering the viscous heat source. In addition, the minimum temperature during each-stage-fracturing operation decreases first and then increases as the injection rate of fracturing fluid increases because of the compromise between the viscous heat source and forced convection. Furthermore, temperature distributions can be controlled by changing the injection temperature of fracturing fluid. As the injection temperature increases, a positive proportional relationship exists between the minimum temperature of fracturing fluid and the injection temperature. MFHWM can be a standalone tool to analyze temperature distributions of multi-stage hydraulic fracturing. It can also be used to provide better boundary conditions for stress analysis model of casing and cement sheath.

Transportation and deposition of oval and cylindrical shaped proppant particles in complex-fracture systems

Hydraulic fracturing treatment can create complex fractures to provide oil and natural gas flow path. To achieve a high conductivity, the proppant should be placed properly in the fractures. Up to date, nearly all proppant materials used are spherical or nearly spherical particles and the effect of proppant shape is rarely reported. In this work, we investigate the flow, transport and deposition of non-spherical proppant particles in complex fractures. The results show that in the primary fracture, the packing patterns of ovals behave as spheres, but cylinders show a significant difference. Ovals can enter subsidiary fractures at a lower pump rate than cylinders and spheres. The effect of fluid viscosity on the packing pattern is also examined, revealing a significant influence in the primary fracture, but not much in the subsidiary fracture. The proppant transportation efficiency decreases with increasing the fluid viscosity for the conditions considered in this work.

Stochastic inversion for equivalent hydraulic fracture characterization using low-frequency distributed acoustic sensing data

Distributed fiber-optic sensing, a game-changing technology, has been successfully applied in monitoring hydraulic fracturing treatments. The cross-well fiber-optic strain/strain-rate responses are directly related to the fracture-propagation process and dynamic fracture geometry. Extracting the insightful information regarding hydraulic fractures requires robust interpretation workflows. In this paper, we aim to develop a stochastic inversion approach to characterize the dynamic equivalent fracture geometry and quantify the associated uncertainties using cross-well low-frequency distributed acoustic sensing (LF-DAS) measurements. A fast analytical forward solver based on the 3D displacement discontinuity method is developed to model the strain. The objective function is the sum-of-squares error between the modeled strain and the measured strain. We focus on an equivalent fracture geometry with a predefined length centered around the monitoring well, which is a reasonable assumption considering the spatial sensitivity of LF-DAS. Therefore, the model parameters reduce to fracture width and height of the equivalent fracture. We adopted the delayed rejection adaptive metropolis (DRAM) algorithm, an efficient Markov-chain Monte Carlo (MCMC)-based method, to perform the optimization. The efficiency and accuracy of the algorithm are tested using a synthetic case that has three monitoring wells at different locations. The mean values of fracture width and height are both close to the true values with negligible standard deviations for all the three monitoring wells. The algorithm performance is not sensitive to the initial guess and the predefined length needs to be large enough. Then, a field case with a single cluster from the HFTS-2 project is presented. The fracture width increases from about 0.5 mm to about 0.9 mm during the pumping stage and gradually decreases during the shut-in period. The fracture height changes during the pumping stage and stabilizes at about 150 m during the shut-in period, the trend of which is consistent with the LF-DAS signals from the offset vertical monitoring well. To the best of our knowledge, this is the first algorithm that can efficiently quantify the fracture width and height simultaneously. The results could provide novel insights on the characteristics of fracture geometry and significantly improve the understanding of complex fracture propagation processes in subsurface reservoirs.

Fracture Initiation and Propagation in the Hot Dry Rock Subject to the Cyclic Injection Hydraulic Fracturing Treatment

Cyclic injection hydraulic fracturing is a promising way for the geothermal energy exploitation by reactivating the fractures in geothermal reservoir. However, fracture initiation and growth induced by cyclic injection schemes have been inadequately studied for hot dry rock (HDR), and the cyclic injection fracturing optimized often by experience. For this reason, the initiation and propagation of hydraulic fractures in the HDR under different cyclic injection methods were determined by experiment research for hydraulic fracturing. The results show that the cyclic frequency and injection rate play different roles in the stimulation of HDR. The cyclic injection with low frequency-low pressure can create more branched fractures, forming a short but complex hydraulic fracture network. However, when high flow-high frequency injection method is subjected, the branch fractures formed are significantly reduced, but each branch fracture can be fully expanded. To fully exploit the advantages of different injection methods, a numerical model that contains a fracture network was established with PFC software, and an alternating cyclic injection scheme with synergistic control of the cyclic frequency and injection rate was proposed. The comparison results indicated that the alternating cyclic injection method can effectively improve the fracturing effect in the HDR. The stimulation area of the alternating cyclic injection method is about 2.3 times and 2.7 times that of the low flow-low frequency and high flow-high frequency injection methods, respectively. The method presented here can be adopted to optimize the fracture growth regime and provide a scientific basis for EGS hydraulic fracturing design.

Deep neural network model for estimating montney shale gas production using reservoir, geomechanics, and hydraulic fracture treatment parameters

The development of a shale gas project requires an accurate prediction of the production potential owing to the high cost of horizontal well drilling and hydraulic fracturing treatment. Previous research developed models for estimating shale gas production based on the reservoir and hydraulic fracturing data. They reported a high degree of uncertainty in the prediction as a result of the fracture properties' locking information. This research aims to reduce the uncertainty in shale gas production prediction by developing a deep neural network (DNN) model that incorporates reservoir, geomechanics, and fracture treatment parameters to predict monthly Montney shale gas production. The DNN model, optimized using the Keras Tuner optimization tool, employs a unique architecture of eight hidden layers and integrates production time as an input feature. This allows the model to predict production rates at any time point in the reservoir's life cycle. The prediction model was developed using 102,000 simulation data and blind tested using other 18,000 unseen simulation data, which were achieved by coupling a hydraulic fracture simulator with a reservoir simulator. The model revealed an average error of 13.41%, with a promising correlation between predicted and simulated gas production rates (R2 > 0.85), and cumulative gas production (R2 > 0.89). These results demonstrate the model's accuracy in predicting Montney shale gas production and its utility in assessing the economic viability of shale gas projects. In conclusion, the research introduces an important advancement in reducing uncertainty in shale gas production prediction, providing an accurate tool that has wide applications in assessing the viability of shale gas projects and suggesting further exploration in refining the prediction techniques for other geological formations.

Experimental and Simulation Investigation on Ball-Sealer Transport and Diversion Performance Aided by Machine Learning Method

Summary Ball-sealer diversion has been proven to be an effective and economical way to increase fractures and fracturing volume in multistage hydraulic fracturing and matrix acidizing treatments. However, designing and implementing a successful ball-sealer diversion treatment is still challenging. Typically, operators rely on empirical data to determine diversion parameters and need an understanding of accurate ball transport and diversion behaviors. A model for optimizing operating parameters, including fluid and ball properties, and predicting the diversion performance of ball sealers before treatment is needed for designing the fracturing process. In this work, we systematically investigated ball-sealer diversion using experimental and numerical methods. The resolved model of computational fluid dynamics (CFD) and discrete element method (DEM) is first developed to simulate the transport of a large ball in a horizontal wellbore with side holes. The experimental results validated the numerical model. The effects of the ball position in the pipe, flow ratio of the hole to pipe, injection flow rate, and ball density on the diversion performance were studied under field parameters. The results show that the ball sealer easily misses the heel-side perforation due to the inertial effect and travels to the toe side due to the large inertia and turbulent flow. The ball position and flow rate ratio are crucial for the diversion performance. There is a threshold value of the ball position under the specific condition, and the ball successfully turns to the perforation only when the threshold distance is met. A ball sealer closer to the perforation will have a larger probability of blocking the hole than the ball at the other side of the wellbore. The larger the flow rate ratio, the more the drag force on the ball, and the ball can successfully divert to the perforation despite the ball being far from the hole. The injection flow rate and ball density negatively correlate with the diversion performance due to the large inertia and gravity. The best classification result with the F1 score of 87.0% in the prediction set was achieved using the random forest (RF) algorithm. It provides new insight into developing ball sealers and adjusting fracturing parameters based on machine learning (ML) methods.

Aperture size distribution, length, and preferential location of bed-parallel veins in shale

Bed-parallel, calcite-filled veins (BPVs) are common in shale formations, and although they have been widely described in other studies, little is known about their population aperture size distribution. To address this knowledge gap, we analyzed BPV sizes in outcrops and cores from the Vaca Muerta Formation, Neuquén Basin, Argentina; in two cores from the Marcellus Formation, Appalachian Basin, northeast Pennsylvania; and in one core from the Wolfcamp Shale, Delaware Basin, West Texas. Nine out of ten aperture size populations follow a negative exponential distribution, with one following a weak power law. Bed-parallel vein size distribution and intensity vary among formations and within the same shale. We define three groups of distributions: (1) Vaca Muerta outcrops, with the highest BPV intensity and the largest BPVs (cumulative frequency of 4.9 BPVs per meter [BPVs/m] for apertures 0.265 mm to 8.7 cm); (2) Vaca Muerta cores with a similar BPV intensity overall but with no apertures wider than 1.2 cm; and (3) Vaca Muerta, Wolfcamp, and Marcellus cores with the fewest BPVs (cumulative frequency up to 0.63 BPVs/m) and very few wider than 1 cm. Aperture and length in two outcrop data sets are weakly positively correlated and follow power laws with exponents of 0.44 and 0.49. Mechanical interfaces at boundaries between different lithologies exert a strong control on BPV location, with 65–75% of observed interfaces having BPVs along them. Only 25–30% of the BPVs occur at observed material interfaces, however, and unless subtle, unobserved mechanical layering is present, other factors must also control location. BPV intensity and organic richness (TOC) from Vaca Muerta well logs are correlated in some instances but not in others, indicating TOC is not always a good proxy for BPV location or intensity. These findings provide useful information for modeling of hydraulic fracture treatments where BPVs may influence development of the stimulated fracture network, for example by limiting height growth.