Fracture Geometry Research Articles

Evaluation of hydraulic fracturing of horizontal wells in tight reservoirs based on the deep neural network with physical constraints

Accurate diagnosis of fracture geometry and conductivity is of great challenge due to the complex morphology of volumetric fracture network. In this study, a DNN (deep neural network) model was proposed to predict fracture parameters for the evaluation of the fracturing effects. Field experience and the law of fracture volume conservation were incorporated as physical constraints to improve the prediction accuracy due to small amount of data. A combined neural network was adopted to input both static geological and dynamic fracturing data. The structure of the DNN was optimized and the model was validated through k-fold cross-validation. Results indicate that this DNN model is capable of predicting the fracture parameters accurately with a low relative error of under 10% and good generalization ability. The adoptions of the combined neural network, physical constraints, and k-fold cross-validation improve the model performance. Specifically, the root-mean-square error (RMSE) of the model decreases by 71.9% and 56% respectively with the combined neural network as the input model and the consideration of physical constraints. The mean square error (MRE) of fracture parameters reduces by 75% because the k-fold cross-validation improves the rationality of data set dividing. The model based on the DNN with physical constraints proposed in this study provides foundations for the optimization of fracturing design and improves the efficiency of fracture diagnosis in tight oil and gas reservoirs.

The simple shifted fracture method

AbstractWe propose a simplified version of the Shifted Fracture Method (SFM), which relies on an approximate fracture geometry representation combined with approximate interface conditions. In particular, we show that the complexities of earlier SFM implementations, associated with the use of a mixed variational formulation of the equilibrium equations, can be avoided. This approach has minimal impact on the overall accuracy of numerical computations but leads to considerable gains in performance. These outcomes can be justified because the proposed simplified SFM accurately accounts for the area of the fracture surface and prevents the severe mesh dependencies observed in classical cohesive zone models or node‐release/element‐deletion techniques. We also show that the proposed approach can be combined with a phase‐field model to more easily capture branching and merging of fractures.

Evaluation of Parent Well Depletion Effects on Fracture Geometry Based on Low-Frequency Distributed Acoustic Sensing in Hydraulic Fracture Test Site-2

Summary Low-frequency distributed acoustic sensing (LF-DAS) has recently received much attention for its ability to monitor fracture propagation at offset wells. Hydraulic Fracture Test Site-2 (HFTS-2), a Department of Energy–sponsored field-based research experiment, has acquired LF-DAS data sets during the stimulation of many horizontal wells in the Wolfcamp Formation of the Permian Basin. Over 100 stimulated stages with different completion designs in four horizontal wells were monitored by two horizontal offset wells and one vertical pilot hole with permanent fibers. The parent well depletion affected all four horizontal wells in almost half of their lateral section. Several studies have been performed on the acquired comprehensive data set. In this study, we apply our novel Green’s function-based inversion algorithm to calculate the fracture width of each stage and investigate the impact of parent well depletion on fracture geometry. The Green’s function-based inversion algorithm has been successfully applied to a few stages of field case studies. The Green’s function matrix was built based on linear elasticity theory (3D displacement discontinuity method) to relate the fracture openings with strain responses measured along the length of the fiber. This novel algorithm only relies on measured strain to solve fracture geometry at the monitoring well. Therefore, it is independent of the physics of the fracture propagation process and can be used to validate hydraulic fracture modeling results. Using our inversion algorithm, we can efficiently and quantitatively interpret LF-DAS data to provide information on fracture geometry and completion efficiency. We analyze more than 100 stages of the LF-DAS measurements obtained at the fiber wells B3H and B4H during B1H, B2H, and B4H stimulations. We apply our inversion algorithm for four data sets covering the stimulation of the abovementioned three wells. The fracture growth at stages in the parent well’s depleted zone is biased more toward upper formation and in the easterly direction. The fracture width at the stages in the parent well’s depletion zone is reduced compared to fracture widths at stages in the nondepleted zone irrespective of the monitoring well location relative to the treatment wells. This difference in fracture widths will affect the proppant distribution to a great extent, thereby affecting the effectiveness of the stimulation. We also illustrate the application of the inversion algorithm for stages that have both conventional fracture hits with “heart-shaped” signals as well as fracture reopening signals. Our inversion algorithm gives a reasonable estimate of the fracture width that aligns with the qualitative analysis of microseismic data sets and statistic summary of fracture hit numbers of HFTS-2. We believe that this quantitative study provides us with insights into the fracture geometry due to parent well depletion effects.

A Numerical Model for Pressure Analysis of a Well in Unconventional Fractured Reservoirs

Fractured reservoirs are highly heterogeneous in both matrix and fracture properties, which results in significant variations in well production. Assessing and quantifying the influence of fractures on fluid flow is essential for developing unconventional reservoirs. The complicated effects of fractures in unconventional fractured reservoirs on fluid flow highly depend on fracture geometry, fracture distribution, and fracture properties, which can be reflected in pressure transient testing. The biggest challenge lies in delineating the pre-existing natural fracture distribution pattern, density, azimuth, and connectivity. Using the advanced finite element method, this paper builds a finely characterized near-wellbore model to numerically simulate the pressure transient testing process in naturally fractured reservoirs and further evaluates fracture-related effects to obtain a more accurate solution. First, the numerical program is benchmarked by the analytical solutions and numerical results of Eclipse. Next, different fracture models with single fractures or fracture networks are set up to investigate the effects of fracture parameters numerically (e.g., fracture location, fracture dip angle, fracture spacing, the ratio of fracture permeability to matrix permeability, fracture network orientation, horizontal fracture distribution, etc.) on pressure transient behaviors in naturally fractured reservoirs. Velocity and pressure profiles are presented to visualize and analyze their effects, and new features in the flow regimes of the derivative plots of the bottom-hole pressure are identified and discussed. Finally, based on geological and geophysical data, including image logs, core descriptions, wireline logs, and seismic and well test data, a practical fractured model of the Dalwogan 2 well in the Surat basin is built, analyzed, and compared with homogenous and measured data. The results show significance in characterizing the complex fracture networks in near-wellbore models of unconventional fractured reservoirs.

Multicluster Fractures Propagation during Temporary Plugging Fracturing in Naturally Fractured Reservoirs Integrated with Dynamic Perforation Erosion

Summary Temporary plugging technology has been widely applied in multicluster fracturing for the uniform growth of multiple fractures. To investigate the propagation behavior of multiple fractures and explore a better fracturing scheme during temporary plugging fracturing, a 2D finite element method (FEM)-discrete fracture network (DFN) model is established. An improved traction-separation law is used to describe the constitutive behavior of fractures under different types of stress. The model is further integrated with the perforation pressure drop model, considering the dynamic perforation erosion effect to simulate the fracture geometry more accurately. Based on the model, the impact of the perforation erosion effect on the propagation of multicluster fractures in the naturally fractured reservoir is quantitatively evaluated first. The result showed that the effect can intensify the nonuniformity among multicluster fractures, especially under the condition of small cluster spacing. Then, the simulation for temporary plugging fracturing is carried out under different cluster spacings. Finally, the plugging time optimization in temporary plugging fracturing is explored. The model and results presented in this paper can provide new insight into the impact of the perforation erosion effect and exploration for plugging time optimization in temporary plugging fracturing.

Development of numerical model-based machine learning algorithms for different healing stages of distal radius fracture healing

Background and objectivesEarly therapeutic exercises are vital for the healing of distal radius fractures (DRFs) treated with the volar locking plate. However, current development of rehabilitation plans using computational simulation is normally time-consuming and requires high computational power. Thus, there is a clear need for developing machine learning (ML) based algorithms that are easy for end-users to implement in daily clinical practice. The purpose of the present study is to develop optimal ML algorithms for designing effective DRF physiotherapy programs at different stages of healing. MethodFirst, a three-dimensional computational model for the healing of DRF was developed by integrating mechano-regulated cell differentiation, tissue formation and angiogenesis. The model is capable of predicting time-dependant healing outcomes based on different physiologically relevant loading conditions, fracture geometries, gap sizes, and healing time. After being validated using available clinical data, the developed computational model was implemented to generate a total of 3600 clinical data for training the ML models. Finally, the optimal ML algorithm for each healing stage was identified. ResultsThe selection of the optimal ML algorithm depends on the healing stage. The results from this study show that cubic support vector machine (SVM) has the best performance in predicting the healing outcomes at the early stage of healing, while trilayered ANN outperforms other ML algorithms in the late stage of healing. The outcomes from the developed optimal ML algorithms indicate that Smith fractures with medium gap sizes could enhance the healing of DRF by inducing larger cartilaginous callus, while Colles fractures with large gap sizes may lead to delayed healing by bringing excessive fibrous tissues. ConclusionsML represents a promising approach for developing efficient and effective patient-specific rehabilitation strategies. However, ML algorithms at different healing stages need to be carefully chosen before being implemented in clinical applications.

Cyclic Liquid Nitrogen Fracturing Performance on Coal with Various Coal Ranks: Laboratory Investigation and Mechanism Analysis

Summary Hydraulic fracturing is one of the important stimulation methods to enhance the productivity of coalbed methane (CBM) wells. However, the commonly used water-based fracturing fluids can bring some bottlenecks such as large amount of water consumption, clay-mineral swelling, and poor fracturing performance on ductile coals. Cyclic liquid nitrogen (LN2) fracturing, as a novel nonaqueous stimulation method, has the potential to solve the above problems. In cyclic LN2 fracturing, supercooling LN2 is injected in a cyclic manner [i.e., alternating high injection rate (or pressure) and low injection rate (or pressure)]. Coals will be subjected to cyclic freeze-thaw, stress oscillation, and fatigue damage, which is expected to improve the stimulated reservoir volume. First, laboratory cyclic LN2 fracturing tests were conducted on coal samples with various coal ranks to investigate the fracture initiation/propagation behavior and fracture network patterns. Cyclic water fracturing tests were also conducted as comparisons. Then, computed tomography (CT) scanning and geomechanical/petrophysical properties tests before and after LN2 fracturing were performed to assist in understanding the cyclic LN2 fracturing mechanisms and implications. Finally, to solve the field application concerns, we investigated the possible fracture geometries at the field scale, temperature distribution of LN2 along the wellbore during injection, and the economic feasibility. The key factors affecting the temperature distribution during LN2 transportation along the wellbore were clarified for the first time. The results indicate that cyclic LN2 fracturing shows the potential to decrease the breakdown pressure and produce complex fracture networks. Different coal ranks have different responses to cyclic LN2 fracturing attributed to the variances in natural fracture development and geomechanical/petrophysical properties. Besides, increasing the cycle number is effective in enhancing the cyclic LN2 fracturing performance on coals with relatively higher geomechanical strengths and tighter rock mass. The suggested cycle numbers from low to high for different coal ranks are listed here: low-rank coal < high-rank coal < middle-rank coal. In field applications, gaseous nitrogen (N2) can be used as the annulus fluid to provide an effective insulation for heat transfer between the low-temperature LN2 and the surrounding environment. In addition, the net present value (NPV) analysis indicates that LN2 fracturing is an economically feasible stimulation method, which can exceed slickwater fracturing in some cases. The key findings are expected to provide preliminary insights into the potential field applications of cyclic LN2 fracturing in CBM or other unconventional oil/gas exploitation.

Understanding Subsurface Fracture Evolution Dynamics Using Time‐Lapse Full Waveform Inversion of Continuous Active‐Source Seismic Monitoring Data

AbstractPredicting the behavior, geometry, and flow properties of subsurface fractures remains a challenging problem. Seismic models that can characterize fractures usually suffer from low spatiotemporal resolution. Here, we develop a correlative double‐difference time‐lapse full waveform inversion of continuous active source seismic monitoring data for determining high‐spatiotemporal‐resolution time‐lapse Vp models of in‐situ fracture evolution at a shallow contamination site in Wyoming, USA. Assisted by rock physics modeling, we find that (a) rapidly increasing pore pressure initializes and grows the fracture, increasing the porosity slightly (from ∼13.7% to ∼14.6%) in the tight clay formation, thus decreasing Vp (∼50 m/s); (b) the fluid injection continues decreasing Vp, likely through the introduction of gas bubbles in the injectate; and (c) final Vp reductions reach over ∼150 m/s due to a posited ∼4.5% gas saturation. Our results demonstrate that high‐resolution Vp changes are indicative of mechanical and fluid changes within the fracture zone during hydrofracturing.

Numerical Simulation of Gas-Liquid Gravity Displacement in Vertical Fractures during Drilling of Carbonate Formations.

In petroleum drilling, carbonate formations characterized by natural fractures can result in troublesome gas-liquid gravity displacement, which refers to the phenomenon that the drilling mud leakage and gas kick are simultaneously triggered. This work focuses on clarifying the mechanism of gas-liquid displacement in vertical fractures during the drilling of carbonate formations and investigating the characteristics of gas-liquid displacement under various conditions. First, the bottom hole pressure allowing for gas-liquid gravity displacement is analyzed, which determines the coexistence condition of leakage and kick in vertical fractures. Then, a theoretical model of gas-liquid displacement flow in a vertical fracture is established. To verify the reliability and accuracy of the model, the results of numerical simulation are compared with those of a visualization experiment. The development process and flow characteristics of gas-liquid displacement in the fracture under different conditions are numerically simulated. The effects of pressure difference, drilling mud property, and fracture geometry on the gas-liquid displacement rate are analyzed. It is found that the drilling mud leakage rate increases with the increase of fracture width, fracture height, and drilling mud density, while it decreases with the increase of pressure difference and fracture length. The gas invasion rate increases with the increase of fracture width, fracture height, and pressure difference, while it decreases with the increase of drilling mud density and fracture length. The equations for leakage rate and gas invasion rate are derived by the response surface method, and the methods for mitigating gas-liquid gravity displacement are discussed. It is expected that the present work provides a better understanding of the gas-liquid gravity displacement in carbonate formations.

Simulation of hydraulic fracture initiation and propagation for glutenite formations based on discrete element method

The existence of gravels in the glutenite formations leads to the complex geometries of hydraulic fracturing propagation and difficult construction in fracturing engineering. To study the hydraulic fracturing propagation law of glutenite formations, this paper establishes a fracture propagation model for the heterogeneous glutenite formations based on discrete element method, and analyzes the effects of gravel content, particle size, distribution, horizontal stress difference, fracturing fluid viscosity and flow rate on hydraulic fracturing propagation behavior. Results show that the complex geometries of hydraulic fractures in glutenite formations can lead to the generation of branched fractures and fracture bifurcation. Small-sized gravels have little effect on the fracture propagation shape which leads to a single main fracture with a flat fracture surface, on the contrary, large-sized gravels may induce hydraulic fractures to deflect along the gravel interface and form branched fractures with distorted fracture surfaces. Hydraulic fractures can propagate around gravels under the condition of high stress difference, high viscosity and medium flow rate. Gravels can prevent the propagation of hydraulic fractures under low stress difference, low viscosity and small flow rate. Hydraulic fracture bifurcation can occur when encountering gravels under high stress difference and large displacement. Properly increasing the high viscosity of fracturing fluids can effectively promote the main hydraulic fracture propagation and reduce the fracture tortuosity, thereby avoiding sand up.

Fracture Extraction From Logging Image Using a Dual Encoder-Decoder Architecture With Swin Transformer

Imaging logging is a method of imaging the physical parameters of the borehole wall or the objects around the borehole according to the observation of the geophysical field in the borehole. Imaging logging data can determine the dip angle and structural characteristics of the formation and observe the geometry and development degree of fractures. The performance of existing target segmentation networks relies on large volumes of data. However, logging images are expensive to acquire, so how to effectively extract fractures from small samples of logging images is an urgent problem to be solved. Therefore, we developed a dual encoder-decoder structure using the Swin Transformer, which uses the self-attention mechanism of a hierarchical Vision Transformer with shifted window to model the remote context information. It can overcome the limitations of most convolutional neural network-based methods that cannot establish long-term dependencies and global contextual connections in convolutional operations. In addition, the shifted window mechanism substantially improves the computational efficiency of the model, and the hierarchical structure allows flexibility in modeling at different scales. At the same time, skip connections are established between adjacent layers of the structure, and the higher-level feature maps are stitched with the lower-level feature maps in channel dimensions, which can obtain more high-resolution detail information of fractures, and thus improve the segmentation accuracy. The experimental results show that the performance is better than the mainstream segmentation networks under small training sets of logging images. The effectiveness of our method reveals that it is practical in fracture extraction of logging images.

Late complex tensile fracturing interacts with topography at Cumbre Vieja, La Palma

Volcanic eruptions are often preceded by episodes of in ation and emplacement of magma along tensile fractures. Here we study the 2021 Tajogaite-Cumbre Vieja eruption on La Palma, Canary Islands, and present evidence for tensile fractures dissecting the new cone during the terminal stage of the eruption. We use synthetic aperture radar (SAR) observations, together with drone images and time-lapse camera data, to determine the timing, scale and complexities associated with a fracturing event, which is diverging at a topographic ridge. By comparing the field dataset with analogue models, we further explore the details of lens-shaped fractures that are characteristic for faults diverging at topographic highs and converging at topographic lows. The observations made at Cumbre Vieja and in our models are transferrable to other volcanoes and add further evidence that topography is substantially affecting the geometry and complexity of fractures and magma pathways, and the locations of eruptions.

Investigating the simultaneous fracture propagation from multiple perforation clusters in horizontal wells using 3D block discrete element method

Multi-cluster horizontal well fracturing is one of the key technologies to develop the unconventional reservoirs such as shales. However, the field data shows that some perforation clusters have little production contribution. In this study, a three-dimensional (3D) numerical model for simulating the multiple fracture propagation based on 3D block discrete element method was established, and this model considers the stress interference, perforation friction and fluid-mechanical coupling effect. In order to determine the most appropriate measures to improve the uniformity of multiple fracture propagation, the effect of the geologic and engineering parameters on the multiple fracture propagation in shale reservoirs is investigated. The modeling results show that the geometry of each fracture within a stage is different, and the outer fractures generally receive more fracturing fluid than the interior fractures. The vertical stress almost has no effect on the geometries of multiple fractures. However, higher horizontal stress difference, larger cluster spacing, smaller perforation number, higher injection rate, and smaller fracturing fluid viscosity are conducive to promote the uniform propagation of multiple fractures. The existence of bedding planes will increase the fluid filtration, resulting in a reduction in fracture length. The middle two fractures receive less fluid and the width of them is smaller. Through analyzing the numerical results, a large amount of fracturing fluid should be injected and the proppant with smaller size is suggested to be used to effectively prop the bedding planes. Cluster spacing and perforation number should be controlled in an appropriate range according to reservoir properties. Increasing the injection rate and reducing the viscosity of fracturing fluid are important means to improve the geometry of each fracture.

Numerical Simulation Research on the Effect of Artificial Barrier Properties on Fracture Height

Hydraulic fracturing is an important measurement for the stimulation of oil and gas wells and is widely used in the development of low-permeability and ultra-low-permeability reservoirs. However, fractures can pass through barriers with poor properties during fracturing, resulting in fractures that do not reach the pre-designed length. In a worse situation, it is possible to communicate with the water layer and cause sudden water flooding, resulting in the failure of the fracturing construction. In order to improve the efficiency of fracturing construction, an effective way to control the height of fractures is by laying diverting agents to form artificial barriers. In this study, we established a three-dimensional numerical calculation model of fracture propagation, considering artificial barriers in the finite element analysis framework; the fracture propagation is governed by a cohesive zone model. The influence of artificial barriers with different Young’s modulus and different permeability on the fracture height was simulated and calculated. Different fracture geometries under different pumping injection rates were also considered. The simulation results show that the smaller the Young’s modulus of the artificial barrier, the smaller the extension in the direction of the fracture height: when its Young’s modulus is 28 GPa, the half fracture height is about 25 m, while when Young’s modulus increases to 36 GPa, the half fracture height increases by about 10m. When the fracture does not penetrate the artificial barrier area, the larger the Young’s modulus, the smaller the fracture width and the larger the fracture height. With the change in the permeability of the artificial barrier, the change in the fracture width direction of the fracturing fracture is only about 0.5 m, but the inhibition on the fracture height direction is more obvious; in the case of maximum permeability and minimum permeability, the fracture height change is 10 m. The influence of pumping injection rates on the width and height of the fracture is obvious: with the increase in the pumping rates, both the height and width of the fractures increase. However, when the pumping rate increases from 0.12 m3/s to 0.14 m3/s, the change in the direction of fracture height is no longer significant, and the increase is only 0.6 m. This study investigates the role of artificial barrier properties and pumping rates in controlling fracture height extension, clarifies the feasibility of artificial barriers to control fracture height technology, and provides guidance for the selection of diverting agents and the determination of the pumping rate in the process of fracturing construction.

Applicability of the Continuum Mapping Approach for Groundwater Flow Modeling in 3D Fracture Networks

Abstract A methodology for simulating groundwater flow in three-dimensional (3D) stochastic fracture rocks based on a commonly used finite-difference method is presented in this paper. Different realizations of fracture networks are generated by the fracture continuum method (FCM), in which appropriate 3D cuboids are used to describe the geometry of fractures. Then, the effects of different parameter distributions on the fracture networks indicated that the length, orientation, and density of fractures all play significant roles in the connectivity of fractures in this methodology. Greater length and density and wider orientation range of fractures lead to greater connectivity. The proper contrast in hydraulic conductivities between the fractures and matrix is found to be approximately 105 due to the contribution of fluid flow in the matrix which can be ignored. It is shown that the fracture density plays a key role in stabilizing the equivalent hydraulic conductivity (Ke) of the fracture networks. Furthermore, the greater length and closer orientation of fractures to the general flow direction, the larger Ke of the generated fracture networks possess. The findings of this study can help for a better understanding of the mechanism of FCM and the influence of geometry characteristics on the hydraulic conductivity of FCM models.

Field-Scale Modeling of Interwell Tracer Flow Behavior to Characterize Complex Fracture Networks Based on the Embedded Discrete Fracture Model in a Naturally Fractured Reservoir

Summary In a naturally fractured reservoir, natural fractures can not only provide main paths for fluid flow and increase its permeability but also complicate flow behavior and production performance. Interwell tracer tests have been widely applied to estimate the petrophysical properties; however, limited attempts have been made to accurately identify the natural fracture networks. In this study, the newly proposed numerical models have been verified and used to characterize the fracture distributions in a naturally fractured reservoir conditioned to tracer transport behavior. The stochastic fracture modeling approach is implemented to generate the randomly distributed natural fractures which are dealt with the embedded discrete fracture model (EDFM) while ensuring its sufficient accuracy. To be specific, the matrix domain is discretized using the structured grids, within which each embedded fracture is divided into a series of segments. Subsequently, nonneighboring connections (NNCs) allow us to couple the flow of fluid and tracer between the nonneighboring grid cells, while the historical tracer profiles are matched to delineate the geometry and properties of the fractures by taking multiple tracer transport mechanisms into account. Furthermore, the influences of fracture number, fracture length, fracture orientation, and tracer dispersion on the tracer production concentration have been investigated through sensitivity analysis. The response of an interwell tracer model is sensitive to the fracture parameters rather than tracer properties. A fracture network with its orientation parallel to the mainstream direction will cause the earliest tracer breakthrough. The tracer breakthrough time with an average fracture length of 40 m is 110 days earlier than that with a mean fracture length value of 10 m, while the tracer production peak concentration for the former is nearly two times higher than for the latter. A larger fracture number results in an earlier tracer breakthrough, and an intermediate fracture number will lead to the highest tracer production concentration. Additionally, the newly developed model has been validated through its comparison with the commercial ECLIPSE simulator and then extended to field applications to identify the possible fracture distributions by simulating multiwell tracer tests in the Midale field. The flexible and pragmatic EDFM-based method developed in this study can model the interwell tracer flow behavior as well as characterize the properties and geometries of the natural fractures with better accuracy and calculation efficiency in comparison with other fracture simulation methods (e.g., local grid refinement method).

A Hydraulic Fracture Geometry Inversion Model Based on Distributed-Acoustic -Sensing Data

Summary Distributed-acoustic-sensing (DAS) data have been widely used to monitor multifracture hydraulic fracturing. Interpreting hydraulic fracture geometry (width and length) using DAS data is a popular topic of current research. However, the previous study can only estimate the fracture width near the offset well from single low-frequency DAS (LF-DAS) data. Due to the multiplicity problem, no study was attempted to characterize fracture lengths from DAS data. In this paper, we propose a new model to inverse the fracture length and width over treatment time from multiple sources of data [LF-DAS, high-frequency DAS (HF-DAS), and injection rate data]. First, HF-DAS waterfall plots of the treatment well and injection rate curves are aligned to determine the volume of fluid injected into each fracture. LF-DAS data along the offset well are related to fracture width by the Green function. The fracture length and width are determined by combining the Green function and fluid volume constraint. Second, the Picard and the least-squares methods are used to improve the robustness of the model computation. The inversion model is validated by a fracture propagation case generated by the displacement discontinuity method (DDM). In addition, the effects of the distance between the fiber and the wellbore, spatial sampling spacing, and fracture spacing on the computational stability of the inversion model are discussed. By combining DAS data and other monitoring data (e.g., inject rate) from treatment or offset well, the fracture length and width with treatment time can be accurately estimated. Results of fracture geometry interpretation can optimize fracture design and help improve production efficiency.

DFN: An Emerging Tool for Stochastic Modelling and Geomechanical Design

The discrete fracture networks (DFN) have become indispensable tools for geomechanical modelling of jointed rock masses. The technology creates a three-dimensional (3D) representation of fracture geometry used in the construction of surface and subsurface engineering projects in mining, civil engineering, and fracturing of the reservoir in the oil and gas industry. The approach depends on the accuracy of the data obtained during site investigation to create models that represent the fracture geometry of the structure. The better the acquired information available, the better the stochastic analysis that determines the engineering applications and designs that can be carried out. Therefore, it is important to use instruments that can capture fracture distribution characteristics such as fracture intensity, fracture orientation, spatial distribution, fracture length, fracture aperture, and size. This study provides a detailed review of the recent advances in the application of a DFN for modelling jointed rock masses in different engineering applications. The paper shows the principles of modelling in a DFN, including various data-capturing methodologies, and the general application of DFN in various fields. Several case studies where the DFN method was applied are presented in the paper. These include evaluation of slope in an open pit mine, modelling of discontinuity in tunneling, stability evaluation of coal seam longwall, the design of high-level radioactive waste, prediction of groundwater flow, fracturing of petroleum reservoirs, and geothermal cracking of shale gas in the coal bed. However, despite the versatility of the DFN technique, there are still some limitations and challenges to the integration of complexities encountered in rock masses within DFN models.

An investigation of data analysis method for hydraulic fracturing based on the water hammer effect

Hydraulic fracturing plays a crucial role in the development of unconventional resources, and assessing fracture geometry is a fundamental aspect of hydraulic fracturing analysis. Among the various technologies for evaluating fracture geometry, the water percussion signal-based method has gained popularity due to its cost-effectiveness, convenience, and real-time capabilities. In this study, we present a methodology for analyzing fracture data that utilizes the water percussion effect. By leveraging the impact of fractures on water percussion pressure attenuation, we propose an inverse calculation approach to determine fracture geometry. Firstly, we introduce the RCI (Reservoir-Completion-Interaction) circuit model, which effectively addresses the bottom hole fracture boundary and simulates the variation of water percussion pressure in the wellbore. Secondly, the simulation results are utilized in an iterative process to determine the RCI values, which are then utilized for the inversion calculation of fracture geometry. Finally, we apply this method to a field case and compare the simulation results with microseismic monitoring data. A larger resistance (R) value indicates a smaller fracture volume, while the (C) value can be used to monitor any poorly performing stages of the fracturing simulation process. The (I) value primarily affects the parameter calculation of the fracture size, especially the fracture width. The results of the field application show that the accuracy rate exceeding 80%, validating the reliability of the model and providing a valuable reference for field fracturing data analysis.

A study of patients with failure of proximal femoral nail fixation

A prospective study with an attempt to evaluate 36 cases of proximal femoral nailing taking into consideration the various modifiable and non-modifiable factors associated with failure of PFN like bone quality, fracture geometry, fracture reduction, implant selection, placement and to suggest possible explanations and recommendations to avoid such complication. The objectives of this study is to evaluate the possible radiographic findings leading to implant failure in PFN since the index surgery & to evaluate the type, outcome and complications of implant extraction & revision surgery in patients with a failed PFN. We followed up the patient for a minimum of six months at every six weekly intervals. At every follow up the patients were assessed clinically for pain, swelling, mobility at fracture site, joint stiffness, signs of infection, wound status and radio-logically (X-ray) for union status, alignment implant status and infection. Final assessment was done on based on the Modified Harris Hip score. We considered the outcome as favourable when fracture union was achieved with fair/good/excellent/poor score was considered as unfavourable outcome. All data was collated, compared and analysed using descriptive statistics.