Abrasive water jet (AWJ) perforation is an effective mean for stimulation in oil and gas wells. However, the mechanism of perforation formation and the regulation of its parameter remain poorly understood. This study investigates the variation in hole shape during AWJ perforation through a series of experimental designs and analyses. By analyzing the variation in perforation shape with injection time, the rock-breaking damage caused by AWJ and the flow characteristics in the perforation were quantitatively characterized. The results show that the process of perforation formation is governed by the coupling of three physical effects. The inflow increases the hole depth by vertically impacting the hole tip, while the backflow enlarges the hole diameter by eroding the hole wall. As the fluid mechanical energy dissipates along the path, the evolution of the perforation slows down during the later perforation period. Because the rock breaking ability of inflow is stronger than that of backflow, the ratio of hole depth to hole diameter of AWJ perforation increases with the increase of injection time. Specifically, when the injection time ranges from 5 s to 300 s, the ratio increases from 7 to 28. The rock breaking ability of the backflow decreases from the tip to the orifice, whereas the duration of the backflow’s action on the hole wall increases in the same direction. Under the combined influence of rock breaking ability and rock breaking time, the hole evolves from a conical shape to a spindle shape, and the degree of spindle increases. With the increase of injection time and hole depth, the fluid mechanical energy loss becomes more severe. The change rate of hole depth decreased to 11.3% and the change rate of hole diameter decreased to 4.3%. The evolution of the AWJ perforation became slow.

Reservoir fracability evaluation is one of the prerequisites to improve the effect of balanced fracturing of unconventional oil and gas fields. At present, reservoir fracability evaluation mainly depends on logging data theory to explain rock mechanics parameters, and the application effect on fracturing is uneven. In this paper, the characteristics of rock mechanical parameters are directly reflected by the bit rock breaking data and the reservoir fracability is clustered by drilling and logging data. We established a reservoir fracability clustering model based on a self-organizing map (SOM) unsupervised clustering algorithm. The elbow method is used to determine the optimal clustering number, and the parameter optimization method of fracture placement is formed. The optimal design of three-cluster perforation placement is carried out for typical vertical wells in the Tarim Basin with large thickness reservoirs. The results show that the drilling time, dc-exponent, weight on bit, torque, true formation resistivity, acoustic and neutron data are significantly correlated with reservoir fracability and can be used as characteristic parameters. The established model can effectively distinguish the difference of reservoir fracability along the wellbore axis, and select the fractures in the fracturable well section of the same type of reservoir, which is expected to improve the effect of balanced fracturing.

The abrasive water jet has remarkable effect in the application of accelerating drilling speed, deep penetration perforation and fracturing stimulation. In-depth understanding of the mechanism of abrasive water jet rock breaking is one of the keys to improve its application effect. Based on the arbitrary Lagrange-Euler finite element coupling algorithm, an independent packaged finite element mesh method for describing abrasives is presented in this paper. The grid of the water jet unit is set to change with the movement of the material to realize the fluid flow characteristics, and the speed is set to the material. The abrasive unit is set to the grid does not change with the movement of the material to achieve the solid particle characteristics, and the speed is set to the grid. Considering the dynamic impact damage of rock and the cooperation between water jet and abrasive, an abrasive water jet rock breaking model was established to characterize the multi-phase and multi-physical coupling process of water jet flow, rock damage and failure. The model focused on the impact damage of abrasive particles and water jet on rock in microseconds. Two sets of meshes were used to capture the collaborative rock breaking action of abrasives and water jets, and the temporal and spatial evolution characteristics of key parameters such as rock breaking volume, rock damage field, pressure field of water jet and energy contribution rate of water jet and abrasive to rock breaking were obtained. The results show that abrasive plays the main role and water jet plays the auxiliary role in the process of rock breaking. The mechanism of abrasive and water jet cooperative rock breaking is analyzed. The abrasive impingement of rock causes high degree of local damage of rock, which reduces the difficulty of water jet breaking rock. In addition, the impact of abrasive water jet on rock breakage creates a new interface between water jet and rock, which increases the impact pressure water jet and improves the rock breaking ability of water jet. Therefore, water in abrasive water jet has higher impact force and energy utilization rate than that of pure water jet. The predamage of abrasive impact on rock combined with the higher pressure of water jet stagnation is one of the important mechanisms that abrasive water jet has several times higher efficiency and energy utilization than pure water jet. The results can provide a theoretical model and design basis for optimizing the rock breaking parameters of abrasive water jet.

Effective completion design in hydraulic fracturing (HF) is crucial for optimizing production in unconventional reservoirs. Traditional geometric designs often fail to account for geological and engineering heterogeneity, leading to suboptimal stimulation. This study introduces a mechanism-guided data-driven model for optimized completion design that covers the entire process from sweet spot evaluation to stage and cluster optimization. For geological sweet spot evaluation, a mechanism-guided weighted K-medoids clustering model was developed by assigning weights to petrophysical parameters based on their correlation with production profiles. Engineering sweet spots were characterized using bottomhole mechanical specific energy (MSE_b) and minimum horizontal in-situ stress (S_hmin). The completion design optimization employed dynamic programming and a hybrid multi-objective optimization approach (NSGA-Ⅱ), integrating geological and engineering sweet spots with operational constraints. The study showed a positive correlation between high-quality geological sweet spots and production (average correlation coefficient of 0.34), and a negative correlation between fluid allocation and engineering sweet spots (correlation coefficient of −0.46). Field application in the Jimsar Sag, Xinjiang, demonstrated that the proposed model significantly outperforms traditional geometric designs. Test wells showed an average 186% increase in cumulative production per 100 m over three months compared to conventional wells. The key findings of this work provide a novel technical pathway for optimized completion design of unconventional reservoirs with significant engineering applicability.

The accurate evaluation of hydraulic fracturing performance is essential for the iterative optimization of unconventional reservoir development. In this aspect, fracturing pressure diagnostics has been recognized as a non-invasive technique that significantly reduces operational time and cost. However, pressure-based diagnostics lack a unified workflow for the evaluation of fracture complexity and area and cannot provide sufficient guidance for design optimization. Thus, this paper proposes an integrated diagnostic framework, constructed by pressure interpretation and data mining, from which the hydraulic fracture complexity and fracture area can be quantified. The normalized fracture complexity index is defined by propagation events and energy intensity extracted from wavelet-transformed pressure signals, and the fracture area is evaluated from pressure falloff analysis. Data mining is then used to optimize the fracturing parameters based on these two indices. The results show that the proposed framework effectively characterizes the stimulated fracture area and complexity and reveals their relationships with fracturing parameters and geological factors on the basis of multi-stage data from three horizontal coalbed methane wells. The stimulated fracture area is primarily determined by the fracturing fluid volume and pumping rate, while the fracture complexity is strongly regulated by the pumping rate and compressive strength of the rock. A negative correlation was detected between the fracture complexity and the main fracture area. To balance the main area and complexity of fractures, it is necessary to optimize the key fracturing parameters. This study provides a low-cost tool that can diagnose hydraulic fracturing performance and effectively optimize unconventional completion.

Hydraulic fracturing is a crucial technique for the extraction of geothermal energy from hot dry rock reservoirs. However, the development of such reservoirs faces significant challenges due to the high in-situ stress and strong elastic-plastic behavior of these rocks, which often result in simplified fracture geometries and subsequent low heat extraction efficiency. To address this issue, a novel reservoir treatment method based on thermal expansion and contraction principles is proposed. By applying alternating heating-cooling treatments to the reservoir, cyclic thermal stress is generated within the rock to enhance the complexity of post-fracturing fracture networks. To investigate the resultant hydraulic fracture propagation under alternate-temperature loading, a custom-developed thick-walled cylinder expansion fracturing device was employed to study the fracture propagation mechanisms in hot dry rock samples under cyclic thermal loading. The fracture network complexity was characterized by the fractal dimension method. Experimental results demonstrated that alternate thermal load cycling significantly enhances the fracture network complexity compared to conventional single-phase heat treatment. The maximum improvement in fractal dimension (3.86% increase) was observed at 500 ℃. Under alternating temperature loads, the upper surface fractures predominantly exhibited bilateral symmetric structures. At 600 ℃, a substantial increase in branched fractures and rock debris near boreholes occurred, indicating that alternating temperature loads significantly enhance the complexity of engineered fracture networks in hot dry rock. These findings suggest that incorporating thermal cycling into hydraulic fracturing processes can significantly improve the fracture network complexity, thereby enhancing the efficiency of heat extraction from hot dry rock reservoirs.

The digital twin, as the decision center of the automated drilling system, incorporates physical or data-driven models to predict the system response (rate of penetration, down-hole circulating pressure, drilling torques, etc.). Real-time drilling torque prediction aids in drilling parameter optimization, drill string stabilization, and comparing the discrepancy between observed signal and theoretical trend to detect down-hole anomalies. Due to their inability to handle huge amounts of time series data, current machine learning techniques are unsuitable for the online prediction of drilling torque. Therefore, a new way, the just-in-time learning (JITL) framework and local machine learning model, are proposed to solve the problem. The steps in this method are: (1) a specific metric is designed to measure the similarity between time series drilling data and scenarios to be predicted ahead of bit; (2) parts of drilling data are selected to train a local model for a specific prediction scenario separately; (3) the local machine learning model is used to predict drilling torque ahead of bit. Both the model data test results and the field data application results certify the advantages of the method over the traditional sliding window methods. Moreover, the proposed method has been proven to be effective in drilling parameter optimization and pipe sticking trend detection. Finally, we offer suggestions for the selection of local machine learning algorithms and real-time prediction with this approach based on the test results.

The difference in microstructure leads to the diversity of shale mechanical properties and bedding fractures distribution patterns. In this paper, the microstructure and mechanical properties of Longmaxi marine shale and Qingshankou continental shale were studied by X-ray diffractometer (XRD), field emission scanning electron microscope (FE-SEM) with mineral analysis system, and nanoindentation. Additionally, the typical bedding layers area was properly stratified using Focused Ion Beam (FIB), and the effects of microstructure and mechanical properties on the distribution patterns of bedding fractures were analyzed. The results show that the Longmaxi marine shale sample contains more clay mineral grains, while the Qingshankou continental shale sample contains more hard brittle mineral grains such as feldspar. For Longmaxi marine shale sample, hard brittle minerals with grain sizes larger than 20 μm is 18.24% and those with grain sizes smaller than 20 μm is 16.22%. For Qingshankou continental shale sample, hard brittle minerals with grain sizes larger than 20 μm is 40.7% and those with grain sizes smaller than 20 μm is 11.82%. In comparison to the Qingshankou continental shale sample, the Longmaxi marine shale sample has a lower modulus, hardness, and heterogeneity. Laminated shales are formed by alternating coarse-grained and fine-grained layers during deposition. The average single-layer thickness of Longmaxi marine shale sample is greater than Qingshankou continental shale sample. The two types of shale have similar bedding fractures distribution patterns and fractures tend to occur in the transition zone from coarse-grained to fine-grained deposition. The orientation of the fracture is usually parallel to the bedding plane and detour occurs in the presence of hard brittle grains. The fracture distribution density of the Longmaxi marine shale sample is lower than that of the Qingshankou continental shale sample due to the strong heterogeneity of the Qingshankou continental shale. The current research provides guidelines for the effective development of shale reservoirs in various sedimentary environments.

The perforating phase leads to complex and diverse hydraulic fracture propagation behaviors in laminated shale formations. In this paper, a 2D high-speed imaging scheme which can capture the interaction between perforating phase and natural shale bedding planes was proposed. The phase field method was used to simulate the same conditions as in the experiment for verification and hydraulic fracture propagation mechanism under the competition of perforating phase and bedding planes was discussed. The results indicate that the bedding planes appear to be no influence on fracture propagation while the perforating phase is perpendicular to the bedding planes, and the fracture propagates along the perforating phase without deflection. When the perforating phase algins with the bedding planes, the fracture initiation pressure reserves the lowest value, and no deflection occurs during fracture propagation. When the perforating phase is the angle 45°, 60° and 75° of bedding planes, the bedding planes begin to play a key role on the fracture deflection. The maximum deflection degree is reached at the perforating phase of 75°. Numerical simulation provides evidence that the existence of shale bedding planes is not exactly equivalent to anisotropy for fracture propagation and the difference of mechanical properties between different shale layers is the fundamental reason for fracture deflection. The findings help to understand the intrinsic characteristics of shale and provide a theoretical basis for the optimization design of field perforation parameters.