Production logging (PL) instruments play a pivotal role in the comprehensive management and monitoring of oil and gas reservoirs. These devices facilitate the resolution of complex flow diagnosis challenges throughout the life cycle of hydrocarbon field exploitation. However, the advent of highly deviated well drilling technology has exposed certain limitations inherent in conventional centralized logging sensing techniques. When fluid flow within horizontal wells becomes segregated or even laminar, these traditional methods struggle to accurately decipher the zonal productions of oil, gas, and water. To address this challenge, multi-array production logging tools were developed in the late 1990s. Historically, these tools were characterized by considerable lengths, reaching up to 30 feet for an entire suite incorporating flow speed and holdup sensors that were not always collocated. Despite the integration of multiple sensors, uncertainties in determining flow profiles persisted. In this paper, we propose a novel integrated multi-parameter evaluation method based on measurements from a recently developed ultracompact flow array sensing tool, aimed at enhancing the accuracy of reservoir evaluation. The validity of the multi-parameter method is substantiated through a comparison of the new tool with an industry benchmark array PL tool on the same well. By combining the monitoring results, an optimization strategy for oil and gas extraction is presented, which is expected to improve the oil and gas recovery rate, thereby providing guidance for subsequent extraction endeavors. Moreover, we demonstrate how this innovative integrated workflow significantly enhances energy savings and efficiency, further underlining its value in modern oil and gas field management.

During perforation in ultra-deep wells, the blast shock wave can induce dynamic responses of the perforating tubing, leading to potential downhole accidents such as vibration, deformation, and even fracture of the perforating tubing. To comprehend the dynamic response characteristics of the perforating tubing under blast impact load, we conducted a joint finite element simulation using SolidWorks, Hypermesh, and LS-DYNA. The simulation included deformation analysis, motion analysis, and strength analysis of the perforating tubing. By analyzing these factors, we obtained the change in velocity, acceleration, and equivalent stress of the perforating tubing over time under the blast load. The finite element analysis indicates the following: (a) the bottom of the perforating tubing is susceptible to significant tension compression cycle; (b) the velocity amplitude variation is smallest at the top of the perforating tubing, while the frequency and peak values of velocity changes are maximal at the bottom of the perforating tubing; and (c) the top and bottom of the tubing string are the vulnerable parts of the perforating tubing system.

Since light propagation in a multimode fiber (MMF) exhibits visually random and complex scattering patterns due to external interference, this study numerically models temperature and curvature through the finite element method in order to understand the complex interactions between the inputs and outputs of an optical fiber under conditions of temperature and curvature interference. The systematic analysis of the fiber’s refractive index and bending loss characteristics determined its critical bending radius to be 15 mm. The temperature speckle atlas is plotted to reflect varying bending radii. An optimal end-to-end residual neural network model capable of automatically extracting highly similar scattering features is proposed and validated for the purpose of identifying temperature and curvature scattering maps of MMFs. The viability of the proposed scheme is tested through numerical simulations and experiments, the results of which demonstrate the effectiveness and robustness of the optimized network model.

The perforating–fracturing–testing combined technology has emerged as a crucial well completion technique to enhance production efficiency. However, the shock loads generated during perforation in the packed section of an oil and gas well significantly affect the stability of the perforating tubing string system, potentially leading to deformation or even fracture. During the perforating operation, a large amount of blast products is generated, and as these products escape the perforating gun and interact with the perforating fluid, the fluid pressure pulsates. These pressure fluctuations are the primary cause of the dynamic response of the perforating tubing string. The greatest threat to tubing string integrity occurs when pulsating pressure reaches its peak amplitude, potentially leading to tubing failure. To address this, this study employs underwater explosion theory to analyze the pressure variations during the generation and propagation of shock waves in perforation operations. Additionally, quantitative numerical simulation analysis reveals key relationships governing peak perforating fluid pressure: peak pressure remains remarkably stable at 370–371 MPa despite variations in perforating fluid viscosity (0–110 cP) or tubing Young’s modulus (100–260 GPa). However, it responds significantly to other parameters: fluid density (1–3 g/cm³) causes a linear increase from 335 MPa to 598 MPa; total charge mass drives a proportional rise from 162 MPa to 388 MPa; detonation interval (0–50 μs) elevates pressure from 268 MPa to 378 MPa; and formation pressure (0–100 MPa) increases it from 315 MPa to 372 MPa. Crucially, peak pressure decreases from 376 MPa to 243 MPa as the explosion space expands (0–5 m³). Furthermore, a nonlinear regression model is developed to predict peak perforating shock loads. The results indicate that residual perforation energy critically impacts tubing string safety. Validated against two field cases, the model achieves nearly 10% error compared to predictions from Pulsfrac (industry-standard perforating shock software), meeting field requirements while providing actionable insights for wellbore integrity and perforating tubing string stability.