Wellbore stability monitoring system based on fusion of optical fiber sensing signal and logging technology

Abstract

The application discloses a well wall stability monitoring system based on fusion of optical fiber sensing signals and logging technology, and relates to the technical field of well wall stability monitoring.The system comprises a logging data acquisition module, an optical fiber sensing monitoring module, a space-time coupling calibration module, a multi-field signal interpretation module, a well wall stability analysis module and an early warning output module.Through the cooperative setting of the logging data acquisition module and the optical fiber sensing monitoring module, the system realizes the synchronous acquisition of the wellbore stratum static geological parameters and the well wall dynamic multi-physical field sensing signals, completes the full space-time coupling calibration of the two types of data by establishing a unified depth and time benchmark, solves the core problems of the disconnection between the traditional optical fiber monitoring signals and the stratum properties and the insufficient interpretation accuracy, realizes the accurate differentiation between the stratum inherent characteristics and the well wall damage signals by constructing the optical fiber signal interpretation model constrained by the logging stratum parameters, and improves the accuracy and reliability of the well wall stability monitoring.

Description

Technical Field

[0001] This invention relates to the field of wellbore stability monitoring technology, specifically a wellbore stability monitoring system based on the fusion of fiber optic sensing signals and logging technology. Background Technology

[0002] The wellbore is a core structure in wellbore engineering, including oil and gas wells, geological exploration wells, and hydrological wells. It isolates the internal space of the wellbore from the surrounding formation rock, maintains the integrity of the wellbore structure, and ensures the safety of drilling operations and subsequent production operations. It consists of the open hole wellbore during the drilling process and the composite wellbore formed by the casing, cement sheath, and formation after completion. It is the core object of safety management throughout the entire life cycle of the wellbore. During wellbore drilling and long-term production service, wellbore instability can lead to a series of engineering accidents such as wellbore narrowing, wellbore collapse, stuck pipe, casing deformation and damage, and cementing failure. These accidents can range from extending the drilling cycle and significantly increasing operating costs to causing major safety and environmental accidents such as wellbore scrapping and formation fluid leakage. Therefore, monitoring the stability of the wellbore is a core technical support for ensuring the safety of wellbore drilling operations and the stability of long-term production service.

[0003] Well logging technology is a core engineering technology that involves running specialized well logging instruments into the wellbore to continuously collect physical, chemical, and mechanical parameters of the formation and wellbore along the well depth. Fiber optic sensing technology is a monitoring technology that uses the photoelastic, thermo-optic, and acousto-optic effects of optical fibers to achieve distributed and continuous acquisition of physical quantities along the fiber optic deployment path. The integration of the geological prior constraints provided by well logging technology and the dynamic continuous monitoring capabilities provided by fiber optic sensing technology is the core development direction for solving the problems of the disconnect between static geological constraints and dynamic response, and the inability to balance monitoring accuracy and continuity in wellbore stability monitoring.

[0004] However, existing wellbore stability monitoring technologies still have certain shortcomings. Among existing wellbore stability monitoring technologies, logging technology can only obtain static data of the wellbore and formation, and cannot achieve continuous real-time monitoring of wellbore damage evolution. Fiber optic sensing monitoring lacks prior constraints of logging formation parameters, making it difficult to distinguish between formation background signals and wellbore damage anomaly signals, resulting in low interpretation accuracy and high false alarm rate. At the same time, the two types of technologies are mostly used independently, without establishing a unified spatiotemporal benchmark to achieve deep coupling. This fails to solve the core pain point of the disconnect between static geological analysis and dynamic continuous monitoring, and is difficult to meet the needs of high-precision control of wellbore stability throughout its entire life cycle under complex operating conditions. Therefore, developing a wellbore stability monitoring system based on the integration of fiber optic sensing signals and logging technology is of great significance. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a wellbore stability monitoring system based on the integration of fiber optic sensing signals and logging technology. It can establish a unified depth and time reference through the coordinated setting of the logging data acquisition module and the fiber optic sensing monitoring module, and construct a fiber optic signal interpretation model constrained by logging formation parameters. This solves the problems in existing technologies such as the disconnect between logging static data and fiber optic dynamic monitoring data, the lack of geological prior constraints in fiber optic sensing signal interpretation, low accuracy of wellbore stability monitoring interpretation, high false alarm rate, and inability to achieve continuous management and control throughout the entire life cycle.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a wellbore stability monitoring system based on the fusion of fiber optic sensing signals and logging technology, the system comprising: a logging data acquisition module, a fiber optic sensing monitoring module, a spatiotemporal coupling calibration module, a multi-field signal interpretation module, a wellbore stability analysis module, and an early warning output module;

[0007] The well logging data acquisition module obtains static geological and engineering parameters of the formation through well logging operations in the target well section, and constructs a basic geological model for wellbore stability;

[0008] The fiber optic sensing and monitoring module deploys sensing fibers along the entire target wellbore to collect dynamic time-series sensing signals of multiple physical fields throughout the entire life cycle of the wellbore.

[0009] The signal input terminal of the spatiotemporal coupling calibration module is connected to the signal output terminals of the well logging data acquisition module and the fiber optic sensing monitoring module, respectively, to establish a unified depth coordinate reference and time dimension reference for the static data acquired by well logging and the dynamic sensing data acquired by fiber optics, and to complete the point-by-point matching and time-series synchronous calibration of the two types of data.

[0010] The signal input terminal of the multi-field signal interpretation module is communicatively connected to the signal output terminal of the spatiotemporal coupling calibration module. Based on the basic geological model of wellbore stability, a fiber optic multiphysics signal interpretation model constrained by well logging formation parameters is established to interpret the calibrated sensing signals and extract the wellbore structural damage characteristic signals.

[0011] The signal input terminal of the wellbore stability analysis module is communicatively connected to the signal output terminal of the multi-field signal interpretation module. Based on the wellbore structural damage characteristic signal obtained by interpretation, combined with the basic geological model of wellbore stability, the wellbore stability state of the target well section is analyzed.

[0012] The signal input terminal of the early warning output module is communicatively connected to the signal output terminal of the wellbore stability analysis module, and outputs corresponding early warning information based on the wellbore stability state and the preset instability critical criterion.

[0013] Furthermore, the spatiotemporal coupling calibration module performs the following operations during the data calibration process:

[0014] Using the wellbore core elevation as the depth reference origin, a continuous depth coordinate system covering the entire depth range of the target well section is established. The depth markers corresponding to the static data output by the logging data acquisition module and the depth markers corresponding to the dynamic sensing data output by the fiber optic sensing monitoring module are read respectively, and the depth markers of the two types of data are mapped to the same continuous depth coordinate system.

[0015] Using a unified clock source at the ground control terminal as the time reference, a synchronization timestamp is established for the acquisition nodes of well logging data and the time-series acquisition sequence of fiber optic sensor data to complete the time-series synchronization of the two types of data.

[0016] Based on the mapped depth coordinates and the synchronized timestamps, point-by-point matching and calibration of well logging static data and fiber optic dynamic sensing data are completed.

[0017] Furthermore, the multi-field signal interpretation module performs the following operations during the signal interpretation process:

[0018] Read the calibration-completed static logging data and fiber optic dynamic sensing data output by the spatiotemporal coupling calibration module, retrieve the wellbore stability basic geological model constructed by the logging data acquisition module, and establish a fiber optic multiphysics signal interpretation model with the logging formation parameters in the model as constraints.

[0019] Based on the interpretation model, the background reference range of the fiber optic sensing signal at each depth location corresponding to the target well section is determined by the well logging formation parameters at each depth location.

[0020] The real-time signal from the fiber optic sensor at the corresponding depth position is compared with the background reference range. Non-damage interference signals are removed, and the wellbore structural damage feature signals are extracted. The depth position and time node corresponding to the damage feature signals are marked.

[0021] Furthermore, the multi-field signal interpretation module establishes a fiber optic multiphysics signal interpretation model constrained by well logging formation parameters. This model includes the mapping relationship between formation parameters and fiber optic sensing signals. The mapping relationship covers the correspondence between formation lithology and fiber optic strain signal reference values, formation pore pressure and fiber optic temperature signal reference values, and in-situ stress distribution and fiber optic vibration signal reference values. Based on the well logging formation parameters at each depth in the target well section, the interpretation model generates a sequence of fiber optic sensing signal reference values ​​at the corresponding depths. The fiber optic strain signal reference value is calculated using the following formula: ,in, The reference value for the fiber optic strain signal at depth z in the target well section is given. Here is the P-wave impedance value at depth z. Let z be the minimum horizontal principal stress value at depth z. denoted as ρ, where ρ is the formation pore pressure at depth z, α is the lithology coupling coefficient, β is the geostress coupling coefficient, and γ is the pore pressure coupling coefficient. All three coefficients are determined by multiple linear regression fitting of the core mechanics experimental data of the target well section obtained by the well logging data acquisition module and the corresponding depth fiber optic sensor calibration data.

[0022] Furthermore, the wellbore stability analysis module performs the following operations during the steady-state analysis process:

[0023] Read the wellbore structural damage characteristic signal output by the multi-field signal interpretation module, retrieve the wellbore stability basic geological model constructed by the well logging data acquisition module, and match the formation parameters at the depth location corresponding to the damage characteristic signal.

[0024] Based on damage characteristic signals and corresponding formation parameters, the stress evolution process and damage accumulation degree of the wellbore surrounding rock at the target depth are inverted. The damage accumulation degree of the wellbore surrounding rock is quantified by damage variables, and the calculation formula for the damage variables is as follows: ,in, Let z be the damage variable of the surrounding rock at the target well depth z at time t. The measured fiber strain at depth z at time t is given. Let z be the dynamic elastic modulus of the surrounding rock at depth z. Let z be the initial elastic modulus of the surrounding rock at depth z. and All values ​​are determined by calculation based on the longitudinal and transverse wave velocity data obtained from the acoustic logging data acquisition module.

[0025] Based on the inversion results, the wellbore stability safety factor at each depth location in the target well section is calculated. Combined with the preset stability state classification rules, the wellbore stability state at each depth location in the target well section is determined.

[0026] Furthermore, the wellbore stability analysis module is pre-set with wellbore stability grading rules. These rules include multiple consecutive safety factor intervals, each corresponding to a wellbore stability level. The wellbore stability analysis module calculates the wellbore stability safety factor at each depth in the target well section. The formula for calculating the wellbore stability safety factor is: ,in, Let z be the wellbore stability safety factor at the target well depth z position at time t. Let z be the uniaxial compressive strength of the surrounding rock at depth z. Let Z be the tangential stress of the surrounding rock at depth z at time t. The data is determined by calculation using sonic logging data and density logging data acquired by the well logging data acquisition module. The wellbore stability analysis module determines the wellbore stability distribution sequence by combining the geostress logging data obtained by the well logging data acquisition module with the damage variable inversion. The wellbore stability analysis module compares the calculated wellbore stability safety factor at each depth of the target well section with the safety factor interval within the classification rules, matches the wellbore stability status level at the corresponding depth position, and generates the wellbore stability status distribution sequence for the entire depth range of the target well section.

[0027] Furthermore, the early warning output module is pre-set with a critical criterion for wellbore instability. The critical criterion corresponds one-to-one with the wellbore stability level. Each wellbore stability level corresponds to a set of early warning output rules. The early warning output module reads the distribution sequence of wellbore stability of the target well section output by the wellbore stability analysis module, compares the wellbore stability level at each depth position in the sequence with the pre-set critical criterion for instability, triggers the early warning output rule of the corresponding level, and outputs the early warning information of the corresponding depth position.

[0028] Furthermore, the well logging data acquisition module is equipped with an acoustic logging unit, a density logging unit, a geostress logging unit, a caliper logging unit, and a porosity logging unit. The acoustic logging unit collects P-wave velocity and S-wave velocity data of the formation in the target well section; the density logging unit collects the volume density data of the formation in the target well section; the geostress logging unit collects the maximum horizontal principal stress, minimum horizontal principal stress, and vertical principal stress data of the formation in the target well section; the caliper logging unit collects the wellbore diameter and wellbore trajectory data of the target well section; and the porosity logging unit collects the porosity and pore pressure data of the formation in the target well section. Based on the collected data, the well logging data acquisition module constructs a basic geological model of the wellbore stability of the target well section.

[0029] Furthermore, the fiber optic sensing monitoring module includes a distributed fiber optic sensing unit, a fiber optic signal demodulation unit, and a wellhead signal conversion unit. The distributed fiber optic sensing unit uses a single-mode strain-temperature integrated sensing fiber. The distributed fiber optic sensing unit is continuously deployed along the outer wall of the casing of the target wellbore. The distributed fiber optic sensing unit is tightly attached to the outer wall of the casing by a fixing clip. The fiber optic signal demodulation unit is deployed at the wellhead ground control end. The fiber optic signal demodulation unit is fused to the wellhead end of the distributed fiber optic sensing unit through the wellhead signal conversion unit. The fiber optic signal demodulation unit collects the strain, temperature, and vibration timing sensing signals transmitted by the distributed fiber optic sensing unit according to a preset sampling frequency.

[0030] Furthermore, the spatiotemporal coupling calibration module, multi-field signal interpretation module, wellbore stability analysis module, and early warning output module are all integrated into the industrial-grade processing host at the ground control terminal. Each module establishes a bidirectional communication connection through an industrial Ethernet bus. The logging data acquisition module and the fiber optic sensing monitoring module establish a bidirectional communication connection with the industrial-grade processing host at the ground control terminal through a wireless communication link. The logging data acquisition module and the fiber optic sensing monitoring module synchronously transmit the acquired corresponding data to the industrial-grade processing host according to a preset transmission cycle.

[0031] Compared with existing technologies, this wellbore stability monitoring system based on the fusion of fiber optic sensing signals and logging technology has the following advantages:

[0032] This invention achieves the synchronous acquisition of static geological parameters of the wellbore formation and dynamic multi-physics field sensing signals of the wellbore wall through the coordinated setup of a well logging data acquisition module and a fiber optic sensing monitoring module. By establishing a unified depth and time reference, it completes the full spatiotemporal coupling calibration of the two types of data, solving the core problems of the disconnect between traditional fiber optic monitoring signals and formation properties and insufficient interpretation accuracy. By constructing a fiber optic signal interpretation model constrained by well logging formation parameters, it achieves accurate differentiation between inherent formation characteristics and wellbore damage signals, improving the accuracy and reliability of wellbore stability monitoring. It realizes the deep integration of static geological constraints and dynamic continuous monitoring, providing stable and reliable technical support for the safety management and control of the wellbore throughout its entire life cycle.

[0033] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0035] Figure 1 This is a schematic diagram of a wellbore stability monitoring system based on the fusion of fiber optic sensing signals and logging technology.

[0036] Figure 2 This is a flowchart of the wellbore stability monitoring system based on the fusion of fiber optic sensing signals and logging technology.

[0037] Figure 3 This is a flowchart of the multi-field signal interpretation module during signal interpretation. Detailed Implementation

[0038] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0039] This invention provides a wellbore stability monitoring system based on the fusion of fiber optic sensing signals and logging technology. It is a complete technical solution for wellbore stability monitoring throughout the entire lifecycle of various wellbore projects, including oil and gas wells, geological exploration wells, and hydrological wells. The system is based on a logging data acquisition module that obtains static geological and engineering parameters of the formation and builds a basic geological model for wellbore stability. At its core, a fiber optic sensing module deploys sensing fibers along the entire wellbore to collect dynamic time-series sensing signals from multiple physical fields, such as strain, temperature, and vibration. A spatiotemporal coupling calibration module establishes a unified depth coordinate reference and time dimension reference to complete point-by-point matching and time-series synchronous calibration of static logging data and dynamic sensing data. A multi-field signal interpretation module constructs a fiber optic multi-physics field signal interpretation model constrained by logging formation parameters to remove non-damaging interference signals and accurately extract wellbore structural damage characteristic signals. A wellbore stability analysis module combines damage characteristic signals with the basic geological model to invert the surrounding rock stress evolution process and damage accumulation degree, and calculates the wellbore stability safety factor. Finally, an early warning output module outputs corresponding levels of early warning information based on preset instability critical criteria. The six core modules achieve two-way data interaction and collaborative operation through communication links, which completely solves the core pain points of traditional monitoring technology, such as the disconnect between static geological analysis and dynamic continuous monitoring, the lack of geological prior constraints in the interpretation of fiber optic sensor signals, and the insufficient monitoring accuracy and high false alarm rate. It provides high-precision safety management and control support for the entire process of well drilling construction, well completion operations and long-term production service.

[0040] The technical solution of the present invention will be described in detail below with reference to specific embodiments. In this embodiment, an onshore deep clastic rock oil and gas well is selected as the application scenario. This type of well has the characteristics of large well depth, complex geostress distribution, variable formation lithology, and high risk of wellbore instability. The whole life cycle monitoring of wellbore stability is carried out based on the patented system of the present invention. The complete implementation process is as follows.

[0041] Hardware deployment and multi-source data acquisition for the monitoring system: Before the monitoring operation starts, the on-site deployment of the system hardware and the debugging of the data acquisition unit are completed to ensure the stable operation of the well logging data acquisition module and the fiber optic sensing monitoring module, so as to provide accurate raw data for subsequent data processing.

[0042] The well logging data acquisition module is equipped with acoustic logging, density logging, geostress logging, caliper logging, and porosity logging units. These units are integrated into a logging instrument string and then run into the target well section for continuous logging data acquisition according to wellbore logging operation specifications. The acoustic logging unit acquires formation P-wave and S-wave velocity data point-by-point along the well depth; the density logging unit simultaneously acquires formation bulk density data; the geostress logging unit obtains data on the maximum, minimum, and vertical principal stresses of the formation; the caliper logging unit records wellbore diameter and wellbore trajectory parameters; and the porosity logging unit acquires formation porosity and pore pressure data. All logging data is transmitted to the surface control terminal in real time. Based on these multi-dimensional parameters, the well logging data acquisition module integrates information on formation lithology, mechanical properties, stress distribution, and pore characteristics to construct a basic geological model of wellbore stability for the target well section. This model serves as the core geological constraint for subsequent signal interpretation and stability analysis.

[0043] The fiber optic sensing monitoring module comprises a distributed fiber optic sensing unit, a fiber optic signal demodulation unit, and a wellhead signal conversion unit. A single-mode strain-temperature integrated sensing fiber optic cable is selected as the distributed fiber optic sensing unit, which is continuously deployed axially along the outer wall of the target well casing. The sensing fiber optic cable is tightly fitted to the outer wall of the casing using fixing clips, ensuring that the fiber optic cable can accurately sense changes in strain, temperature, and vibration of the surrounding rock. The fiber optic signal demodulation unit is deployed at the wellhead ground control end and is fused to the wellhead end of the distributed fiber optic sensing unit via the wellhead signal conversion unit. After commissioning, data acquisition begins at a preset sampling frequency, continuously acquiring strain, temperature, and vibration time-series sensing signals throughout the entire lifecycle of the well casing, achieving continuous monitoring of the well casing's dynamic response across the entire domain.

[0044] like Figure 1 As shown, this system consists of six core components: a well logging data acquisition module, a fiber optic sensing and monitoring module, a spatiotemporal coupling calibration module, a multi-field signal interpretation module, a wellbore stability analysis module, and an early warning output module. The modules communicate bidirectionally with each other via an industrial Ethernet bus and a wireless communication link to achieve real-time data transmission and collaborative processing.

[0045] Spatiotemporal coupling calibration enables synchronous matching of static and dynamic data. After the original data acquisition is completed, the spatiotemporal coupling calibration module is started to carry out data calibration work, establish a unified spatiotemporal reference for well logging static data and fiber optic dynamic sensing data, and solve the problem of depth and time mismatch between the two types of data.

[0046] Using the wellbore core elevation as the depth reference origin, a continuous depth coordinate system covering the entire depth range of the target well section was established. Depth markers corresponding to static geological parameters output by the well logging data acquisition module and depth markers corresponding to dynamic sensing data output by the fiber optic sensing monitoring module were read separately. The depth markers of both types of data were completely mapped to the same continuous depth coordinate system, eliminating depth reference deviations between different acquisition units. Using a unified clock source at the ground control terminal as the time reference, synchronization timestamps were added to the timing sequences of well logging data acquisition nodes and fiber optic sensing data acquisition, ensuring complete temporal alignment between static data acquired at different times and real-time dynamic data. Based on the unified depth coordinates and synchronization timestamps, point-by-point matching and calibration of well logging static data and fiber optic dynamic sensing data were completed, providing a spatiotemporally consistent data source for subsequent multi-field signal interpretation.

[0047] like Figure 2 As shown, the overall workflow of this system starts with the acquisition of static geological parameters from well logging and the acquisition of dynamic optical fiber sensing signals. After spatiotemporal coupling calibration, multi-field signal interpretation, damage feature extraction, wellbore stability analysis, and safety factor calculation, it determines whether the instability critical criterion has been exceeded and finally outputs early warning information, forming a closed-loop monitoring process.

[0048] Multi-field signal interpretation model construction and wellbore damage feature extraction: After the spatiotemporal coupling calibration is completed, the multi-field signal interpretation module reads the complete data after calibration, retrieves the basic geological model of wellbore stability, and constructs a fiber optic multiphysics signal interpretation model constrained by well logging formation parameters to achieve accurate differentiation between background signals and damage signals.

[0049] First, based on the formation parameters in the basic geological model, corresponding mapping relationships are established between formation lithology and fiber optic strain signals, formation pore pressure and fiber optic temperature signals, and geostress distribution and fiber optic vibration signals, forming an interpretation model framework adapted to the target well section. Then, based on the interpretation model, well logging formation parameters at various depths in the target well section are matched, and the background reference interval for the fiber optic sensing signals at the corresponding depths is calculated. The real-time acquired fiber optic sensing signals are compared one by one with the background reference interval, eliminating non-damaging signals such as inherent formation characteristics and environmental interference, accurately extracting wellbore structural damage characteristic signals, and marking the depth location and time node corresponding to the damage signals.

[0050] like Figure 3 As shown, the multi-field signal interpretation follows a standardized process, sequentially completing data reading after calibration, retrieval of the basic geological model, construction of the well logging formation parameter constraint interpretation model, calculation of the fiber optic sensor signal reference value sequence, comparison of real-time signals with reference values, removal of non-destructive interference signals, and extraction of wellbore structural damage characteristic signals. The entire process relies on geological parameter constraints to improve interpretation accuracy.

[0051] In the specific implementation of this embodiment, the reference value of the fiber optic strain signal is determined by the formula... The calculation uses an empirical regression model, which does not require dimensional consistency and is only used for fitting signal baseline values. In the formula... The reference value for the fiber optic strain signal at depth z in the target well section is given. Here is the P-wave impedance value at depth z. Let z be the minimum horizontal principal stress value at depth z. The value represents the formation pore pressure at depth z. The lithological coupling coefficient α, the geostress coupling coefficient β, and the pore pressure coupling coefficient γ are all determined by multiple linear regression fitting using core mechanics experimental data from the core section of the target well and fiber optic sensor calibration data at the corresponding depth. The fitting process uses the formation mechanics parameters obtained from the core mechanics experiment as independent variables and the strain signal from the fiber optic sensor calibration at the corresponding depth as the dependent variable. The least squares method is used to quantify the coefficients, ensuring a high degree of matching between the coupling coefficients and the formation mechanics characteristics and fiber optic sensor response characteristics of the target well section, thus guaranteeing the accuracy of the benchmark value calculation.

[0052] Quantitative analysis and level determination of wellbore stability status; After extracting the structural damage characteristic signals of the wellbore, the wellbore stability analysis module starts the analysis process, and combines the basic geological model and damage characteristic signals to complete the inversion of the degree of damage accumulation of the surrounding rock of the wellbore and the calculation of the stability safety factor.

[0053] First, the formation parameters at the depth corresponding to the damage feature signal are matched. Based on the damage feature signal, the stress evolution process of the surrounding rock at that depth is inverted. The degree of damage accumulation in the surrounding rock is quantified by the damage variable, which intuitively reflects the damage state of the well wall structure.

[0054] In the specific implementation of this embodiment, the wellbore surrounding rock damage variable is determined by the formula... Calculation, where The value range is [0,1]. If the calculation result is less than 0, it is taken as 0; if it is greater than 1, it is taken as 1. In the formula... Let z be the damage variable of the surrounding rock at the target well depth z at time t. The measured fiber strain at depth z at time t is given. Let z be the dynamic elastic modulus of the surrounding rock at depth z. The initial elastic modulus of the surrounding rock at depth z is given. Both the dynamic elastic modulus and the initial elastic modulus of the surrounding rock are determined by calculation using the sonic logging P-wave velocity and S-wave velocity data acquired by the well logging data acquisition module. The calculation process relies on classical rock mechanics theory, converting the sonic velocity data into elastic parameter characterization values ​​to achieve unbiased quantification of the elastic properties of the surrounding rock.

[0055] After calculating the damage variables, the wellbore stability safety factor is calculated. In the specific implementation of this embodiment, the wellbore stability safety factor is calculated using the formula... Calculation. In the formula... Let z be the wellbore stability safety factor at the target well depth z position at time t. Let z be the uniaxial compressive strength of the surrounding rock at depth z. Let be the tangential stress of the surrounding rock at depth z at time t. The uniaxial compressive strength of the surrounding rock is determined by jointly calculating sonic logging data and density logging data acquired by the well logging data acquisition module. The tangential stress of the surrounding rock is determined by combining in-situ stress logging data acquired by the well logging data acquisition module with damage variable inversion. The inversion process fully considers the impact of damage accumulation on the stress distribution of the surrounding rock, significantly improving the accuracy of stress calculation and safety factor assessment.

[0056] The wellbore stability analysis module has a pre-defined wellbore stability grading rule, which includes continuous safety factor intervals, each interval corresponding to an independent stability level. The calculated wellbore stability safety factor at each depth is compared with the grading rule intervals one by one to match the stability level at the corresponding depth, ultimately generating a wellbore stability distribution sequence across the entire depth range of the target well section, clearly presenting the stability distribution of the entire wellbore.

[0057] Early warning information output and on-site safety management: The early warning output module reads the distribution sequence of wellbore stability and makes early warning judgments based on the preset wellbore instability critical criteria. The critical criteria correspond one-to-one with the wellbore stability level, and each level is matched with a unique early warning output rule.

[0058] The stability level at each depth is compared with the instability threshold criterion, triggering the corresponding early warning output rules. This outputs complete early warning information, including damage depth, occurrence time, stability level, and risk severity. The warning information is simultaneously pushed to the field operation terminal in the form of a visual interface, audio-visual prompts, and data messages. Based on the warning information, field personnel promptly take control measures such as adjusting drilling parameters, optimizing wellbore pressure, and reinforcing the wellbore to prevent instability accidents such as wellbore narrowing, collapse, and casing deformation from the source, ensuring continuous and safe wellbore operations.

[0059] In summary, this embodiment, based on the practical application of the patented system in onshore deep oil and gas wells, achieves complete spatiotemporal coupling of static geological parameters of the wellbore formation and dynamic multi-physics field sensing signals of the wellbore through the deep integration of logging technology and fiber optic sensing technology. The establishment of a unified spatiotemporal benchmark solves the problem of disconnected traditional monitoring data; the interpretation model of logging formation parameter constraints enables accurate differentiation between background and damage signals; the quantitative calculation of damage variables and safety factors makes the determination of wellbore stability more scientific and accurate; and the graded early warning mechanism provides an intuitive and reliable basis for on-site safety management. This embodiment effectively improves the accuracy and reliability of wellbore stability monitoring, reduces the false alarm rate, and achieves continuous, real-time, high-precision monitoring of the wellbore throughout its entire lifecycle from drilling to production service. It significantly reduces operational delays, increased costs, and safety risks caused by wellbore instability, providing core technical support for the safe and efficient operation of various wellbore projects, and fully verifying the practicality and advancement of the patented technical solution.

[0060] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A wellbore stability monitoring system based on the fusion of fiber optic sensor signals and logging technology, characterized in that, The system includes: a well logging data acquisition module, a fiber optic sensing monitoring module, a spatiotemporal coupling calibration module, a multi-field signal interpretation module, a wellbore stability analysis module, and an early warning output module; The well logging data acquisition module obtains static geological and engineering parameters of the formation through well logging operations in the target well section, and constructs a basic geological model for wellbore stability; The fiber optic sensing and monitoring module deploys sensing fibers along the entire target wellbore to collect dynamic time-series sensing signals of multiple physical fields throughout the entire life cycle of the wellbore. The signal input terminal of the spatiotemporal coupling calibration module is connected to the signal output terminals of the well logging data acquisition module and the fiber optic sensing monitoring module, respectively, to establish a unified depth coordinate reference and time dimension reference for the static data acquired by well logging and the dynamic sensing data acquired by fiber optics, and to complete the point-by-point matching and time-series synchronous calibration of the two types of data. The signal input terminal of the multi-field signal interpretation module is communicatively connected to the signal output terminal of the spatiotemporal coupling calibration module. Based on the basic geological model of wellbore stability, a fiber optic multiphysics signal interpretation model constrained by well logging formation parameters is established to interpret the calibrated sensing signals and extract the wellbore structural damage characteristic signals. The signal input terminal of the wellbore stability analysis module is communicatively connected to the signal output terminal of the multi-field signal interpretation module. Based on the wellbore structural damage characteristic signal obtained by interpretation, combined with the basic geological model of wellbore stability, the wellbore stability state of the target well section is analyzed. The signal input terminal of the early warning output module is communicatively connected to the signal output terminal of the wellbore stability analysis module, and outputs corresponding early warning information based on the wellbore stability state and the preset instability critical criterion.

2. The wellbore stability monitoring system based on the fusion of fiber optic sensor signals and logging technology according to claim 1, characterized in that, The spatiotemporal coupling calibration module performs the following operations during the data calibration process: Using the wellbore core elevation as the depth reference origin, a continuous depth coordinate system covering the entire depth range of the target well section is established. The depth markers corresponding to the static data output by the logging data acquisition module and the depth markers corresponding to the dynamic sensing data output by the fiber optic sensing monitoring module are read respectively, and the depth markers of the two types of data are mapped to the same continuous depth coordinate system. Using a unified clock source at the ground control terminal as the time reference, a synchronization timestamp is established for the acquisition nodes of well logging data and the time-series acquisition sequence of fiber optic sensor data to complete the time-series synchronization of the two types of data. Based on the mapped depth coordinates and the synchronized timestamps, point-by-point matching and calibration of well logging static data and fiber optic dynamic sensing data are completed.

3. The wellbore stability monitoring system based on the fusion of fiber optic sensor signals and logging technology according to claim 1, characterized in that, The multi-field signal decoding module performs the following operations during signal decoding: Read the calibration-completed static logging data and fiber optic dynamic sensing data output by the spatiotemporal coupling calibration module, retrieve the wellbore stability basic geological model constructed by the logging data acquisition module, and establish a fiber optic multiphysics signal interpretation model with the logging formation parameters in the model as constraints. Based on the interpretation model, the background reference range of the fiber optic sensing signal at each depth location corresponding to the target well section is determined by the well logging formation parameters at each depth location. The real-time signal from the fiber optic sensor at the corresponding depth position is compared with the background reference range. Non-damage interference signals are removed, and the wellbore structural damage feature signals are extracted. The depth position and time node corresponding to the damage feature signals are marked.

4. The wellbore stability monitoring system based on the fusion of fiber optic sensor signals and logging technology according to claim 3, characterized in that, The multi-field signal interpretation module establishes a fiber optic multiphysics signal interpretation model constrained by well logging formation parameters. This model includes the mapping relationship between formation parameters and fiber optic sensing signals. This mapping relationship covers the correspondence between formation lithology and fiber optic strain signal reference values, formation pore pressure and fiber optic temperature signal reference values, and in-situ stress distribution and fiber optic vibration signal reference values. Based on the well logging formation parameters at various depths in the target well section, the interpretation model generates a sequence of fiber optic sensing signal reference values ​​for the corresponding depths. The fiber optic strain signal reference value is calculated using the following formula: ,in, The reference value for the fiber optic strain signal at depth z in the target well section is given. Here is the P-wave impedance value at depth z. Let z be the minimum horizontal principal stress value at depth z. Let denot be the formation pore pressure at depth z, α be the lithological coupling coefficient, β be the geostress coupling coefficient, and γ be the pore pressure coupling coefficient.

5. The wellbore stability monitoring system based on the fusion of fiber optic sensor signals and logging technology according to claim 1, characterized in that, The wellbore stability analysis module performs the following operations during the steady-state analysis process: Read the wellbore structural damage characteristic signal output by the multi-field signal interpretation module, retrieve the wellbore stability basic geological model constructed by the well logging data acquisition module, and match the formation parameters at the depth location corresponding to the damage characteristic signal. Based on damage characteristic signals and corresponding formation parameters, the stress evolution process and damage accumulation degree of the wellbore surrounding rock at the target depth are inverted. The damage accumulation degree of the wellbore surrounding rock is quantified by damage variables, and the calculation formula for the damage variables is as follows: ,in, Let z be the damage variable of the surrounding rock at the target well depth z at time t. The measured fiber strain at depth z at time t is given. Let z be the dynamic elastic modulus of the surrounding rock at depth z. Let z be the initial elastic modulus of the surrounding rock at depth z. Based on the inversion results, the wellbore stability safety factor at each depth location in the target well section is calculated. Combined with the preset stability state classification rules, the wellbore stability state at each depth location in the target well section is determined.

6. The wellbore stability monitoring system based on the fusion of fiber optic sensing signals and logging technology according to claim 5, characterized in that, The wellbore stability analysis module has preset wellbore stability grading rules. The grading rules include multiple consecutive safety factor intervals, each safety factor interval corresponding to a wellbore stability level. The wellbore stability analysis module calculates the wellbore stability safety factor at each depth position of the target well section. The formula for calculating the wellbore stability safety factor is as follows: ,in, Let z be the wellbore stability safety factor at the target well depth z position at time t. Let z be the uniaxial compressive strength of the surrounding rock at depth z. Given the tangential stress of the surrounding rock at depth z at time t, the well wall stability analysis module compares the calculated well wall stability safety factor at each depth of the target well section with the safety factor interval within the grading rules, matches the well wall stability state level at the corresponding depth position, and generates a well wall stability state distribution sequence for the entire depth range of the target well section.

7. The wellbore stability monitoring system based on the fusion of fiber optic sensor signals and logging technology according to claim 6, characterized in that, The early warning output module is preset with a critical criterion for wellbore instability. The critical criterion corresponds one-to-one with the wellbore stability level. Each wellbore stability level corresponds to a set of early warning output rules. The early warning output module reads the distribution sequence of wellbore stability of the target well section output by the wellbore stability analysis module, compares the wellbore stability level at each depth position in the sequence with the preset critical criterion for instability, triggers the early warning output rule of the corresponding level, and outputs the early warning information of the corresponding depth position.

8. The wellbore stability monitoring system based on the fusion of fiber optic sensing signals and logging technology according to claim 1, characterized in that, The well logging data acquisition module is equipped with an acoustic logging unit, a density logging unit, a geostress logging unit, a caliper logging unit, and a porosity logging unit. The acoustic logging unit collects P-wave velocity and S-wave velocity data of the formation in the target well section. The density logging unit collects the volume density data of the formation in the target well section. The geostress logging unit collects the maximum horizontal principal stress, minimum horizontal principal stress, and vertical principal stress data of the formation in the target well section. The caliper logging unit collects the wellbore diameter and wellbore trajectory data of the target well section. The porosity logging unit collects the porosity and pore pressure data of the formation in the target well section. Based on the collected data, the well logging data acquisition module constructs a basic geological model of the wellbore stability of the target well section.

9. The wellbore stability monitoring system based on the fusion of fiber optic sensor signals and logging technology according to claim 1, characterized in that, The fiber optic sensing monitoring module includes a distributed fiber optic sensing unit, a fiber optic signal demodulation unit, and a wellhead signal conversion unit. The distributed fiber optic sensing unit uses a single-mode strain and temperature integrated sensing fiber. The distributed fiber optic sensing unit is continuously deployed along the outer wall of the casing of the target wellbore. The distributed fiber optic sensing unit is tightly attached to the outer wall of the casing by a fixing clip. The fiber optic signal demodulation unit is deployed at the wellhead ground control end. The fiber optic signal demodulation unit is fused to the wellhead end of the distributed fiber optic sensing unit through the wellhead signal conversion unit. The fiber optic signal demodulation unit collects the strain, temperature, and vibration time-series sensing signals transmitted by the distributed fiber optic sensing unit according to a preset sampling frequency.

10. The wellbore stability monitoring system based on the fusion of fiber optic sensing signals and logging technology according to claim 1, characterized in that, The spatiotemporal coupling calibration module, multi-field signal interpretation module, wellbore stability analysis module, and early warning output module are all integrated into the industrial-grade processing host at the ground control terminal. Each module establishes a bidirectional communication connection through an industrial Ethernet bus. The logging data acquisition module and the fiber optic sensing monitoring module establish a bidirectional communication connection with the industrial-grade processing host at the ground control terminal through a wireless communication link. The logging data acquisition module and the fiber optic sensing monitoring module synchronously transmit the corresponding acquired data to the industrial-grade processing host according to a preset transmission cycle.

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