A fracturing operation monitoring and early warning system and method thereof

Abstract

The present application relates to the technical field of fracturing engineering safety monitoring and intelligent early warning, and specifically relates to a fracturing construction monitoring and early warning system and method, which comprises: obtaining an initialized equivalent system resistance and a flow state correction index; constructing a reference physical model; calculating a theoretical pressure value; calculating a deviation index; in response to the deviation index being greater than a preset dynamic judgment threshold, triggering geological state inversion; in response to the deviation index being less than or equal to the dynamic judgment threshold, returning to execute the step of real-time collection of a current real-time pressure value and a current real-time displacement value of a high-pressure grouting pump; inversely solving to obtain an updated equivalent system resistance; calculating to obtain a risk index; generating a hierarchical early warning and decision instruction; and in response to an early warning event confirmation, updating the initialized equivalent system resistance in the reference physical model to the updated equivalent system resistance; the present application realizes the automation and intelligentization of early warning and decision making, ensures construction safety and improves engineering quality.

Description

Technical Field

[0001] This invention relates to the field of safety monitoring and intelligent early warning technology for fracturing engineering, specifically a fracturing construction monitoring and early warning system and method. Background Technology

[0002] With the widespread application of hydraulic fracturing technology in complex geological conditions, the construction process faces enormous uncertainties and risks. The complex and variable underground geological structure often leads to nonlinear abrupt changes in construction parameters, posing a serious threat to project safety and quality.

[0003] Currently, real-time monitoring of fracturing operations mainly relies on the experience of on-site operators, who make judgments by observing abnormal fluctuations in parameters such as pressure and displacement. This method is highly dependent on personal experience and lacks unified quantitative standards, often resulting in a lag in the identification of sudden geological events. In addition, traditional fixed threshold alarm methods are difficult to adapt to complex and ever-changing working conditions, easily leading to false alarms or missed alarms. They cannot accurately capture key information caused by sudden changes in geological structure. This passive response monitoring mode increases the risk of human misjudgment and is difficult to meet the high requirements of safety and accuracy in modern engineering.

[0004] Therefore, how to achieve real-time, accurate, and quantitative identification of nonlinear abrupt changes in underground geological structures during fracturing, and provide proactive, hierarchical early warning and decision support, has become a key technical problem that urgently needs to be solved to ensure construction safety and improve project quality. Summary of the Invention

[0005] To solve the above-mentioned technical problems, the present invention provides a fracturing construction monitoring and early warning system and method. Specifically, the technical solution of the present invention is as follows:

[0006] A method for monitoring and early warning during fracturing operations, comprising:

[0007] Collect real-time pressure and discharge values ​​of the high-pressure grouting pump during the initial stabilization phase;

[0008] Based on the real-time pressure and displacement values ​​during the initial steady-state phase, the initial equivalent system resistance and flow correction index are obtained by nonlinear least squares fitting.

[0009] A baseline physical model is constructed based on the initial equivalent system drag and the flow regime correction exponent.

[0010] Real-time acquisition of the current real-time pressure and discharge value of the high-pressure grouting pump;

[0011] The theoretical pressure value is calculated based on the baseline physical model and the current real-time displacement value;

[0012] The deviation index is calculated by combining the theoretical pressure value with the current real-time pressure value;

[0013] If the deviation index exceeds a preset dynamic judgment threshold, geological state inversion is triggered to execute subsequent steps.

[0014] If the deviation index is less than or equal to the dynamic judgment threshold, the process returns to the step of performing real-time acquisition of the current real-time pressure value and the current real-time discharge value of the high-pressure grouting pump.

[0015] Based on the current real-time pressure and displacement values ​​at the moment of triggering geological state inversion, the updated equivalent system resistance is obtained by inverse calculation of the benchmark physical model.

[0016] The risk index is calculated based on the initial equivalent system resistance and the updated equivalent system resistance.

[0017] Based on the risk index matching and the preset decision rule base, tiered early warning and decision instructions are generated;

[0018] In response to the confirmation of an early warning event, the initial equivalent system resistance in the baseline physical model is updated to the updated equivalent system resistance to reset the monitoring baseline.

[0019] Preferably, the generation of the dynamic threshold includes:

[0020] Calculate the mean and standard deviation of the deviation index during the reference stable period;

[0021] The products of the mean and standard deviation multiplied by a pre-set confidence coefficient are summed to generate a dynamic judgment threshold.

[0022] Preferably, the calculation of the deviation index includes:

[0023] Obtain the absolute difference between the current real-time pressure value and the theoretical pressure value;

[0024] The absolute difference is divided by the theoretical pressure value to generate a standardized deviation index.

[0025] Preferably, the updated equivalent system resistance is obtained by inverse solving, including:

[0026] It is assumed that the flow regime correction index remains unchanged when the geological state inversion is triggered;

[0027] The updated equivalent system resistance is obtained by dividing the current real-time pressure value at the trigger moment by the flow correction exponent of the current real-time displacement value at that moment.

[0028] Preferably, the calculation of the risk index includes:

[0029] Obtain the absolute difference between the updated equivalent system resistance and the initial equivalent system resistance;

[0030] The absolute difference is divided by the initial equivalent system resistance to generate a risk index that quantifies changes in geological structure.

[0031] Preferably, the decision rule base pre-sets multiple risk index ranges and generates tiered early warnings and decision instructions, including:

[0032] The calculated risk index is matched with multiple risk index ranges;

[0033] Output the warning level and recommended operation instructions corresponding to the risk index range that matches the risk index.

[0034] Preferably, resetting the monitoring baseline includes:

[0035] The updated equivalent system resistance is used as the new initial equivalent system resistance;

[0036] The baseline physical model is updated based on the new initial equivalent system resistance for subsequent monitoring and early warning.

[0037] A fracturing operation monitoring and early warning system, comprising:

[0038] The data acquisition module is used to collect the real-time pressure and real-time discharge values ​​of the high-pressure grouting pump during the initial stabilization stage, and to collect the current real-time pressure and current real-time discharge values ​​in real time.

[0039] The model processing module is used to calibrate and obtain the initial equivalent system drag and flow correction index based on the real-time pressure and displacement values ​​during the initial steady-state phase, and to construct the baseline physical model.

[0040] The deviation calculation module is used to calculate the theoretical pressure value based on the baseline physical model and the current real-time displacement value, and to calculate the deviation index by combining the current real-time pressure value.

[0041] The event judgment module is used to determine whether the deviation index is greater than the preset dynamic judgment threshold. If it is greater, the state inversion module is triggered. If it is less than or equal to the threshold, the data acquisition module is instructed to continue real-time acquisition.

[0042] The state inversion module is used to reverse-solve for the updated equivalent system resistance based on the current real-time pressure value and the current real-time displacement value at the trigger time.

[0043] The risk decision-making module is used to calculate the risk index based on the initial equivalent system resistance and the updated equivalent system resistance, and to generate graded early warning and decision instructions based on the risk index and the decision rule base.

[0044] The model update module is used to update the initial equivalent system resistance in the baseline physical model to the updated equivalent system resistance in response to the confirmation of the early warning event, so as to reset the monitoring baseline.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1. This invention constructs a complete closed loop from data acquisition, model calibration, real-time monitoring, anomaly identification, state inversion, risk quantification to decision support and adaptive model updates. The method acquires real-time pressure and displacement values ​​during the initial stabilization phase and uses nonlinear least squares fitting to calibrate the initial equivalent system resistance and flow correction index, thereby constructing a benchmark physical model that reflects conventional geological conditions. In the real-time monitoring phase, the system continuously acquires current pressure and displacement values ​​and calculates the theoretical pressure value based on the benchmark model. By comparing the theoretical pressure with the actual pressure and calculating the deviation index, the system can quantitatively assess the deviation between the physical process and the benchmark model in real time. This process realizes a shift from passive response to proactive early warning, greatly improving the sensitivity and accuracy of monitoring and reducing the risk of human error.

[0047] 2. This method designs a dynamic judgment threshold generation mechanism based on statistical process control theory, overcoming the technical defects of fixed thresholds that are prone to false alarms or missed alarms under complex working conditions. The dynamic judgment threshold is adaptively generated based on the mean and standard deviation of the deviation index during the reference stable period. It can be adjusted according to the actual fluctuations of equipment status, slurry characteristics and recent geological conditions. This mechanism effectively suppresses false alarms caused by sensor noise and fluctuations in normal working conditions, while ensuring high detection sensitivity for real and significant geological abrupt events, thereby enhancing the robustness and environmental adaptability of the early warning system.

[0048] 3. This method transforms the absolute pressure error into a standardized, dimensionless deviation index, solving the problem that traditional methods struggle to determine the severity of anomalies based solely on the absolute value of the pressure difference. This standardized design ensures that the severity of deviations is comparable under different pressure conditions, guaranteeing that the deviation index can reliably and consistently reflect the true degree of system deviation from the baseline state, providing a more accurate and consistent input for subsequent abrupt change assessments.

[0049] 4. This invention provides a real-time model correction mechanism based on the principle of prioritizing physical reality. When the system determines that a nonlinear abrupt change has occurred, it can quickly utilize the actual pressure and displacement values ​​at the trigger moment, and through the inverse operation of the baseline model, solve for an updated equivalent system resistance that can characterize the new geological state. This step assumes that the flow regime correction index remains unchanged in a short period of time, simplifying the complex bivariate problem into a univariate solution, thereby improving the efficiency and stability of the inversion calculation. This rapid and quantitative state inversion capability provides a key physical basis for subsequent risk assessment and accurate decision-making.

[0050] 5. This invention achieves automation and intelligence in early warning and decision-making by matching the risk index with a preset decision rule base. Simultaneously, the system also possesses an adaptive update mechanism. After an early warning event is confirmed, the updated equivalent system resistance is used as the new monitoring benchmark, enabling the system to learn and adapt to new physical realities. This avoids persistent false alarms caused by benchmark failure, greatly enhancing the intelligence level and practical value of the entire early warning system, ensuring construction safety, and improving project quality. Attached Figure Description

[0051] The present invention will be further explained below with reference to the accompanying drawings and embodiments:

[0052] Figure 1 This is a flowchart of the method of the present invention;

[0053] Figure 2 This is a structural block diagram of the system of the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0055] Example 1:

[0056] Please see Figure 1 A method for monitoring and early warning during fracturing operations, comprising:

[0057] Collect real-time pressure and discharge values ​​of the high-pressure grouting pump during the initial stabilization phase;

[0058] Based on the real-time pressure and displacement values ​​during the initial steady-state phase, the initial equivalent system resistance and flow correction index are obtained by nonlinear least squares fitting.

[0059] A baseline physical model is constructed based on the initial equivalent system drag and the flow regime correction exponent.

[0060] Real-time acquisition of the current real-time pressure and discharge value of the high-pressure grouting pump;

[0061] The theoretical pressure value is calculated based on the baseline physical model and the current real-time displacement value;

[0062] The deviation index is calculated by combining the theoretical pressure value with the current real-time pressure value;

[0063] If the deviation index exceeds a preset dynamic judgment threshold, geological state inversion is triggered to execute subsequent steps.

[0064] If the deviation index is less than or equal to the dynamic judgment threshold, the process returns to the step of performing real-time acquisition of the current real-time pressure value and the current real-time discharge value of the high-pressure grouting pump.

[0065] Based on the current real-time pressure and displacement values ​​at the moment of triggering geological state inversion, the updated equivalent system resistance is obtained by inverse calculation of the benchmark physical model.

[0066] The risk index is calculated based on the initial equivalent system resistance and the updated equivalent system resistance.

[0067] Based on the risk index matching and the preset decision rule base, tiered early warning and decision instructions are generated;

[0068] In response to the confirmation of an early warning event, the initial equivalent system resistance in the baseline physical model is updated to the updated equivalent system resistance to reset the monitoring baseline.

[0069] This embodiment discloses a fracturing construction monitoring and early warning method. Its core purpose is to accurately identify and quantify nonlinear mutation events in the fracturing process by constructing a data-physics real-time coupled model, thereby providing graded early warning and intelligent decision support.

[0070] The initial step of this method is to collect the real-time pressure and discharge values ​​of the high-pressure grouting pump during the initial stabilization phase. In this embodiment, the initial stabilization phase is defined as a time interval after the start of grouting construction, where the root mean square error of the pumping pressure and discharge within a preset time window is less than a set value, representing the current normal and stable geological conditions. Through a standard data acquisition interface, the system synchronously acquires the real-time pump outlet pressure value measured by the pressure sensor and the real-time discharge value measured by the flow meter, forming a dataset for parameter calibration, where the i-th set of data is represented as... ;

[0071] To establish a physical model capable of characterizing this initial state, this method uses real-time pressure and displacement values ​​from the initial steady-state phase, employing nonlinear least squares fitting to calibrate and obtain the initial equivalent system resistance. and flow regime correction index This step aims to abstract the physical process in the initial stage into a mathematical model; its specific implementation involves utilizing multiple sets of collected data. Data, solving for the objective function Minimized and This calibration process ensures that the subsequently constructed baseline model has the highest prediction accuracy under normal operating conditions.

[0072] Based on the calibration results, this method is based on the initial equivalent system resistance. and flow regime correction index A benchmark physical model is constructed; this benchmark physical model is a mathematical expression used to describe the grouting process under normal and stable geological conditions, specifically in this embodiment as follows: The core function of this model is to, in subsequent real-time monitoring, analyze the real-time displacement input. It continuously predicts a theoretical pressure value. This provides a reliable baseline for subsequent anomaly detection;

[0073] Once the real-time monitoring phase begins, the system continuously collects the current real-time pressure value of the high-pressure grouting pump. and current real-time displacement value This step is similar to the initial acquisition, but its purpose is to obtain current data for real-time comparison.

[0074] Based on this baseline physical model, the system uses the baseline physical model and the current real-time displacement value. The theoretical pressure value was calculated. The system will collect the latest data. Substitute into the established benchmark physical model In this process, the theoretical pressure that meets the initial stable geological conditions at this discharge rate is calculated. ;

[0075] To quantify the degree of deviation between reality and theory, the system combines theoretical pressure values. Compared with the current real-time pressure value The deviation index was calculated. This step is passed The formula is used for calculation, where This is a tiny positive constant set to prevent the denominator from being zero; the formula transforms the absolute error of pressure into a standardized relative error, making the severity of the deviation comparable under different pressure conditions.

[0076] To achieve accurate identification of abnormal events, the system responds to the deviation index. Greater than the preset dynamic judgment threshold If this is not achieved, geological state inversion is triggered to execute subsequent steps; the dynamic judgment threshold λ here is an adaptively generated threshold based on historical data statistics; once... The system then determines that a nonlinear physical abrupt change has occurred; in contrast, the response to the deviation index... Less than or equal to the dynamic judgment threshold If the current real-time pressure and discharge values ​​of the high-pressure grouting pump are collected in real time, the process will return to the previous step and continue routine monitoring.

[0077] Once the geological state inversion is triggered, the system uses the current real-time pressure value at the moment the geological state inversion is triggered. and current real-time displacement value The updated equivalent system resistance is obtained by inversely solving the problem using the inverse operation of the baseline physical model. This process is based on the principle of prioritizing physical reality, acknowledging that the current model has failed, and through... The formula calculates in reverse a way that can explain the current real data. New model parameters This step assumes the flow regime index. The pressure remains constant over a short period, thus attributing the sudden change in pressure to system resistance. Dramatic changes;

[0078] get Subsequently, to quantify the risk level, the system is based on the initial equivalent system resistance. and the updated equivalent system resistance Calculate the risk index Through formula Calculate the relative rate of change of system resistance; this risk index It directly and linearly corresponds to the degree of drastic change in geological structure;

[0079] Based on this risk index, the system... The system matches a pre-defined decision rule base to generate tiered early warnings and decision instructions; it also has a built-in mapping rule base that maps risk indices across different ranges. It is linked to specific warning levels and recommended operation instructions to achieve automated warnings and intelligent decision-making;

[0080] To ensure the long-term effectiveness of the system, the system response to the confirmation of early warning events will initialize the equivalent system resistance in the baseline physical model. Updated to the updated equivalent system resistance To reset the monitoring baseline; this operation is performed via To achieve this, and to make it reflect the latest geological conditions. As a new benchmark, this closed-loop update mechanism ensures that the system can learn and adapt to the new physical reality after each geological event.

[0081] This invention constructs a fracturing construction monitoring and early warning method through the aforementioned complete closed-loop process, encompassing data acquisition, model calibration, real-time monitoring, anomaly identification, state inversion, risk quantification, decision support, and adaptive model updates. The lumped-parameter physical model employed in this method offers advantages in computational efficiency and sensitivity to abrupt events, making it particularly suitable for real-time monitoring and early warning scenarios. This model aims to identify nonlinear changes in the overall characteristics of the system, rather than precisely characterizing the three-dimensional geometry of the fracture network; this simplification makes the method highly practical for engineering applications. Compared to traditional methods that rely on operator experience or fixed thresholds, this invention can reveal nonlinear abrupt changes in underground geological structures in real time and quantitatively, greatly improving the sensitivity and accuracy of monitoring, realizing a shift from passive response to proactive early warning, and reducing the risk of human error through intelligent decision support, thus ensuring construction safety and improving project quality.

[0082] Example 2:

[0083] The generation of dynamic thresholds includes:

[0084] Calculate the mean and standard deviation of the deviation index during the reference stable period;

[0085] The products of the mean and standard deviation multiplied by a pre-set confidence coefficient are summed to generate a dynamic judgment threshold.

[0086] This embodiment specifies the generation method of dynamic judgment threshold; its purpose is to design a trigger threshold that can adaptively adjust, effectively filter normal data fluctuations, and accurately capture real abnormal signals, thereby overcoming the technical defects of fixed thresholds that are prone to false alarms or missed alarms under complex working conditions.

[0087] The generation method includes: calculating the mean of the deviation index during the reference stability period. and standard deviation The reference stabilization period can be the model initialization phase or the most recently confirmed normal construction phase; the system records all deviation indices within this phase. The values ​​of are calculated, and their statistical mean and standard deviation are determined.

[0088] Mean with standard deviation Multiply by the preset confidence coefficient The products are then added together to generate a dynamic threshold. The specific calculation formula is as follows: ;

[0089] in, The physical meaning refers to the average level of the deviation index during the stable period, and it is obtained by calculating from historical deviation index data;

[0090] The physical meaning refers to the standard deviation of the deviation index during the stable period, which is obtained by calculating from historical deviation index data;

[0091] k. Physical Confidence Coefficient: This parameter is designed to balance the sensitivity and specificity of the early warning system. Its value is based on the results of retrospective analysis of historical normal construction data. For example, setting... To achieve optimal capture of mutation events while ensuring that 99.7% of normal fluctuations are not falsely reported;

[0092] By using this dynamic threshold generation method based on statistical process control theory, the triggering condition for early warning is no longer a fixed, empirical value, but can be adaptively adjusted according to the actual fluctuations in equipment status, slurry characteristics, and recent geological conditions. This greatly enhances the robustness and environmental adaptability of the early warning system, effectively suppressing false alarms caused by sensor noise and fluctuations in normal operating conditions, while ensuring high detection sensitivity for real and significant geological abrupt events.

[0093] Example 3:

[0094] The calculation of the deviation index includes:

[0095] Obtain the absolute difference between the current real-time pressure value and the theoretical pressure value;

[0096] The absolute difference is divided by the theoretical pressure value to generate a standardized deviation index.

[0097] This embodiment provides a detailed explanation of how the deviation index is calculated. Its purpose is to design a standardized deviation measurement method that can fairly assess the degree of deviation between model predictions and actual conditions, regardless of the magnitude of the absolute value of the current construction pressure.

[0098] The calculation method includes: obtaining the current real-time pressure value. Compared with theoretical pressure value The absolute difference, i.e. ;

[0099] Divide the absolute difference by the theoretical pressure value To generate a standardized deviation index. The complete calculation formula is:

[0100]

[0101] in, The data is collected in real time by a pressure sensor.

[0102] The source is calculated from the baseline physical model in the preceding steps;

[0103] Physical meaning: A tiny normal value set to prevent the denominator from being zero when the theoretical pressure is extremely low. It can be derived from the statistical value of the historical minimum pressure under this operating condition, for example, taking 0.1% of it;

[0104] By converting absolute error into relative error, the deviation index in this embodiment... It becomes a dimensionless parameter; this standardized design makes the severity of deviations directly comparable at different construction stages; it solves the problem that traditional methods cannot judge the severity of anomalies based solely on the absolute value of the pressure difference; therefore, this calculation method ensures that the deviation index can stably and reliably reflect the true degree of deviation of the system from the baseline state, regardless of the current working conditions, providing a more accurate and consistent input for subsequent abrupt change judgments.

[0105] Example 4:

[0106] The updated equivalent system resistance is obtained by inverse solving, including:

[0107] It is assumed that the flow regime correction index remains unchanged when the geological state inversion is triggered;

[0108] The updated equivalent system resistance is obtained by dividing the current real-time pressure value at the trigger moment by the flow correction exponent of the current real-time displacement value at that moment.

[0109] This embodiment uses the updated equivalent system resistance obtained through reverse engineering. The core logic is explained in detail; its technical purpose is to be able to quickly and reasonably update the physical model parameters when the monitoring system determines that a nonlinear mutation has occurred, so as to quantitatively explain and characterize the new geological state after the mutation.

[0110] This reverse solution process is based on a key technical premise: assuming a flow regime correction exponent. It remains unchanged when the geological state is triggered for inversion; its underlying technical logic lies in the significant difference between abrupt changes in geological structure and changes in slurry flow characteristics on a time scale, the former being instantaneous while the latter is relatively stable; this design represents a key technical trade-off, which involves complex bivariate ( The problem is simplified to a single-variable solution. While sacrificing the detailed characterization of flow regime changes, it greatly improves the efficiency, stability and ability to capture the main contradictions of the inversion calculation, ensuring the instantaneous requirement of real-time early warning.

[0111] Based on this assumption, the specific solution steps are as follows: The current real-time pressure value at the trigger moment... Divide by the current real-time displacement value at that moment Flow correction index The power is used to obtain the updated equivalent system resistance. This step is based on the baseline physical model. The direct inverse operation of is calculated using the following formula: ;

[0112] in, The source is the actual pressure value measured by the pressure sensor at the moment when the geological state inversion was triggered;

[0113] The source is the actual discharge value measured by the flow meter at the moment when the geological state inversion was triggered;

[0114] The source uses the flow regime correction index already calibrated in the baseline model; to ensure the robustness of the inversion calculation, the state inversion module has a built-in judgment on the validity of the displacement value; only the current real-time displacement value at the time of triggering the inversion is considered valid. This inverse calculation is only performed when the displacement exceeds a preset minimum effective displacement threshold. This minimum effective displacement threshold is typically set based on the rated operating parameters of the high-pressure grouting pump and construction process requirements; for example, it can be taken as 10% of the normal construction displacement range to ensure that the inverse calculation is performed under stable pump operation. If the value is below this threshold, the system will mark the event as caused by a change in pumping status and will not trigger geological state inversion, thereby avoiding calculation instability and false alarms caused by operating conditions such as pump stoppage or low-speed operation.

[0115] The reverse engineering method in this embodiment provides a real-time model correction mechanism based on the principle of prioritizing physical reality. It can rapidly deduce, using real measurement data, a physical parameter that can quantitatively describe the macroscopic resistance characteristics of the new geological system at the instant a sudden change occurs. For example, when pressure In displacement When the value drops sharply while remaining essentially unchanged, the calculated value is... It will be much smaller than the original This directly and quantitatively corresponds to the scenario of slurry rushing into a large cave from a narrow fissure; this rapid and quantitative state inversion capability provides key physical basis for subsequent risk assessment and accurate decision-making.

[0116] It should be noted that the assumptions in this embodiment are intended to prioritize capturing drastic changes in resistance caused by abrupt changes in geological structure. For other complex working conditions such as significant changes in slurry properties or flow regime itself, this method can be further extended by introducing multi-parameter synchronous inversion or pattern recognition algorithms to achieve more refined physical scene identification.

[0117] Example 5:

[0118] The calculation of the risk index includes:

[0119] Obtain the absolute difference between the updated equivalent system resistance and the initial equivalent system resistance;

[0120] The absolute difference is divided by the initial equivalent system resistance to generate a risk index that quantifies changes in geological structure.

[0121] The decision rule base pre-sets multiple risk index ranges and generates tiered early warnings and decision instructions, including:

[0122] The calculated risk index is matched with multiple risk index ranges;

[0123] Output the warning level and recommended operation instructions corresponding to the risk index range that matches the risk index.

[0124] Resetting the monitoring baseline includes:

[0125] The updated equivalent system resistance is used as the new initial equivalent system resistance;

[0126] The baseline physical model is updated based on the new initial equivalent system resistance for subsequent monitoring and early warning.

[0127] This embodiment is a further refinement and collaborative explanation of a series of core functions from risk assessment and decision generation to model updating. These steps together constitute a complete perception-decision-adaptation closed loop.

[0128] To achieve risk assessment, this method imposes the following limitations on the calculation of the risk index: Obtaining the updated equivalent system resistance. Equivalent system resistance with initialization The absolute difference is then divided by the initial equivalent system resistance. To generate a risk index that quantifies changes in geological structure. Its calculation formula is ;

[0129] To achieve decision support, this method imposes the following limitations on the generation of tiered early warning and decision instructions: the system pre-sets multiple risk index ranges in the decision rule base, such as the first-level early warning range. and Level II warning zone The specific thresholds for these risk index ranges are pre-set based on statistical analysis of similar abrupt events in historical fracturing operation data, combined with the experience of on-site experts, aiming to distinguish geological structural changes of different severity; the calculated risk indices... Match these intervals and output the warning level and recommended action instructions corresponding to the matched intervals; for example, if the calculation shows... If the system matches the first-level warning zone, it will automatically trigger a yellow warning and send a warning message to the user interface: System resistance has decreased significantly; Recommendation: Reduce displacement by 30%.

[0130] To achieve system self-adaptation, this method imposes the following limitations on resetting the monitoring benchmark: the updated equivalent system resistance... As a new initial equivalent system resistance That is, execution Operation, and based on the new Update the baseline physical model for subsequent monitoring and early warning;

[0131] This embodiment constructs a complete intelligent closed loop from quantitative risk assessment to intelligent decision support, and then to system self-adaptation. It realizes the automation and standardization of early warning and decision-making, and ensures that the monitoring system can learn new geological realities after experiencing a geological mutation event, avoiding continuous false alarms caused by the failure of the baseline. The synergistic effect of the three greatly improves the intelligence level and practical value of the entire early warning system.

[0132] Example 6:

[0133] Please see Figure 2 A fracturing construction monitoring and early warning system, comprising:

[0134] The data acquisition module is used to collect the real-time pressure and real-time discharge values ​​of the high-pressure grouting pump during the initial stabilization stage, and to collect the current real-time pressure and current real-time discharge values ​​in real time.

[0135] The model processing module is used to calibrate and obtain the initial equivalent system drag and flow correction index based on the real-time pressure and displacement values ​​during the initial steady-state phase, and to construct the baseline physical model.

[0136] The deviation calculation module is used to calculate the theoretical pressure value based on the baseline physical model and the current real-time displacement value, and to calculate the deviation index by combining the current real-time pressure value.

[0137] The event judgment module is used to determine whether the deviation index is greater than the preset dynamic judgment threshold. If it is greater, the state inversion module is triggered. If it is less than or equal to the threshold, the data acquisition module is instructed to continue real-time acquisition.

[0138] The state inversion module is used to reverse-solve for the updated equivalent system resistance based on the current real-time pressure value and the current real-time displacement value at the trigger time.

[0139] The risk decision-making module is used to calculate the risk index based on the initial equivalent system resistance and the updated equivalent system resistance, and to generate graded early warning and decision instructions based on the risk index and the decision rule base.

[0140] The model update module is used to update the initial equivalent system resistance in the baseline physical model to the updated equivalent system resistance in response to the confirmation of the early warning event, so as to reset the monitoring baseline.

[0141] This embodiment discloses a fracturing construction monitoring and early warning system. Through modular structural design, the system achieves the integration and automation of data processing, model calculation and decision support.

[0142] The system includes:

[0143] The data acquisition module aims to provide real-time, synchronous data input for the entire system. This module is used to acquire the real-time pressure and discharge values ​​of the high-pressure grouting pump during the initial stabilization phase, and to acquire the current real-time pressure and discharge values ​​in real time.

[0144] The model processing module, as the core computing unit of the system, is used to calibrate and obtain the initial equivalent system resistance based on the real-time pressure and displacement values ​​during the initial steady-state phase, using a built-in nonlinear least squares fitting algorithm. and flow regime correction index And based on this, a benchmark physical model is constructed;

[0145] The deviation calculation module aims to quantify the deviation between physical reality and model predictions in real time; this module is used to calculate the deviation based on the baseline physical model and the current real-time displacement value. Calculate the theoretical pressure value And combined with the current real-time pressure value The deviation index was calculated. ;

[0146] The event judgment module, as the system's anomaly detection unit, is used to determine the deviation index. Is it greater than the preset dynamic judgment threshold? If the value is greater than 1, it is determined to be a nonlinear mutation event and the state inversion module is triggered; if the value is less than or equal to 1, the data acquisition module is instructed to continue normal real-time acquisition.

[0147] The state inversion module aims to reverse-engineer model parameters that characterize the new geological state when an anomalous event occurs; this module is used to solve for the current real-time pressure value at the trigger time. and current real-time displacement value The updated equivalent system resistance is obtained by inversely solving the problem using the inverse operation of the baseline physical model. ;

[0148] The risk decision-making module aims to translate changes in physical parameters into intuitive risk levels and actionable instructions; this module is used to determine the risk level based on the initial equivalent system resistance. and the updated equivalent system resistance Calculate the risk index And based on this risk index It matches the built-in decision rule library to generate tiered warnings and decision instructions;

[0149] The model update module aims to ensure the long-term adaptability and effectiveness of the system. This module is used in response to operator confirmation of warning events, updating the initial equivalent system resistance in the baseline physical model. Updated to the updated equivalent system resistance calculated by the state inversion module. To reset the monitoring baseline;

[0150] Example 6:

[0151] This invention provides a method for monitoring and early warning during fracturing operations. The following detailed explanation uses the actual monitoring process of shale gas well fracturing operations as an example:

[0152] During the initial stabilization grouting stage, the data acquisition module continuously collected five sets of real-time pressure and discharge data from the high-pressure grouting pump. The specific data is shown in Table 1 below:

[0153]

[0154] Using the data in the table above, the model processing module solves the objective function by fitting the data using the nonlinear least squares method. Calibration yields the initial equivalent system resistance. and flow regime correction index ;

[0155] Based on this, the baseline physical model is constructed as follows: This model accurately describes the pressure-displacement relationship under current geological conditions.

[0156] During the subsequent reference stabilization period, the system continuously calculated 100 deviation indices based on the baseline physical model. According to statistics, the mean of the deviation index for this group is The standard deviation is ;

[0157] Set confidence coefficient (To cover 99.7% of normal fluctuations), the dynamic judgment threshold is calculated as follows:

[0158]

[0159] After entering the real-time monitoring phase:

[0160] exist At any given moment, the data acquisition module measures the current real-time displacement value. m³ / min, current real-time pressure value MPa; The deviation calculation module first calculates the theoretical pressure value: MPa; then calculate the deviation index: ;because The event judgment module determines that the system is operating normally and continues monitoring;

[0161] exist At that moment, the hydraulic fracturing fracture suddenly connected with a large natural fracture network underground, causing a sharp drop in pressure; the data acquisition module measured the current real-time displacement value. m³ / min (basically stable), while the current real-time pressure value has suddenly dropped to m³ / min. MPa; The deviation calculation module recalculates the theoretical pressure value: MPa; and calculate the deviation index at this moment: ;because The event judgment module determines that a nonlinear mutation has occurred and immediately triggers the geological state inversion.

[0162] The state inversion module assumes a flow correction index. Remains unchanged in a short period of time, based on Using real data at each moment, we can reverse engineer the solution to obtain the updated equivalent system resistance:

[0163]

[0164] Subsequently, the risk decision-making module calculates a risk index to quantify the severity of this geological structural change:

[0165]

[0166] The risk decision-making module matches decisions based on a pre-defined decision rule base (as shown in Table 2 below):

[0167]

[0168] Calculated risk index The system falls within the Level 2 warning range of (0.3, 0.7); the system automatically generates and issues an orange warning, and pushes a decision instruction to the operator's interface: "The system resistance has decreased significantly, suspected to be a large-scale communication gap, it is recommended to reduce the displacement by 30%."

[0169] After the on-site operators complete the emission reduction operation according to the instructions and confirm the warning event, the model update module updates the initial equivalent system drag in the baseline physical model to... That is, execution Operations; New benchmark physics model It takes effect and is used for subsequent monitoring and early warning, enabling the system to learn and adapt to new geological conditions and avoid continuous false alarms caused by the failure of the baseline.

[0170] This invention provides a complete and automated fracturing construction monitoring and early warning solution through the above-mentioned modular system design. Each module performs its own function and works closely together, and the innovative method is solidified into a stable and reliable hardware or software system. The system can independently complete the entire process from bottom-level data acquisition to top-level intelligent decision-making, encapsulates complex algorithm models internally, and provides clear and timely early warning information and clear handling suggestions for on-site operators, thereby significantly improving the safety, efficiency and scientific nature of fracturing construction under complex geological conditions.

[0171] The above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention; any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0172] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for monitoring and early warning during fracturing operations, characterized in that, include: Collect real-time pressure and discharge values ​​of the high-pressure grouting pump during the initial stabilization phase; Based on the real-time pressure and displacement values ​​during the initial steady-state phase, the initial equivalent system resistance and flow correction index are obtained by nonlinear least squares fitting. A baseline physical model is constructed based on the initial equivalent system drag and the flow regime correction exponent. Real-time acquisition of the current real-time pressure and discharge value of the high-pressure grouting pump; The theoretical pressure value is calculated based on the baseline physical model and the current real-time displacement value; The deviation index is calculated by combining the theoretical pressure value with the current real-time pressure value; If the deviation index exceeds a preset dynamic judgment threshold, geological state inversion is triggered to execute subsequent steps. If the deviation index is less than or equal to the dynamic judgment threshold, the process returns to the step of performing real-time acquisition of the current real-time pressure value and the current real-time discharge value of the high-pressure grouting pump. Based on the current real-time pressure and displacement values ​​at the moment of triggering geological state inversion, the updated equivalent system resistance is obtained by inverse calculation of the benchmark physical model. The risk index is calculated based on the initial equivalent system resistance and the updated equivalent system resistance. Based on the risk index matching and the preset decision rule base, tiered early warning and decision instructions are generated; In response to the confirmation of an early warning event, the initial equivalent system resistance in the baseline physical model is updated to the updated equivalent system resistance to reset the monitoring baseline.

2. The fracturing construction monitoring and early warning method according to claim 1, characterized in that, The generation of dynamic thresholds includes: Calculate the mean and standard deviation of the deviation index during the reference stable period; The products of the mean and standard deviation multiplied by a pre-set confidence coefficient are summed to generate a dynamic judgment threshold.

3. The fracturing construction monitoring and early warning method according to claim 1, characterized in that, The calculation of the deviation index includes: Obtain the absolute difference between the current real-time pressure value and the theoretical pressure value; The absolute difference is divided by the theoretical pressure value to generate a standardized deviation index.

4. The fracturing construction monitoring and early warning method according to claim 1, characterized in that, The updated equivalent system resistance is obtained by inverse solving, including: It is assumed that the flow regime correction index remains unchanged when the geological state inversion is triggered; The updated equivalent system resistance is obtained by dividing the current real-time pressure value at the trigger moment by the flow correction exponent of the current real-time displacement value at that moment.

5. The method for monitoring and early warning during fracturing operations according to claim 1, characterized in that, The calculation of the risk index includes: Obtain the absolute difference between the updated equivalent system resistance and the initial equivalent system resistance; The absolute difference is divided by the initial equivalent system resistance to generate a risk index that quantifies changes in geological structure.

6. The method for monitoring and early warning during fracturing operations according to claim 1, characterized in that, The decision rule base pre-sets multiple risk index ranges and generates tiered early warnings and decision instructions, including: The calculated risk index is matched with multiple risk index ranges; Output the warning level and recommended operation instructions corresponding to the risk index range that matches the risk index.

7. The method for monitoring and early warning during fracturing operations according to claim 1, characterized in that, Resetting the monitoring baseline includes: The updated equivalent system resistance is used as the new initial equivalent system resistance; The baseline physical model is updated based on the new initial equivalent system resistance for subsequent monitoring and early warning.

8. A fracturing construction monitoring and early warning system, based on the fracturing construction monitoring and early warning method according to any one of claims 1-7, characterized in that, include: The data acquisition module is used to collect the real-time pressure and real-time discharge values ​​of the high-pressure grouting pump during the initial stabilization stage, and to collect the current real-time pressure and current real-time discharge values ​​in real time. The model processing module is used to calibrate and obtain the initial equivalent system drag and flow correction index based on the real-time pressure and displacement values ​​during the initial steady-state phase, and to construct the baseline physical model. The deviation calculation module is used to calculate the theoretical pressure value based on the baseline physical model and the current real-time displacement value, and to calculate the deviation index by combining the current real-time pressure value. The event judgment module is used to determine whether the deviation index is greater than the preset dynamic judgment threshold. If it is greater, the state inversion module is triggered. If it is less than or equal to the threshold, the data acquisition module is instructed to continue real-time acquisition. The state inversion module is used to reverse-solve for the updated equivalent system resistance based on the current real-time pressure value and the current real-time displacement value at the trigger time. The risk decision-making module is used to calculate the risk index based on the initial equivalent system resistance and the updated equivalent system resistance, and to generate graded early warning and decision instructions based on the risk index and the decision rule base. The model update module is used to update the initial equivalent system resistance in the baseline physical model to the updated equivalent system resistance in response to the confirmation of the early warning event, so as to reset the monitoring baseline.

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