Well periphery full-resolution electromagnetic imaging method and system

Abstract

The invention relates to the technical field of electromagnetic detection and imaging, in particular to a well circumference full-resolution electromagnetic imaging method and system. The method comprises the following steps: acquiring well periphery stratum response through low-intrusion transient electromagnetic excitation, extracting propagation state parameters, and introducing space distinguishability measurement to form well periphery space distinguishability distribution; a self-adaptive electromagnetic excitation configuration is generated, and response enhancement of a low-distinguishable region and energy optimization of a high-distinguishable region are realized through time frequency azimuth phase multi-dimensional modulation; collecting multi-configuration response under the action of adaptive excitation, constructing a time-frequency-azimuth multi-dimensional fingerprint, and performing sparse decoupling and normalization processing to form a high-resolution multi-dimensional distinguishable fingerprint field; a spatial fingerprint consistency relationship is constructed by taking a fingerprint field as a core, a stable and explainable whole-well-periphery electromagnetic imaging result is evolved through consistency propagation and abnormal constraint, and the imaging credibility is synchronously calculated. According to the invention, the resolution and reliability of electromagnetic imaging in a complex well surrounding environment are effectively improved.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic detection and imaging technology, specifically to a well-circumference full-resolution electromagnetic imaging method and system. Background Technology

[0002] In the field of oil and gas exploration and development, a precise understanding of the geological structure around the well is crucial for reservoir evaluation, drilling safety, and optimization of production enhancement measures. Electromagnetic detection and imaging technology, as an important geophysical method, has been continuously valued and applied in the characterization of geological structures in wells due to its sensitivity to formation electrical parameters and controllable detection range.

[0003] Chinese invention patent CN113447990B discloses a method for observing electrical anomalies in well sites. The method includes: transmitting near-steady-state electromagnetic signals to a target formation downhole via a line source excitation signal source, and collecting electromagnetic response signals via a ground receiver on the surface; statistically analyzing the electromagnetic response signals collected at different times, and extracting downhole electrical anomaly information based on the differences in the different electromagnetic response signals; constructing a downhole active, formation-condition electrical anomaly model based on the quasi-steady-state electromagnetic field characteristic response equation and finite element numerical simulation technology, calculating the surface electromagnetic theoretical response signal, which is used for sensitivity analysis of different electromagnetic components to downhole electrical anomalies, and optimizing the excitation method and the arrangement of the ground receiver.

[0004] In recent years, with the advancement of sensor technology, signal processing and computing methods, downhole electromagnetic detection is developing towards higher resolution, stronger environmental adaptability and more intelligent interpretation. In order to better serve the needs of fine detection in complex oil and gas reservoirs and heterogeneous formations, the industry expects to develop an advanced technology that can fully exploit the spatial information of electromagnetic response, adapt to complex downhole environments and achieve highly reliable automated imaging. Summary of the Invention

[0005] The purpose of this invention is to address the problems existing in the background art by proposing a well-rounded full-resolution electromagnetic imaging method and system.

[0006] The technical solution of this invention: a well-circumference full-resolution electromagnetic imaging method, comprising the following specific implementation steps: S1. By applying low-intrusion transient electromagnetic excitation in the well, the formation response around the well is obtained, the propagation state parameters are extracted, the electromagnetic distinguishability index is calculated, and a spatially distinguishable distribution around the well is formed. S2. Based on the spatial distinguishability distribution around the well, a spatial excitation demand function is generated by mapping, and then the time parameter, frequency parameter and phase parameter of the electromagnetic excitation signal in different azimuth intervals are adaptively adjusted to generate an adaptive electromagnetic excitation configuration set containing multiple excitations. S3. Under the action of the adaptive electromagnetic excitation configuration set, the electromagnetic response around the well of multiple configurations is collected. Time-frequency analysis is performed on the response at each spatial location to construct a multidimensional response fingerprint vector. The multidimensional response fingerprint vector is then subjected to spatial sparse decoupling and normalization to form a decoupled and normalized well-around electromagnetic response fingerprint field. S4. Based on the well-circumferential electromagnetic response fingerprint field, a spatial fingerprint consistency kernel is constructed. The structural information is diffused in the high consistency region and suppressed in the low consistency region through an iterative propagation model. At the same time, the local fingerprint deviation is introduced as an anomaly constraint factor to enhance the features of the anomaly region. Finally, the whole-well-circumferential electromagnetic imaging results and the corresponding imaging confidence distribution are evolved and output.

[0007] Preferably, in step S1, extracting the propagation state parameters specifically involves extracting the equivalent propagation delay factor, equivalent energy attenuation coefficient, response diffusion factor, and direction consistency factor from the electromagnetic response signals at each receiving direction. The equivalent propagation delay factor is used to describe the time delay of electromagnetic disturbance propagation to the main response region; The equivalent energy attenuation coefficient is obtained by fitting the attenuation characteristics of the response signal amplitude over time. The response diffusion factor is used to characterize the expansion width of the electromagnetic response in the time domain; The directional consistency factor is used to describe the similarity between the directional response pattern and the adjacent directional response patterns.

[0008] Preferably, in step S2, the mapping to generate the spatial excitation demand function specifically involves: The distinguishability value of each location in the spatial distinguishability distribution around the well is converted into the required excitation demand intensity at that location through an inverse proportional mapping relationship. The value is then weighted by a spatial weighting function determined by well section geometry and well fluid distribution factors to form a quantified spatial excitation demand distribution.

[0009] Preferably, in step S2, the adaptive adjustment of the time and frequency parameters of the electromagnetic excitation signal specifically involves: Based on the spatial excitation demand function, the decay time constant of each excitation signal is dynamically adjusted, and the excitation angular frequency of the excitation signal is adjusted synchronously, so that the excitation in the low resolution region has more sufficient time domain broadening and appropriate frequency domain offset.

[0010] Preferably, in step S2, setting the phase for different azimuth intervals specifically involves: The wellbore space is divided into several intervals along the azimuth. The average value of the excitation demand intensity of all spatial units in each azimuth interval is calculated as the comprehensive excitation demand weight of that interval. Based on this weight, different phase offset values ​​are assigned to excitation signals of different orders in each azimuth interval, thereby forming a controllable phase difference in the azimuth dimension.

[0011] Preferably, in step S3, constructing the multidimensional response fingerprint vector specifically involves: For each spatial location, the original electromagnetic response time series collected under each excitation configuration and each orientation is transformed by the time-frequency feature extraction operator to obtain a feature representation containing spectrum, energy distribution or instantaneous frequency information. The feature representations of the spatial location under all excitation configurations and all orientations are combined to form a multidimensional response fingerprint vector of the spatial location.

[0012] Preferably, in step S3, the spatial sparse decoupling of the multidimensional response fingerprint vector specifically involves: The fingerprint vectors of all spatial units around the well are combined into a fingerprint matrix. For each target spatial unit, the similarity between its fingerprint vector and the fingerprint vectors of all other units is calculated to construct a spatial interference constraint matrix describing the interference intensity. A set of sparse projection coefficients is obtained by solving an optimization problem with regularization constraints. These coefficients are then used to linearly combine the fingerprint vectors of other units to approximate the fingerprint of the target unit. Subtract the approximation result from the original fingerprint vector of the target unit to obtain the fingerprint vector after decoupling with minimized interference.

[0013] Preferably, in step S4, constructing the spatial fingerprint consistency kernel specifically involves: For any two spatial locations in the well perimeter space, calculate the difference measure between their corresponding decoupled normalized fingerprint vectors. Input this difference measure into a kernel function with the fingerprint scale parameter as the control factor. The output value of the kernel function is the consistency kernel value that characterizes the degree of electromagnetic structural similarity between the two points. The smaller the difference, the larger the consistency kernel value.

[0014] Preferably, in step S4, the local fingerprint deviation is introduced as an anomaly constraint factor as follows: For each spatial location, the difference strength between its decoupled normalized fingerprint vector and the mean of the fingerprint vectors of all locations in its neighborhood is calculated to obtain the fingerprint deviation at that location. The fingerprint deviation is mapped to an anomaly weight factor through a non-linear function; During the iterative propagation process, the abnormal weight factor is used as an enhancement coefficient and applied to the structural propagation field at the corresponding position, thereby enhancing and preserving the fingerprint features at that position during the propagation process.

[0015] The technical solution of the present invention: a well-circumference full-resolution electromagnetic imaging system, used to perform the above-mentioned well-circumference full-resolution electromagnetic imaging method, comprising: The well perimeter electromagnetic acquisition and environmental sensing module is equipped with a downhole multi-directional adjustable excitation source and an integrated intelligent multi-directional sensor array. It is used to transmit adaptive electromagnetic signals to the well perimeter, synchronously acquire multi-directional electromagnetic responses, perform local noise suppression and signal preprocessing, and output a high signal-to-noise ratio initial electromagnetic response characteristic data stream. The multi-configuration excitation and spatial fingerprint construction module is connected to the well-circumferential electromagnetic acquisition and environmental perception module. It is used to receive the initial electromagnetic response feature data stream, implement the generation and control of the multi-configuration excitation strategy, and construct and output the decoupled and normalized well-circumferential spatial fingerprint field by performing time-frequency analysis, feature extraction, spatial sparse decoupling and normalization processing on the response data. The spatial fingerprint consistency evolution and anomaly enhancement module is connected to the multi-configuration excitation and spatial fingerprint construction module. It is used to receive the spatial fingerprint field, construct the spatial consistency kernel based on fingerprint similarity, run the iterative propagation algorithm to diffuse structural information in the high consistency region and use the anomaly weight factor to enhance the local anomaly features, and finally evolve to generate a stable well perimeter spatial structure field. The whole-well-circumference imaging output and credibility assessment module is connected to the spatial fingerprint consistency evolution and anomaly enhancement module. It is used to receive the spatial structure field, normalize it to generate a whole-well-circumference continuous electromagnetic imaging map, synchronously calculate the imaging credibility index of each spatial unit and mark the abnormal area, and output imaging results and credibility distribution map that can be used for engineering decision-making.

[0016] Compared with the prior art, the above-mentioned technical solution of the present invention has the following beneficial technical effects: This invention designs a wellbore full-resolution electromagnetic imaging method and system. By constructing a wellbore spatial resolvability field and using it for adaptive excitation design, the electromagnetic resolution capability for complex geological structures around the well is significantly improved. The system employs an intelligent sensor array for in-situ signal acquisition and preprocessing, effectively suppressing downhole noise interference, improving data quality and system response speed, and ensuring the reliability and stability of the imaging process. Based on the spatial fingerprint consistency evolution imaging mechanism, it can achieve natural propagation of structural information and enhanced preservation of anomalous regions without the need for strong regularization assumptions, thereby simultaneously obtaining continuous and smooth background imaging and clear and prominent anomaly markers. This invention has good environmental adaptability and dynamic adjustment capabilities, and can automatically optimize the excitation strategy and imaging parameters according to the actual electromagnetic response characteristics around the well, enhancing its applicability and robustness under different geological conditions and wellbore environments. The overall scheme of this invention forms a closed-loop technical system from excitation, acquisition, processing to imaging, which not only improves the overall performance of full-wellbore electromagnetic imaging, but also provides a reliable basis for engineering decision-making with both visual results and credibility assessment. Attached Figure Description

[0017] Figure 1This is a flowchart of a well-circumference full-resolution electromagnetic imaging method proposed in this invention; Figure 2 This is a system architecture diagram of a well-circumference full-resolution electromagnetic imaging system proposed in this invention. Detailed Implementation

[0018] Example 1, as Figure 1 As shown, the well-circumference full-resolution electromagnetic imaging method proposed in this invention includes the following specific implementation steps: S1. By applying low-intrusion transient electromagnetic excitation in the well, the actual response behavior of the formation around the well to electromagnetic disturbances is obtained, and the complex response is transformed into stable propagation state parameters. Based on this, a spatial distinguishability metric is introduced to quantitatively characterize the distinguishability of different spatial units around the well in the electromagnetic domain. Finally, a spatially distinguishable distribution around the well that can directly constrain subsequent excitation design and imaging decoupling is formed. The specific implementation process is as follows: S11. A short-duration, low-energy transient electromagnetic excitation is applied to the target well section through the downhole transmitting unit. Without significantly altering the original propagation state around the well, this induces a natural electromagnetic response in the near-wellbore formation. Simultaneously, multi-directional receiving units collect response signals from different directions, providing a realistic and low-disturbance raw data foundation for subsequent propagation state analysis. Specifically: To minimize disruption to the original propagation state around the well, the natural response of the formation to electromagnetic excitation is obtained through short-duration, low-energy transient electromagnetic disturbances. Within the target well section, a reference transient excitation signal is applied via a downhole electromagnetic transmission unit, the time expression of which is defined as: ; Electromagnetic response signals are synchronously acquired by receiving units arranged at different locations around the well. , i represents the receiving azimuth number; this response signal truly reflects the comprehensive propagation behavior of electromagnetic waves in the wellbore, well fluid and near-wellbore formation; in, The reference transient electromagnetic excitation signal applied by the transmitting unit in the well is used to induce the transient electromagnetic response of the formation around the well without significantly disturbing the original electromagnetic propagation state around the well; t represents the time variable of excitation or response, used to characterize the entire process of electromagnetic signal transmission, propagation and reception. The initial amplitude of the reference excitation signal is determined by the structural parameters of the downhole transmitting coil, the downhole power supply capacity, and the downhole operation safety regulations. This ensures that the excitation signal can effectively excite the electromagnetic response without introducing nonlinear effects. The decay time constant of the excitation signal is used to control the concentration of excitation energy over time, so that the electromagnetic disturbance mainly acts on the near-wellbore transient propagation stage; This represents the unit step function, used to describe the activation characteristics of the excitation signal within the physically realizable time interval, ensuring that the excitation process conforms to the actual downhole control logic; It represents the electromagnetic response signal in the i-th receiving direction or azimuth, reflecting the comprehensive propagation result of electromagnetic excitation in the wellbore, well fluid and near-well formation, and is the raw observation data for the extraction of propagation state parameters; S12. Perform time-series behavior analysis on the acquired well-circumferential electromagnetic response signals, extracting propagation state parameters from the perspectives of propagation delay, energy attenuation, response diffusion, and directional consistency. These parameters characterize the overall behavior of well-circumferential electromagnetic propagation, replacing the original signal expression susceptible to noise and coupling with a stable parameterized form. Specifically: Stable and comparable propagation state quantities are extracted from the temporal behavior of the response signal and used as an intermediate expression layer for the well-circumferential electromagnetic propagation characteristics. For each received signal By fitting its time envelope, attenuation trend, and initial arrival characteristics, a corresponding propagation state parameter vector is constructed: ; in, The electromagnetic propagation state parameter vector corresponding to the i-th receiving direction is a comprehensive description of the electromagnetic propagation behavior in that direction and is used to compare the propagation characteristics of different directions on a unified scale. The equivalent propagation delay factor is used to describe the time delay experienced by an electromagnetic disturbance from the source to the main response zone in the i-th direction. Its magnitude comprehensively reflects the propagation path length, the electrical properties of the near-wellbore medium, and the wellbore conditions. The equivalent energy attenuation coefficient is obtained by fitting the attenuation characteristics of the response signal amplitude over time. It is used to characterize the loss of electromagnetic energy during propagation and reflects the combined influence of formation electrical properties and well fluid conductivity. The response diffusion factor is used to characterize the spread width of the electromagnetic response in the time domain, reflecting the degree of influence of formation heterogeneity and medium dispersion effect on electromagnetic propagation. The directional consistency factor describes the similarity between the electromagnetic response pattern in this direction and the response pattern in adjacent directions. It is an important indicator for measuring the heterogeneity and directional differences in the wellbore space. S13. Based on propagation state parameters, the response differences between different radial and azimuth spatial units around the well are quantitatively calculated. An electromagnetic distinguishability index is introduced to clarify the distinguishability of each spatial unit in electromagnetic response, thereby identifying potential imaging aliasing regions and naturally high-resolution regions. Specifically: After obtaining the propagation state parameters, a spatial distinguishability index is introduced to quantitatively evaluate the ability to distinguish between different spatial units around the well. The wellbore space is divided into several spatial units along the radial and azimuth directions. For any two spatial units p and q, their electromagnetic distinguishability index is defined as: ; in, An electromagnetic distinguishability index representing the difference between spatial unit p and spatial unit q, used to quantify the degree of difference in their electromagnetic propagation behavior; , and The weighting coefficients for each component in the propagation state parameters are used to balance the influence of different parameters in the distinguishability calculation. Their values ​​are normalized based on downhole noise levels, parameter stability, and engineering experience. S14. The electromagnetic resolvability results of discrete spatial units are fused into a continuous well-perimeter spatial resolvability distribution, forming a constraint field that reflects the strength of the distinguishing ability at different locations around the well. This constraint is then used as a priori input condition for subsequent adaptive excitation configuration design and imaging decoupling reconstruction, specifically: The discriminability results of discrete spatial units are elevated to a continuous spatial constraint form. For any location x around the well, its comprehensive electromagnetic discriminability function is defined as follows: ; To ensure the engineering usability of the results, spatial continuity and stabilization processes were performed to construct a well-perimeter spatially resolvable field: ; To obtain a continuous, resolvable field around the well. Subsequently, based on its numerical distribution characteristics, the well perimeter space was divided into regions of different distinguishability: when When this occurs, it is defined as a low-resolution region, in which different spatial units are highly similar in electromagnetic response, and there is a significant risk of aliasing. when When this is defined as the transition distinguishable region; when When this is the case, it is defined as a high-resolution region; in, Represents the smoothed well perimeter spatial distinguishability field; represents the spatial kernel function, used to describe the influence weights between adjacent spatial units around the well, and its value is related to the radial distance and azimuth difference; y represents any reference position in the space around the well. and The distinguishability threshold is determined adaptively based on the distribution of downhole noise levels and propagation state parameters; x represents the coordinates of any location in the wellbore space. This represents the overall electromagnetic resolvability value at location x around the well. This represents a set of spatial units around a well, used to define the spatial extent involved in distinguishability statistics; This indicates the number of spatial units contained in the well perimeter spatial unit set.

[0019] S2. Based on the well-circumferential spatial resolvability field obtained in step S1, an adaptive electromagnetic excitation configuration is generated. By converting spatial resolvability into excitation requirements and combining multi-dimensional modulation of time, frequency, azimuth, and phase, response enhancement in low-resolvability areas and energy optimization in high-resolvability areas are achieved, thereby providing a highly discriminative response input for subsequent well-circumferential imaging. Simultaneously, it possesses dynamic adjustability to adapt to changes in spatial propagation state. The specific implementation process is as follows: S21. Map the continuous distinguishability field output in step S1 to an excitation demand function. Adaptively determine the intensity demand for excitation at each location based on the spatial distinguishability level. Combine this with downhole geometry and environmental weights to form a quantified spatial excitation demand distribution. This provides a clear objective for temporal and spatial modulation, ensuring that low-distinguishability areas receive more excitation attention while high-distinguishability areas maintain moderate excitation, thus achieving spatially differentiated driving. Specifically: Define an incentive demand function. Through this mapping, the distinguishability field, which was originally only used as an analysis result, is transformed into a quantitative parameter that directly drives the incentive strategy, thus realizing a logical closed loop of analysis before design: ; in, Indicates the intensity of incentive demand; This represents the stability term, the lower limit of system noise, and avoiding a zero denominator. This represents the spatial weighting function, which combines well section geometry, well diameter, and well fluid distribution. S22. Based on the excitation demand function, the decay time and main frequency parameters of the electromagnetic excitation signal are adaptively adjusted to ensure more complete excitation time expansion and appropriate frequency offset in the low-resolution region, forming differentiated responses in the time and frequency domains, enhancing spatial distinguishability, while ensuring downhole power supply and safety constraints, avoiding excessive energy concentration, improving the response distinguishability of different spatial units, and laying the foundation for multi-configuration excitation. Specifically: Incentive demand function It is further used to generate controllable electromagnetic excitation signals, with the goal of making the response in the low-resolution region more distinguishable in the time and frequency domains by adjusting the time broadening and frequency characteristics. Define the k-th excitation signal: ; Adaptive adjustment of signal decay time constant and excitation angular frequency : ; ; in, This represents the k-th excitation signal; This indicates the excitation amplitude, which is adaptively limited based on downhole power supply conditions. Indicates the signal decay time constant; Indicates the excitation angular frequency, which is adaptively adjusted; Indicates the reference phase; and This represents the modulation coefficient, used to control the amplitude of changes in the time structure; Indicates the reference angular frequency; S23. The wellbore space is divided into azimuth intervals. The directional weight is calculated based on the excitation requirements of each interval, and a phase offset is applied to the multi-directional transmitting units to create a controllable phase difference in low-resolution regions. This achieves spatial response separation in the azimuth dimension. Time and frequency modulation, along with directional phase modulation, work synergistically to suppress aliasing and improve the overall wellbore spatial resolution, providing multi-dimensional differentiated signals for subsequent response acquisition. Specifically: The horizontal section along the well diameter of the well perimeter space is divided into M azimuth intervals. Each directional interval covers several spatial units. ; For each directional interval, calculate its comprehensive incentive demand weight: ; For the k-th excitation in the azimuth interval Phase settings on: ; Output the final phase setting set of multiple excitations in each direction. ; in, This represents the comprehensive excitation weight for the m-th azimuth interval, used to determine the additional phase modulation required in that direction; Indicates the number of spatial units contained in the azimuth interval; This represents the set of all spatial units within the corresponding azimuth interval; K represents the number of temporal configurations; M represents the number of spatial azimuth intervals. S24. By combining excitations from all directions, multiple time and frequency modulations, and phase optimization, a complete set of adaptive excitation configurations is generated, which can be dynamically updated to adapt to changes in well perimeter distinguishability. Specifically: By combining the above time / frequency / direction / phase modulation results, an executable set of excitation configurations is generated: ; Where S represents the set of adaptive excitation configurations; This indicates a single excitation signal.

[0020] S3. Under the adaptive excitation configuration generated in step S2, through multi-configuration response acquisition, time-frequency-azimuth multi-dimensional fingerprint construction, sparse decoupling, and normalization processing, a high-resolution, multi-dimensional distinguishable fingerprint field is formed in the well-circumferential space. This provides fine constraints for full-well-circumferential electromagnetic imaging, enhances the response recognizability and imaging accuracy of low-resolution areas, and its specific implementation process is as follows: S31. The adaptive excitation signal generated in step S2 is applied sequentially to the wellbore space. The time response at each spatial location is collected through a wellbore wall or well fluid sensor array to form raw response data containing time, azimuth, and phase information. Simultaneously, considering the heterogeneity of the medium and the influence of noise, the data is ensured to be authentic and reliable, providing a foundation for fingerprint construction. Specifically: The adaptive excitation configuration generated in step S2 Launched sequentially into the perimeter space of the well; For each spatial location x, an intelligent multi-directional sensor array installed in the wellbore or well fluid is used to collect electromagnetic responses. Each sensor node in the array has embedded signal processing capabilities, which can perform local noise suppression, baseline calibration and preliminary impulse response extraction at the acquisition end, and upload the pre-processed feature stream in real time, thereby improving data quality and system response speed (the intelligent multi-directional sensor array includes, but is not limited to: magnetoresistive sensors, induction coil sensors and embedded processing units, supporting online calibration, temperature compensation and protocol-based data output). The original response at each spatial location is denoted as: ; in, Indicates the k-th excitation, azimuth interval Under the given conditions, the original electromagnetic response time series collected at spatial location x; Indicates the spatial location x in orientation. The equivalent propagation transfer function under certain conditions comprehensively reflects factors such as the conductivity, permeability, well fluid properties, and structural boundaries of the medium. This represents the convolution operation; This represents the measurement noise term under the k-th excitation condition, which includes instrument noise, environmental electromagnetic interference, and random disturbance components; S32. Perform time-frequency analysis on the raw response data, and combine it with different excitation configurations and spatial orientation information to construct a multidimensional response fingerprint vector. Quantify the instantaneous frequency, amplitude, and orientation characteristics of each spatial location under multi-configuration excitation to achieve differentiated expression of responses in low-resolution regions. Specifically: Time-frequency analysis was performed on the raw response at each spatial location x to extract instantaneous frequency and amplitude distribution characteristics; The responses to different excitation configurations and orientations are merged to form a multidimensional fingerprint vector: ; in, This represents a time-frequency feature extraction operator, used to convert the time-domain response into a feature representation containing spectrum, energy distribution, or instantaneous frequency information; The original multidimensional electromagnetic response fingerprint vector representing spatial location x is composed of multiple excitation configurations and features under orientation. S33. Spatial decoupling is performed on multidimensional response fingerprints. By constructing a fingerprint matrix and using a sparse projection operator to remove the linear correlation of neighboring units, the fingerprint discrimination of low-discriminability regions is improved, while retaining orientation and temporal information, forming independent and spatially distinguishable response fingerprints. This provides clear, multidimensional features for imaging constraints and anomaly detection. Specifically: The multidimensional fingerprint vector of N sampling spatial units around the well Combined into a matrix: ; For each spatial unit Calculate its similarity to other units and construct a spatial interference constraint matrix. : ; For each unit Solving for the optimal sparse projection coefficients : ; Calculate the decoupled fingerprint: ; Decoupled fingerprints Add spatial resolution enhancement weights: ; Output Enhanced Decoupled Fingerprint Set ; Where N represents the total number of wellbore space sampling units; This represents the entire wellbore spatial fingerprint set, used for global decoupling and adjacent interference analysis; The fingerprint similarity function for spatial units can be represented by cosine similarity or normalized correlation coefficient; Description unit The interference intensity with other units is used for sparse decoupling projection; Represents the sparse projection coefficients, characterizing the relationship between other elements and the target elements. Interference contribution; This represents the regularization coefficient, which controls sparsity, prevents overfitting, and ensures that features are preserved in low-resolution regions. This represents the decoupled fingerprint vector, where spatial interference is minimized. This represents the final enhanced decoupled fingerprint; This represents the adjustment coefficient, which controls the magnitude of spatial resolution enhancement; S34. The decoupled multidimensional response fingerprint is normalized to eliminate amplitude differences between different excitation configurations, generating a spatial fingerprint field with uniform dimensions while preserving distinguishable weight information. The output serves as the constraint input for subsequent full-well-circumference electromagnetic imaging and anomaly prediction algorithms, achieving a closed loop from excitation-driven to imaging constraint, ensuring imaging accuracy and reliability. The decoupled fingerprints are then normalized: ; in, This represents the final spatial fingerprint vector after normalization. Indicates fingerprint after decoupling The statistical mean is used to eliminate bias differences between different spatial units; This represents the statistical standard deviation of the decoupled fingerprint, used to unify the scale range of different spatial units.

[0021] S4. Using the decoupled normalized well-peripheral electromagnetic response fingerprint field output in step S3 as the core mediating variable, a spatial fingerprint consistency relationship is constructed to implicitly map the well-peripheral medium structure into a spatial evolution process of fingerprint similarity. Under the combined effect of consistency propagation and anomaly constraints, a stable and interpretable full-well-peripheral electromagnetic imaging result is formed, and the imaging reliability is given simultaneously, realizing high-resolution imaging and reliable anomaly identification in complex well-peripheral environments. The specific implementation process is as follows: S41. Based on the spatial fingerprint field obtained in step S3, a fingerprint consistency kernel reflecting the similarity of electromagnetic responses between arbitrary well perimeter spatial units is constructed. By quantifying the intensity of fingerprint differences, the continuity and abrupt changes of the subsurface structure are characterized, providing a data-driven association basis for subsequent spatial structure propagation. Define a spatial consistency kernel, and quantify the electromagnetic structural similarity between any two points by constructing a spatial fingerprint consistency kernel function: ; in, Indicates spatial location and The electromagnetic structure consistency value between the two positions is a core value; the larger the value, the more similar the two positions are in terms of electromagnetic structure. It represents a measure of the difference in fingerprint vectors between two spatial locations, reflecting the degree of similarity or difference in their electromagnetic response structures; The fingerprint scale parameter is used to normalize and control fingerprint differences. Its value is derived from the statistical characteristics of downhole measured noise, the number of excitation configurations, and the fingerprint dimension. S42. Using the fingerprint consistency kernel as the weight, an iterative propagation model for the well-circumferential spatial structure is established, allowing structural information to naturally expand in high-consistency regions and automatically suppress in low-consistency regions. This results in a continuous and clearly defined well-circumferential electromagnetic structure distribution without the need for traditional regularization. Specifically: First, the wellbore space is discretized into several spatial units. Based on the wellbore diameter, sampling interval, and tool layout, a finite neighborhood propagation graph structure is constructed. For any spatial unit... Its propagation neighborhood is defined as: ; Based on the consistency kernel, a structure propagation field is defined, and a direction adjustment factor is introduced. A fingerprint structure propagation model is constructed to allow spatial structure information to diffuse naturally in regions of high consistency and be automatically blocked in regions of low consistency, thereby forming a clear structural boundary. ; ; in, Represents a spatial distance function; The neighborhood radius is determined by the well diameter, well wall thickness, and measurement point density, ensuring that propagation only occurs within the physically accessible range. Indicates directional weight; and This indicates the azimuth angle around the well corresponding to the spatial unit; The direction sensitivity coefficient is estimated from the degree of well perimeter anisotropy. and These represent the spatial structure propagation field states at the t-th and t+1-th iterations, respectively; Represents the propagation field of the well perimeter spatial structure. It is an intermediate state variable in the imaging process, used to carry and transmit well perimeter structural information. Its numerical evolution reflects the process of the well perimeter electromagnetic structure gradually forming an overall image from local consistency. Indicates spatial location The neighborhood set; It should be noted that the propagation process does not continue indefinitely, but terminates automatically based on the following criteria: , The convergence threshold is determined jointly by the system noise lower limit and spatial resolution. Once propagation stabilizes, This forms a continuous field of spatial structure around the well; It is necessary to further explain the initial well-circumferential spatial structure propagation field. Assuming it is a constant field, it represents that no bias assumptions are made about the well perimeter structure, and the structural morphology is completely determined by subsequent uniform propagation; S43. By introducing local fingerprint deviation as an anomaly constraint factor, anomalies, cracks, or abrupt change regions are directly embedded into the imaging evolution process. This enhances and preserves the anomalous regions while maintaining the stable propagation of the overall structure. Specifically: Define the degree of abnormal deviation: ; And construct the anomaly weight function: ; Introducing it into the propagation model: ; in, The mean value of the fingerprint vector in the neighborhood of spatial location x is used to characterize the typical electromagnetic response characteristics of the area around that location and is an important reference benchmark for judging local anomalies. The fingerprint deviation at spatial location x represents the intensity of the difference between the fingerprint at that location and the average fingerprint of its neighborhood, and is used to quantify whether there is an electromagnetic structural anomaly or abrupt change at that location. This represents the anomaly enhancement coefficient, which is used to adjust the influence weight of anomalous fingerprints during the imaging evolution process. Its value is set according to the degree of engineering concern, risk level, or anomaly recognition sensitivity requirements. An anomaly weighting factor representing spatial location x is used to enhance or protect anomalous regions during structural propagation, preventing anomalous features from being overly smoothed during propagation. S44. After the propagation process converges, the well-circumferential structural field is normalized to form the final electromagnetic imaging result. Simultaneously, the imaging reliability distribution is calculated based on spatial fingerprint stability, ensuring that the imaging results are not only clearly visualized but also possess engineering interpretability and decision-making reference value. Specifically: Define the final imaging result: ; And define credibility metrics: ; Output a full-well continuous imaging map, anomaly area annotations, and a confidence distribution map for risk assessment and interpretation; in, This represents the final output value of the well-circumferential full-resolution electromagnetic imaging result. This value has been normalized and is used to intuitively characterize the relative distribution of electromagnetic structures in the well-circumferential space. It can be directly used for imaging display and interpretation. and These represent the minimum and maximum values ​​of the spatial structure propagation field in the convergent state, respectively, used to normalize the imaging results and ensure the comparability of imaging results under different well sections or different working conditions; T represents the final convergence iteration number of the structure propagation process. The imaging confidence index represents the spatial location x, which is used to quantify the stability and reliability of the imaging results at that location. The higher the value, the less affected the imaging in that area is by noise and uncertainty. This represents the number of neighboring units at spatial location x, used to average the differences in neighboring fingerprints and avoid bias in confidence calculation due to different neighborhood sizes.

[0022] Example 2, as Figure 2 As shown, the present invention proposes a well-circumferential full-resolution electromagnetic imaging system, which is used to execute a well-circumferential full-resolution electromagnetic imaging method proposed in Embodiment 1. It includes: a well-circumferential electromagnetic acquisition and environmental perception module, a multi-configuration excitation and spatial fingerprint construction module, a spatial fingerprint consistency evolution and anomaly enhancement module, and a well-circumferential imaging output and credibility assessment module.

[0023] The wellbore electromagnetic acquisition and environmental sensing module is used to achieve in-situ identification of electromagnetic propagation status and preliminary spatial information acquisition downhole. It emits adaptive electromagnetic signals into the wellbore space through a multi-directional, adjustable excitation source, and combines it with an intelligent multi-directional sensor array in the wellbore wall or well fluid to acquire response data in real time. This array integrates a high-sensitivity magnetoelectric sensing unit, a microprocessor, and an adaptive filtering algorithm, which can realize acquisition and preprocessing, self-identification of environmental noise, and self-diagnosis of sensor health status. It outputs a high signal-to-noise ratio and high-reliability characteristic data stream. By dynamically scanning the wellbore environment, it generates high-resolution, spatiotemporally aligned initial electromagnetic response information. At the same time, it identifies the heterogeneity and noise characteristics of the wellbore medium, providing accurate raw data and spatial constraint information for subsequent fingerprint construction. The multi-configuration excitation and spatial fingerprint construction module processes the collected raw response data, extracts the multi-dimensional electromagnetic response characteristics of each spatial location through multi-configuration electromagnetic excitation combination and time-frequency analysis methods, and forms a normalized and decoupled spatial fingerprint vector. The spatial fingerprint consistency evolution and anomaly enhancement module establishes a spatial consistency kernel based on the normalized spatial fingerprint vector. This kernel is used to quantify the electromagnetic structural similarity between any spatial units. The structural information is then diffused in the high consistency region through an iterative propagation algorithm. At the same time, a boundary is formed in the weak consistency region. Anomaly fingerprint deviation constraint is introduced to enhance and preserve local anomaly features, so that weak cracks or local anomalies are not smoothed during the propagation process. The whole-well-circumference imaging output and reliability assessment module normalizes the evolved spatial structure field to generate a continuous electromagnetic imaging map of the whole well-circumference. At the same time, it calculates the imaging reliability index of each spatial unit to quantify the stability and reliability of the imaging results, intuitively marks abnormal areas, and outputs spatial structure information that can be used as a reference for engineering decisions.

[0024] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A well-wide resolution electromagnetic imaging method, characterized in that, The specific implementation steps include the following: S1. By applying low-intrusion transient electromagnetic excitation in the well, the formation response around the well is obtained, the propagation state parameters are extracted, the electromagnetic distinguishability index is calculated, and a spatially distinguishable distribution around the well is formed. S2. Based on the spatial distinguishability distribution around the well, a spatial excitation demand function is generated by mapping, and then the time parameter, frequency parameter and phase parameter of the electromagnetic excitation signal in different azimuth intervals are adaptively adjusted to generate an adaptive electromagnetic excitation configuration set containing multiple excitations. S3. Under the action of the adaptive electromagnetic excitation configuration set, the electromagnetic response around the well of multiple configurations is collected. Time-frequency analysis is performed on the response at each spatial location to construct a multidimensional response fingerprint vector. The multidimensional response fingerprint vector is then subjected to spatial sparse decoupling and normalization to form a decoupled and normalized well-around electromagnetic response fingerprint field. S4. Based on the well-circumferential electromagnetic response fingerprint field, a spatial fingerprint consistency kernel is constructed. The structural information is diffused in the high consistency region and suppressed in the low consistency region through an iterative propagation model. At the same time, the local fingerprint deviation is introduced as an anomaly constraint factor to enhance the features of the anomaly region. Finally, the whole-well-circumferential electromagnetic imaging results and the corresponding imaging confidence distribution are evolved and output.

2. The well-circumference full-resolution electromagnetic imaging method according to claim 1, characterized in that, In step S1, the extraction of propagation state parameters specifically involves extracting the equivalent propagation delay factor, equivalent energy attenuation coefficient, response diffusion factor, and direction consistency factor from the electromagnetic response signals at each receiving direction. The equivalent propagation delay factor is used to describe the time delay of electromagnetic disturbance propagation to the main response region; The equivalent energy attenuation coefficient is obtained by fitting the attenuation characteristics of the response signal amplitude over time. The response diffusion factor is used to characterize the expansion width of the electromagnetic response in the time domain; The directional consistency factor is used to describe the similarity between the directional response pattern and the adjacent directional response patterns.

3. The well-circumference full-resolution electromagnetic imaging method according to claim 2, characterized in that, In step S2, the mapping to generate the spatial excitation demand function is specifically as follows: The distinguishability value of each location in the spatial distinguishability distribution around the well is converted into the required excitation demand intensity at that location through an inverse proportional mapping relationship. The value is then weighted by a spatial weighting function determined by well section geometry and well fluid distribution factors to form a quantified spatial excitation demand distribution.

4. The well-circumference full-resolution electromagnetic imaging method according to claim 3, characterized in that, In step S2, the adaptive adjustment of the time and frequency parameters of the electromagnetic excitation signal is specifically as follows: Based on the spatial excitation demand function, the decay time constant of each excitation signal is dynamically adjusted, and the excitation angular frequency of the excitation signal is adjusted synchronously, so that the excitation in the low resolution region has more sufficient time domain broadening and appropriate frequency domain offset.

5. The well-circumference full-resolution electromagnetic imaging method according to claim 4, characterized in that, In step S2, the phase setting for different azimuth intervals is specifically as follows: The wellbore space is divided into several intervals along the azimuth. The average value of the excitation demand intensity of all spatial units in each azimuth interval is calculated as the comprehensive excitation demand weight of that interval. Based on this weight, different phase offset values ​​are assigned to excitation signals of different orders in each azimuth interval, thereby forming a controllable phase difference in the azimuth dimension.

6. The well-circumference full-resolution electromagnetic imaging method according to claim 5, characterized in that, In step S3, the construction of the multidimensional response fingerprint vector is specifically as follows: For each spatial location, the original electromagnetic response time series collected under each excitation configuration and each orientation is transformed by the time-frequency feature extraction operator to obtain a feature representation containing spectrum, energy distribution or instantaneous frequency information. The feature representations of the spatial location under all excitation configurations and all orientations are combined to form a multidimensional response fingerprint vector of the spatial location.

7. The well-circumference full-resolution electromagnetic imaging method according to claim 6, characterized in that, In step S3, the spatial sparse decoupling of the multidimensional response fingerprint vector is specifically performed as follows: The fingerprint vectors of all spatial units around the well are combined into a fingerprint matrix. For each target spatial unit, the similarity between its fingerprint vector and the fingerprint vectors of all other units is calculated to construct a spatial interference constraint matrix describing the interference intensity. A set of sparse projection coefficients is obtained by solving an optimization problem with regularization constraints. These coefficients are then used to linearly combine the fingerprint vectors of other units to approximate the fingerprint of the target unit. Subtract the approximation result from the original fingerprint vector of the target unit to obtain the fingerprint vector after decoupling with minimized interference.

8. The well-circumference full-resolution electromagnetic imaging method according to claim 7, characterized in that, In step S4, constructing the spatial fingerprint consistency kernel specifically involves: For any two spatial locations in the well perimeter space, calculate the difference measure between their corresponding decoupled normalized fingerprint vectors. Input this difference measure into a kernel function with the fingerprint scale parameter as the control factor. The output value of the kernel function is the consistency kernel value that characterizes the degree of electromagnetic structural similarity between the two points. The smaller the difference, the larger the consistency kernel value.

9. The well-circumference full-resolution electromagnetic imaging method according to claim 8, characterized in that, In step S4, the local fingerprint deviation is introduced as an anomaly constraint factor as follows: For each spatial location, the difference strength between its decoupled normalized fingerprint vector and the mean of the fingerprint vectors of all locations in its neighborhood is calculated to obtain the fingerprint deviation at that location. The fingerprint deviation is mapped to an anomaly weight factor through a non-linear function; During the iterative propagation process, the abnormal weight factor is used as an enhancement coefficient and applied to the structural propagation field at the corresponding position, thereby enhancing and preserving the fingerprint features at that position during the propagation process.

10. A well-circumference full-resolution electromagnetic imaging system, used to perform the well-circumference full-resolution electromagnetic imaging method according to any one of claims 1 to 9, characterized in that, include: The well perimeter electromagnetic acquisition and environmental sensing module is equipped with a downhole multi-directional adjustable excitation source and an integrated intelligent multi-directional sensor array. It is used to transmit adaptive electromagnetic signals to the well perimeter, synchronously acquire multi-directional electromagnetic responses, perform local noise suppression and signal preprocessing, and output a high signal-to-noise ratio initial electromagnetic response characteristic data stream. The multi-configuration excitation and spatial fingerprint construction module is connected to the well-circumferential electromagnetic acquisition and environmental perception module. It is used to receive the initial electromagnetic response feature data stream, implement the generation and control of the multi-configuration excitation strategy, and construct and output the decoupled and normalized well-circumferential spatial fingerprint field by performing time-frequency analysis, feature extraction, spatial sparse decoupling and normalization processing on the response data. The spatial fingerprint consistency evolution and anomaly enhancement module is connected to the multi-configuration excitation and spatial fingerprint construction module. It is used to receive the spatial fingerprint field, construct the spatial consistency kernel based on fingerprint similarity, run the iterative propagation algorithm to diffuse structural information in the high consistency region and use the anomaly weight factor to enhance the local anomaly features, and finally evolve to generate a stable well perimeter spatial structure field. The whole-well-circumference imaging output and credibility assessment module is connected to the spatial fingerprint consistency evolution and anomaly enhancement module. It is used to receive the spatial structure field, normalize it to generate a whole-well-circumference continuous electromagnetic imaging map, synchronously calculate the imaging credibility index of each spatial unit and mark the abnormal area, and output imaging results and credibility distribution map that can be used for engineering decision-making.

Images