Method for high frequency pressure identification of perforating cluster liquid entry
Patent Information
- Application Number
- CN202611262994.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-08-19
- Publication Date
- 2026-10-09
Smart Images
Figure CN122885472A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of hydraulic fracturing technology for oil and gas wells, and in particular to a method for identifying fluid entering perforation clusters using high-frequency pressure. Background Technology
[0002] In multi-cluster perforation fracturing, multiple perforation clusters share the same wellbore for fluid supply. However, the initiation pressure, extension pressure, near-wellbore friction, fracture network connectivity, and formation fluid absorption capacity of the fractures connected to each cluster are not the same. Even if the cluster spacing, number of perforations, and perforation diameter are the same, during operation, a few clusters may preferentially introduce fluid and continue to expand, some clusters may only introduce a small amount of fluid, and some clusters may introduce almost no fluid. This imbalance will cause fracturing fluid and proppant to concentrate in a few fractures, reducing the reservoir stimulation volume and increasing the uncertainty of subsequent temporary plugging, diversion, and parameter adjustments.
[0003] Conventional construction pressure curves primarily reflect the combined results of pump pressure, hydrostatic pressure, wellbore friction, perforation friction, and formation net pressure. While their low-frequency trends can characterize the overall operating conditions, they struggle to separate the local fluid inflow responses of adjacent perforation clusters. High-frequency pressure records also include pump surges, valve actions, electrical interference, sensor spikes, slow pressure drift, and superimposed reflections from multiple downhole interfaces. Directly comparing peak values, root mean square (RMS) values, or single-shot spectra can easily lead to misinterpreting equipment noise or occasional fluctuations as perforation cluster responses.
[0004] However, the existing technology has the following problem: without additional downhole flow meters, it is difficult to stably extract water hammer reflection characteristics corresponding to different perforation clusters from high-frequency pressure signals containing pumping disturbances, equipment noise and wellbore reflection components. Summary of the Invention
[0005] In view of this, the purpose of the present invention is to provide a method for identifying fluid injection into perforation clusters using high-frequency pressure, so as to alleviate the technical problem that it is difficult to stably extract water hammer reflection characteristics corresponding to different perforation clusters from high-frequency pressure signals containing pumping disturbances, equipment noise and wellbore reflection components without additional downhole flow meters.
[0006] In a first aspect, embodiments of this application provide a method for identifying liquid entering a perforation cluster using high-frequency pressure, the method comprising: Step S1: Collect the discrete pressure sequence of the target fracturing section, the bridge plug design depth measurement, the initial effective wave velocity, and the design depth measurement of multiple perforation clusters; Step S2: Preprocess the discrete pressure sequence to obtain a transient pressure sequence; perform windowing processing on the transient pressure sequence to obtain multiple analysis windows; perform cepstrum calculation on the multiple analysis windows to obtain the cepstrum of each analysis window. Step S3: Within each analysis window, the initial two-way travel time of the bridge plug is determined based on the bridge plug design depth sounding and the initial effective wave velocity. Within the wide search band of the initial two-way travel time of the bridge plug, analysis windows that meet the preset conditions for the proportion of bridge plug reflected energy are selected. The maximum cepstral peak is extracted within the local search range of the selected analysis windows to determine the measured two-way travel time of the bridge plug and the quality index of the bridge plug ridge. Step S4: Based on the measured two-way travel time of the bridge plug, the designed depth sounding of the bridge plug, and the designed depth sounding of the multiple perforation clusters, determine the predicted two-way travel time of each perforation cluster, and establish a dynamic search gate for each perforation cluster according to the predicted two-way travel time. Step S5: Based on the bridge plug ridge quality index, select qualified analysis windows from the multiple analysis windows, and extract the response score of each perforation cluster within the dynamic search gate of the qualified analysis window; Step S6: Determine the relative liquid inflow contribution of each perforation cluster based on the response score to complete the liquid inflow analysis of the perforation cluster.
[0007] In one implementation of the first aspect, the process of windowing the transient pressure sequence to obtain multiple analysis windows, and performing cepstrum calculation on the multiple analysis windows to obtain the cepstrum of each analysis window, includes: The transient pressure sequence is segmented according to the analysis window length and overlap rate. A window function is applied to each analysis window, and a Fourier transform is performed, resulting in the following expression: , in, For the first The preprocessed pressure sequence within each analysis window For frequency serial number, The number of points in the Fourier transform. The imaginary unit, This indicates the amplitude and phase of pressure fluctuations at different frequencies; The cepstrum is obtained by subtracting the smoothed spectral envelope from the analysis window after Fourier transform and then performing an inverse Fourier transform. , is represented as , , in, To remove the smoothed spectral envelope from the logarithmic amplitude spectrum, To prevent the smallest positive number from taking the logarithm of zero, For frequency domain smoothing operators, This is the inverse discrete Fourier transform. This is the inverted frequency index.
[0008] In one implementation of the first aspect, the determination of the initial two-way travel time of the bridge plug based on the bridge plug design depth sounding and the initial effective wave velocity is expressed as follows: , in, The initial two-way travel time for the bridge plug. Design depth measurement for bridge plugs, This represents the initial effective wave velocity.
[0009] In one implementation of the first aspect, the determination of the predicted two-way travel time of each perforation cluster based on the measured two-way travel time of the bridge plug, the designed depth sounding of the bridge plug, and the designed depth sounding of the multiple perforation clusters is expressed as follows: , in, To predict round-trip time, the bridge plug was used to measure the round-trip time. , Design depth measurement for bridge plugs, For the first A cluster of perforations is designed for depth measurement. The effective wave velocity used for the initial positioning of the bridge plug. For the first in this window Cluster prediction of two-way travel time.
[0010] In one implementation of the first aspect, the dynamic search gate for each perforation cluster is established based on the predicted two-way time, as expressed as: , in, For the first Dynamic search gate for a perforation cluster The half-width of the dynamic search gate.
[0011] In one implementation of the first aspect, the process of selecting qualified analysis windows from the plurality of analysis windows based on the bridge plug ridge quality index, and extracting the response score of each perforation cluster within the dynamic search gate of the qualified analysis windows, includes: Based on the bridge plug ridge quality index, analysis windows that meet the preset conditions for the proportion of bridge plug reflected energy and whose bridge plug peak prominence is greater than or equal to the preset prominence threshold are selected to obtain the qualified analysis windows. The response score for each perforation cluster is extracted within the dynamic search gate of the qualified analysis window, and the response score is expressed as follows: , in, The normalized intensity of the candidate peak relative to the local background. For the first The first qualified analysis window Normalized reflection energy of a dynamic search gate for a perforation cluster. The proportion of windows with qualified bridge plugs and valid candidate peaks within the perforation cluster to the total number of windows. The standard deviation of the time difference between the predicted time of the perforation cluster and the time of the candidate peak within the effective window. From the wellhead to the first Attenuation correction factor for the propagation distance of a perforation cluster. To allow for fluctuations in time deviation.
[0012] In one implementation of the first aspect, the process of determining the relative liquid ingress contribution of each perforation cluster based on the response score includes: The response score of each perforation cluster is normalized to obtain the relative liquid ingress contribution, expressed as: , in, For the first The relative liquid ingress contribution of each perforation cluster For the first j The response score of each perforation cluster.
[0013] In one implementation of the first aspect, the discrete pressure sequence of the target fracturing section is represented as follows: , in, For sampling sequence number, For the first Each sampling time, The sampling pressure value, Sampling frequency, It is the Nyquist frequency.
[0014] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.
[0015] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description
[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0017] Figure 1 A schematic flowchart of the high-frequency pressure identification method for liquid entry into perforated clusters provided in an embodiment of the present invention; Figure 2 This is a diagram showing the relationship between the impedance change of the perforation cluster branch and the water hammer wave reflection response provided in an embodiment of the present invention. Figure 3 A schematic diagram illustrating the single-window matching relationship between a fixed-time gate and a bridge plug ridge line correction dynamic gate provided in an embodiment of the present invention; Figure 4 This is a schematic diagram showing the correction and calculation comparison of the dynamic search gate for the bridge plug reflection ridge through-hole cluster provided in an embodiment of the present invention. Detailed Implementation
[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0019] Please see Figure 1 As shown, it is a flowchart illustrating the high-frequency pressure identification method for fluid injection into perforated clusters provided in an embodiment of the present invention.
[0020] To facilitate understanding of this embodiment, a method for identifying liquid entering a perforation cluster using high-frequency pressure, as disclosed in this embodiment of the invention, will first be described in detail, including: Step S1: Collect the discrete pressure sequence of the target fracturing section, the bridge plug design depth measurement, the initial effective wave velocity, and the design depth measurement of multiple perforation clusters; Step S2: Preprocess the discrete pressure sequence to obtain a transient pressure sequence; perform windowing processing on the transient pressure sequence to obtain multiple analysis windows; perform cepstrum calculation on the multiple analysis windows to obtain the cepstrum of each analysis window. Step S3: Within each analysis window, the initial two-way travel time of the bridge plug is determined based on the bridge plug design depth sounding and the initial effective wave velocity. Within the wide search band of the initial two-way travel time of the bridge plug, analysis windows that meet the preset conditions for the proportion of bridge plug reflected energy are selected. The maximum cepstral peak is extracted within the local search range of the selected analysis windows to determine the measured two-way travel time of the bridge plug and the quality index of the bridge plug ridge. Step S4: Based on the measured two-way travel time of the bridge plug, the designed depth sounding of the bridge plug, and the designed depth sounding of the multiple perforation clusters, determine the predicted two-way travel time of each perforation cluster, and establish a dynamic search gate for each perforation cluster according to the predicted two-way travel time. Step S5: Based on the bridge plug ridge quality index, select qualified analysis windows from the multiple analysis windows, and extract the response score of each perforation cluster within the dynamic search gate of the qualified analysis window; Step S6: Determine the relative liquid inflow contribution of each perforation cluster based on the response score to complete the liquid inflow analysis of the perforation cluster.
[0021] Specifically, this invention involves windowing the transient pressure sequence of the fracturing section and performing cepstral calculations. Within the initial two-way time wide search band, effective analysis windows are selected based on the proportion of reflected energy. The measured two-way time of the bridge plug and its ridge quality index are then determined through the local maximum cepstral peak. Using the measured two-way time of the bridge plug and the designed depth of each perforation cluster as benchmarks, the predicted two-way time of each perforation cluster is calculated and a dynamic search gate is established. Within the qualified windows selected by the ridge quality index, the response score of each perforation cluster is extracted. Finally, the relative contribution of each perforation cluster to fluid inflow is determined, and the two-way transmission is extracted using the cepstral domain. By analyzing time-dependent reflection components and combining them with bridge plug reflection ridges, the common downhole time offset and the relative position of perforation clusters can be correlated. A dynamic cluster position search gate constrained by bridge plug measured ridges, rather than a fixed time range throughout the entire construction period, can reduce the mismatch of fixed gate peak positions caused by changes in effective wave velocity and construction conditions, thereby improving the detection signal-to-noise ratio and positioning accuracy of weak reflection signals from perforation clusters. Cepstral analysis combined with ridge quality screening can suppress background interference and false peaks, thus stably extracting water hammer wave reflection features corresponding to different perforation clusters from high-frequency pressure signals.
[0022] Please see Figure 2 As shown, it is a graph showing the relationship between the impedance change of the perforation cluster branch and the water hammer wave reflection response provided in an embodiment of the present invention.
[0023] Specifically, the embodiments of the present invention are based on the principles of water hammer wave reflection and perforation cluster fluid response, and the main wellbore is equivalent to a characteristic impedance. , will the Each perforation cluster and its connecting cracks are equivalent to branch admittance. This is only used to describe the reflection changes caused by variations in branch fluid absorption capacity, pore friction, and fracture connectivity; it is not used to directly invert absolute fracture geometric parameters. The pressure reflection coefficient of this branch... Represented as: , in, This is the equivalent density of the fracturing fluid inside the wellbore. The effective propagation speed of pressure waves, The effective flow area of the main wellbore. Main wellbore characteristic impedance, For the first The equivalent branch admittance of a perforation cluster and its fracture system.
[0024] In this embodiment of the invention, when the opening degree of the perforation cluster, the perforation friction and the fluid absorption capacity of the fracture change, the equivalent branch admittance changes accordingly, thereby changing the amplitude, energy and stability of the reflected wave. Therefore, under the same fracturing section, similar excitation and the same acquisition link conditions, the relative fluid inflow response between clusters can be constructed by extracting the reflection response corresponding to each cluster position and performing propagation attenuation and quality correction.
[0025] Specifically, in this embodiment of the invention, a dedicated high-frequency pressure acquisition device is installed at the wellhead. For example, the fracturing operation pressure is continuously recorded at a sampling frequency of 860Hz, that is, 860 pressure measurement points are obtained per second, and the time interval between a single point is about 1.163ms. According to the sampling theorem, the highest frequency that can be analyzed without aliasing is 430Hz.
[0026] In this embodiment of the invention, the actual sampling frequency should be determined based on the highest effective frequency of the target reflection, the minimum resolvable two-way time difference between adjacent perforation clusters, and the continuous transmission capability of the collector.
[0027] Specifically, the discrete pressure sequence output by the data acquisition unit in this embodiment of the invention is represented as follows: , in, For sampling sequence number, For the first Each sampling time, The sampling pressure value, Sampling frequency, It is the Nyquist frequency.
[0028] In this embodiment of the invention, the high-frequency pressure at the wellhead is composed of low-frequency construction pressure, periodic fluctuations of the pumping system, water hammer waves in the wellbore, reflections from multiple downhole interfaces, and random noise.
[0029] Specifically, the embodiments of the present invention perform data processing, first removing sensor glitch and communication anomalies, and then removing low-frequency trends formed by slow changes in pump pressure, changes in wellbore friction, and changes in construction discharge.
[0030] In this embodiment of the invention, the preprocessed transient pressure sequence for: , in, and respectively with The local sliding median and absolute deviation of the median are centered on the value; These are the linear interpolation values of the two most recent valid sampling points before and after the outlier. This indicates a zero-phase bandpass filter. It is a slow-changing pressure trend.
[0031] In this embodiment of the invention, the slow-varying pressure trend is a least-squares linear or low-order polynomial.
[0032] In this embodiment of the invention, 4.5 It can suppress isolated sampling spikes while preserving as much of the true water hammer front as possible from multiple sampling points.
[0033] In this embodiment of the invention, the linear interpolation value is used when the number of consecutive outliers does not exceed 3 sampling points; if the number exceeds 3 sampling points, the corresponding analysis window is marked as invalid and will not be included in subsequent cepstral statistics.
[0034] In this embodiment of the invention, the lower passband is used to reduce the slow changes in construction pressure and the low-frequency changes in wellbore friction, while the upper passband is used to suppress high-frequency noise from the sensor. If there are stable power frequency or fixed frequency components of the pump group in the spectrum, a narrowband notch is set at the corresponding frequency. Specifically, a passband of 3 to 180 Hz is used, and notches are set at 50 Hz and 100 Hz. The actual passband is determined by verifying the construction spectrum and the pump pulse frequency.
[0035] Specifically, the embodiments of the present invention are based on a length of The analysis window is segmented, and adjacent windows are set to overlap.
[0036] In this embodiment of the invention, the initial length of the analysis window is set to 10s, the overlap rate of adjacent windows is 80%, and the window length is required to be no less than 3 times the two-way propagation time of the farthest target reflection position. When the discharge volume, liquid content, or sand concentration changes significantly, the analysis segment is re-divided.
[0037] Specifically, in this embodiment of the invention, the Hanning window function is used for each analysis window to reduce spectral leakage caused by truncation. Represented as: , in, The sampling sequence number within the window; Then for the first Performing a Discrete Fourier Transform on each analysis window, it can be represented as follows: , in, For the first The preprocessed pressure sequence within each analysis window For frequency serial number, The number of points in the Fourier transform. The imaginary unit, This indicates the amplitude and phase of pressure fluctuations at different frequencies during that period.
[0038] Understandably, Fourier spectra are used to check pump impulse frequency, power frequency interference, and effective frequency band of water hammer waves, but the spectrum itself only indicates which frequency components are present and cannot directly indicate which well depth the reflection originates from.
[0039] Specifically, in this embodiment of the invention, the round-trip time of reflection is extracted, the logarithm of the amplitude spectrum is taken to transform the product relationship between the incident wave and the reflection path in the frequency domain into an additive relationship; then the smoothed spectral envelope is subtracted and an inverse Fourier transform is performed to obtain the cepstrum. , represented as: , in, To remove the smoothed spectral envelope from the logarithmic amplitude spectrum, To prevent the smallest positive number from taking the logarithm of zero, For frequency domain smoothing operators, This is the inverse discrete Fourier transform. This is the inverted frequency index.
[0040] In this embodiment of the invention, the cepstral abscissa After conversion to second or millisecond sampling intervals, this represents the two-way propagation time of the pressure wave from the wellhead to the downhole reflection location and back to the wellhead. Subtracting the smoothed spectral envelope effectively reduces the influence of the wellhead excitation source and the acquisition system on the overall shape of the spectrum, thus minimizing the impact of the reflection components with repeating echo intervals on the overall spectrum. A clear peak is formed at that point.
[0041] Specifically, this invention segments the transient pressure sequence according to an overlap analysis window and applies a Hanning window. It then performs a Fourier transform window by window, takes the logarithmic amplitude spectrum, subtracts the smoothed spectral envelope, and performs an inverse transform to obtain a cepstrum with the two-way propagation time as the abscissa. High-frequency sampling combined with bandpass and notch filtering preserves the true water hammer wave front while suppressing pump power frequency interference and random noise. The cepstrum transform converts the influence of the wellhead on the overall shape of the spectrum into a subtractable, slowly varying envelope, so that the reflection of the downhole interface with repeated echo intervals forms a clear peak in the cepstrum domain. This allows for the stable extraction of water hammer wave reflection features corresponding to different perforation clusters from the high-frequency pressure signal.
[0042] Specifically, in each analysis window of this invention, the depth measurement is first performed based on the bridge plug design. and initial effective wave velocity Calculate the initial two-way travel time of the bridge plug , represented as: .
[0043] Specifically, the embodiments of the present invention are in The bridge plug reflection energy percentage is calculated within a wide search band of ±250ms. Only the bridge plug search band energy percentage is retained under the preset condition, i.e., the first 70% of the analysis window. Within the retained analysis window, the maximum cepstrum peak is extracted within a local range of ±60ms based on the bridge plug time center of the previous effective window to obtain the bridge plug ridge quality index.
[0044] In this embodiment of the invention, when the prominence of the candidate peak relative to the local background is not less than 1.5, it is recorded as the measured two-way travel time of the bridge plug in that window. .
[0045] In this embodiment of the invention, the above parameters are the default configuration of the existing program: ±250ms is used to accommodate the design wave velocity and depth measurement error, ±60ms is used to limit the local peak jump within adjacent windows, prominence 1.5 is used to exclude weak peaks that are not clearly distinguishable from the local background, the first 70% energy window is used to eliminate the period when the bridge plug reflection energy is insufficient, and the actual well section can be adjusted according to the bridge plug peak width and data quality while maintaining the same physical meaning.
[0046] Please see Figure 3 and Figure 4 As shown, these are schematic diagrams of the single-window matching relationship between the fixed-time gate and the bridge plug ridge line correction dynamic gate provided in the embodiments of the present invention, and schematic diagrams of the correction and calculation comparison of the bridge plug reflection ridge line through-hole cluster dynamic search gate.
[0047] Figure 3 In the process, the center of the bridge plug ridge line is updated according to "65% of the new peak value and 35% of the previous center value", so that short-term abnormal peaks do not directly change the local search center of the next window. When it is known that the bridge plug reflection should not arrive early, the early jump tolerance can be set to 50ms, and the window exceeding the tolerance does not participate in the trajectory update.
[0048] Figure 4 In the test, the half-width of the time gate was 7ms. The evaluation indicators were the proportion of the target reflection falling into the time gate, the median deviation from the gate center to the target reflection, and the 90th percentile deviation. The target reflection capture rate of the fixed gate was 0.35, the median gate center deviation was 10.81ms, and the 90th percentile deviation was 15.63ms. The target reflection capture rate of the dynamic gate was 1.00, and the gate center deviation was 0ms.
[0049] Specifically, in this embodiment of the invention, the measured two-way travel time of the bridge plug is determined based on the designed depth difference between the bridge plug and each perforation cluster. Converted to predicted two-way travel time, it is expressed as: , in, Design depth measurement for bridge plugs, For the first A cluster of perforations is designed for depth measurement. The effective wave velocity used for the initial positioning of the bridge plug. For the first in this window Cluster prediction of two-way travel time.
[0050] Specifically, embodiments of the present invention establish a dynamic search gate based on the predicted two-way travel time, as follows: , in, For the first Dynamic search gate for perforation clusters The half-width of the dynamic search gate.
[0051] In this embodiment of the invention, the dynamic search gate half-width The half-width is determined by the local bridge plug peak width, cepstrum sampling interval, perforation cluster depth sounding error, and adjacent cluster time interval. The half-width should not exceed half of the prediction time interval of adjacent clusters to avoid a dynamic search gate covering the main peak region of adjacent clusters.
[0052] Specifically, this invention first calculates the initial two-way travel time of the bridge plug based on the designed depth and initial effective wave velocity within each analysis window. Based on the measured two-way travel time of the bridge plug and the difference between the designed depth of each perforation cluster, the reflection time of the bridge plug is converted into the predicted two-way travel time of each cluster. A dynamic search gate is then established, and the dynamic correction of the bridge plug ridge line allows the search gate to adaptively adjust according to the window-by-window changes in the actual wellbore wave velocity and time-depth relationship. This overcomes the positioning drift caused by wave velocity error and depth deviation due to the fixed time gate. Energy ratio pre-screening and local ridge line tracking ensure the stability and reliability of the bridge plug reference peak, improve the resolution of perforation cluster response detection and the accuracy of fluid contribution analysis, thereby stably extracting the water hammer wave reflection characteristics corresponding to different perforation clusters from the high-frequency pressure signal.
[0053] Specifically, the embodiments of the present invention address the first... The first perforation cluster, the first In each analysis period, only when the proportion of bridge plug reflected energy meets the preset conditions, and the bridge plug peak prominence is not lower than a preset prominence threshold of 1.5 and the bridge plug two-way time is valid, is a qualified analysis window obtained, and a dynamic search gate is used. Internal reading of cluster-level cepstral response.
[0054] Specifically, in this embodiment of the invention, the relative intensity of the peak value is obtained by subtracting the local background median within the gate from the candidate peak and then dividing by the absolute deviation of the local median. Simultaneously calculate the proportion of reflected energy inside the door. and candidate peak and Time deviation.
[0055] In this embodiment of the invention, windows with substandard bridge plug quality are directly rejected and not included in the perforation cluster response statistics.
[0056] Specifically, this invention extracts a qualified analysis window and reads the cepstral response of the perforation cluster within the dynamic search gate of the qualified window. Based on the quality gating of the bridge plug ridge, it eliminates interference periods with weak reflection energy, unreliable reference peaks, or bridge plug positioning failure, ensuring that the perforation cluster response is read only within the high confidence window. The three-dimensional joint characterization of peak intensity, energy ratio, and time deviation makes the perforation cluster response not only dependent on peak height, but also takes into account energy concentration and time depth consistency, suppressing the misleading judgment of the contribution of local background fluctuations and random false peaks to the liquid inflow. The local background normalization processing within the dynamic search gate enhances the detectability of weak response clusters under strong background noise, thereby stably extracting the water hammer reflection characteristics corresponding to different perforation clusters from the high-frequency pressure signal.
[0057] Specifically, embodiments of the present invention determine the first based on the peak relative intensity and time deviation. Response score of a perforation cluster , represented as: , in, The normalized intensity of the candidate peak relative to the local background. For the first The first qualified analysis window Normalized reflection energy of a dynamic search gate for a perforation cluster. The proportion of windows with qualified bridge plugs and valid candidate peaks within the perforation cluster to the total number of windows. The standard deviation of the time difference between the predicted time of the perforation cluster and the time of the candidate peak within the effective window. From the wellhead to the first Attenuation correction factor for the propagation distance of a perforation cluster. To allow for fluctuations in time deviation.
[0058] In this embodiment of the invention, the standardization intensity Not less than 3.0, normalized reflected energy Not less than 0.10; allowable time deviation fluctuations. The initial value is 5.0 ms, which can be corrected by the time dispersion of the bridge plug ridge line in the stable construction section.
[0059] Specifically, this invention overcomes the defect of single peak height being susceptible to noise interference by constructing response scores for perforation clusters and integrating multi-dimensional evaluations of comprehensive intensity, energy, and temporal consistency. Propagation distance attenuation correction makes the responses of near and far perforation clusters comparable, avoiding the systematic underestimation of distant clusters due to signal attenuation. The effective window ratio and time deviation fluctuation are jointly constrained, which can stably screen true reflection signals and suppress occasional false peaks, thereby stably extracting water hammer wave reflection features corresponding to different perforation clusters from high-frequency pressure signals.
[0060] Specifically, in this embodiment of the invention, the response score of each perforation cluster is normalized according to the following formula to obtain the relative liquid inflow contribution, expressed as: , in, Indicates the first The relative fluid inflow contribution of each perforation cluster within this fracturing section. For the first j The response score of each perforation cluster.
[0061] In this embodiment of the invention, perforation clusters are divided into dominant fluid inflow clusters, secondary fluid inflow clusters, effective fluid inflow clusters, and weak fluid inflow clusters based on the interpreted well sections in the same block and comparative monitoring data.
[0062] In this embodiment of the invention, perforation clusters with insufficient effective time period ratios or excessive two-way time dispersion are not included in the strength ranking, and the results are marked as requiring verification.
[0063] Specifically, in this embodiment of the invention, the measured two-way time trajectory of the bridge plug, the dynamic search gate of each cluster, the relative fluid inflow contribution, and the results to be verified are output according to the perforation cluster depth or cluster sequence, which are used to evaluate the degree of fluid inflow balance between clusters in this fracturing section.
[0064] In this embodiment of the invention, when the width of the reflection peak exceeds the preset range, or when a high-energy response without a clear peak appears simultaneously in the dynamic search gate of multiple adjacent perforation clusters, the "wideband high energy, insufficient cluster position resolution" flag is output, and the corresponding result is marked as needing to be reviewed, so as to avoid mistaking the broadband pressure impact as a reflection of a certain perforation cluster.
[0065] Specifically, this invention normalizes the response scores of each perforation cluster into relative liquid inflow contribution, marks clusters with insufficient effective time period ratios or excessive two-way time discrepancies as requiring verification, and outputs the measured two-way time trajectory of the bridge plug, dynamic search gate, and contribution results. The verification marking prevents the misjudgment of broadband pressure shocks as single-cluster reflections and avoids incorrect inter-cluster liquid inflow conclusions due to false peak interference. This allows the cluster-level interpretation results to be traced back to the corresponding bridge plug reflection and analysis window, thereby improving the reliability of perforation cluster liquid inflow analysis and the accuracy of on-site decision-making. In this way, the water hammer wave reflection characteristics corresponding to different perforation clusters can be stably extracted from high-frequency pressure signals.
[0066] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present application should be included within the scope of protection of the present application.
Claims
1. A method for identifying liquid ingress into perforation clusters using high-frequency pressure, characterized in that, include: Step S1: Collect the discrete pressure sequence of the target fracturing section, the bridge plug design depth measurement, the initial effective wave velocity, and the design depth measurement of multiple perforation clusters; Step S2: Preprocess the discrete pressure sequence to obtain a transient pressure sequence; perform windowing processing on the transient pressure sequence to obtain multiple analysis windows; perform cepstrum calculation on the multiple analysis windows to obtain the cepstrum of each analysis window. Step S3: Within each analysis window, the initial two-way travel time of the bridge plug is determined based on the bridge plug design depth sounding and the initial effective wave velocity. Within the wide search band of the initial two-way travel time of the bridge plug, analysis windows that meet the preset conditions for the proportion of bridge plug reflected energy are selected. The maximum cepstral peak is extracted within the local search range of the selected analysis windows to determine the measured two-way travel time of the bridge plug and the quality index of the bridge plug ridge. Step S4: Based on the measured two-way travel time of the bridge plug, the designed depth sounding of the bridge plug, and the designed depth sounding of the multiple perforation clusters, determine the predicted two-way travel time of each perforation cluster, and establish a dynamic search gate for each perforation cluster according to the predicted two-way travel time. Step S5: Based on the bridge plug ridge quality index, select qualified analysis windows from the multiple analysis windows, and extract the response score of each perforation cluster within the dynamic search gate of the qualified analysis window; Step S6: Determine the relative liquid inflow contribution of each perforation cluster based on the response score to complete the liquid inflow analysis of the perforation cluster.
2. The method for identifying liquid entry into perforation clusters using high-frequency pressure identification according to claim 1, characterized in that, The process of windowing the transient pressure sequence to obtain multiple analysis windows, and then performing cepstrum calculation on the multiple analysis windows to obtain the cepstrum of each analysis window, includes: The transient pressure sequence is segmented according to the analysis window length and overlap rate. A window function is applied to each analysis window, and a Fourier transform is performed, resulting in the following expression: ， in, For the first The preprocessed pressure sequence within each analysis window For frequency serial number, The number of points in the Fourier transform. The imaginary unit, This indicates the amplitude and phase of pressure fluctuations at different frequencies; The cepstrum is obtained by subtracting the smoothed spectral envelope from the analysis window after Fourier transform and then performing an inverse Fourier transform. , is represented as , ， in, To remove the smoothed spectral envelope from the logarithmic amplitude spectrum, To prevent the smallest positive number from taking the logarithm of zero, For frequency domain smoothing operators, This is the inverse discrete Fourier transform. This is the inverted frequency index.
3. The method for identifying liquid entry into perforation clusters using high-frequency pressure identification according to claim 1, characterized in that, The determination of the initial two-way travel time of the bridge plug based on the bridge plug design depth sounding and the initial effective wave velocity is expressed as follows: ， in, The initial two-way travel time for the bridge plug. Design depth measurement for bridge plugs, This represents the initial effective wave velocity.
4. The method for identifying liquid entry into perforation clusters using high-frequency pressure identification according to claim 1, characterized in that, The method for determining the predicted two-way travel time of each perforation cluster based on the measured two-way travel time of the bridge plug, the designed depth sounding of the bridge plug, and the designed depth sounding of the multiple perforation clusters is expressed as follows: ， in, To predict round-trip time, the bridge plug was used to measure the round-trip time. , Design depth measurement for bridge plugs, For the first A cluster of perforations is designed for depth measurement. The effective wave velocity used for the initial positioning of the bridge plug For the first in this window Cluster prediction of two-way travel time.
5. The method for identifying liquid entry into perforation clusters using high-frequency pressure according to claim 1, characterized in that, The dynamic search gate for each perforation cluster, established based on the predicted two-way time, is expressed as: ， in, For the first Dynamic search gate for a perforation cluster The half-width of the dynamic search gate.
6. The method for identifying liquid entry into perforation clusters using high-frequency pressure according to claim 1, characterized in that, The process of selecting qualified analysis windows from the plurality of analysis windows based on the bridge plug ridge quality index, and extracting the response score of each perforation cluster within the dynamic search gate of the qualified analysis window, includes: Based on the bridge plug ridge quality index, analysis windows that meet the preset conditions for the proportion of bridge plug reflected energy and whose bridge plug peak prominence is greater than or equal to the preset prominence threshold are selected to obtain the qualified analysis windows. The response score for each perforation cluster is extracted within the dynamic search gate of the qualified analysis window, and the response score is expressed as follows: ， in, The normalized intensity of the candidate peak relative to the local background. For the first The first qualified analysis window Normalized reflection energy of a dynamic search gate for a perforation cluster. The proportion of windows with qualified bridge plugs and valid candidate peaks within the perforation cluster to the total number of windows. The standard deviation of the time difference between the predicted time of the perforation cluster and the time of the candidate peak within the effective window. From the wellhead to the first Attenuation correction factor for the propagation distance of a perforation cluster. To allow for fluctuations in time deviation.
7. The method for identifying liquid entry into perforation clusters using high-frequency pressure identification according to claim 1, characterized in that, The process of determining the relative liquid ingress contribution of each perforation cluster based on the response score includes: The response score of each perforation cluster is normalized to obtain the relative liquid ingress contribution, expressed as: ， in, For the first The relative liquid ingress contribution of each perforation cluster For the first j The response score of each perforation cluster.
8. The method for identifying liquid entry into perforation clusters using high-frequency pressure according to claim 1, characterized in that, The discrete pressure sequence of the target fracturing section is represented as follows: ， in, For sampling sequence number, For the first Each sampling time, The sampling pressure value, Sampling frequency, It is the Nyquist frequency.