Undrilled formation velocity prediction method, system and product based on VSP longitudinal and transverse waves

Abstract

The invention discloses an undrilled formation velocity prediction method, system and product based on VSP longitudinal and transverse waves, the method is excited through VSP longitudinal and transverse wave double seismic sources and directly receives downlink waves and uplink waves through a detector arranged in a well, a high-resolution time-depth relation and interval velocity information can be obtained, the high-resolution time-depth relation and interval velocity information comprise underground deep-layer fidelity high-resolution reflection characteristics, and the high-resolution time-depth relation and the interval velocity information can be used for predicting the velocity of an undrilled formation. A reliable starting point is provided for speed prediction below the shaft bottom; secondly, according to the corresponding rule of the speed change and the high-resolution longitudinal and transverse wave data reflection characteristics, the relation between the reflection characteristics and the speed change is established, the speed of the underground undrilled formation is finely predicted through a joint inversion means, a more real and reliable data basis is provided for research of underground exploration and development and the like, and the method is suitable for popularization and application. The exploration and development risk and the drilling cost are greatly reduced.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of geophysical exploration, and particularly relates to a method, system and product for predicting the velocity of un-drilled strata based on VSP P-S waves. BACKGROUND

[0002] With the continuous expansion of oil and gas exploration to the "double complexity" (complex structure, complex lithology), deep-ultra deep and unconventional fields, the requirement for the prediction accuracy of the velocity of un-drilled strata is increasing. The prediction of the velocity of un-drilled strata is a key technical link in drilling engineering, and is directly related to drilling safety, cost control and exploration success rate. The traditional prediction method based on seismic data has problems such as imperfect theoretical basis, limited prediction accuracy and strong multi-solution property. Ground seismic data (such as stacked velocity analysis) can only provide a large-scale average velocity model, and it is difficult to accurately reflect the velocity details of the strata near the wellbore and deep strata, especially in complex structure (such as salt dome, fault) areas, the error is large; in particular, in complex geological conditions such as the overpressure mudstone section of the Bohai Bay Basin, due to the lack of velocity data from adjacent wells for reference, the use of velocity body data to predict the velocity of un-drilled strata often has large errors; logging data (such as sonic logging, density logging) only cover the drilled well section, and oil and gas reservoir evaluation and drilling engineering (such as ultra-deep well design, fracturing scheme) urgently need to predict the velocity structure of un-drilled strata (below the well bottom) to reduce exploration risks. SUMMARY

[0003] In view of the problem that the existing technology cannot accurately predict the velocity of un-drilled strata below the well bottom in the current oil and gas exploration and development, the application provides a method, system and product for predicting the velocity of un-drilled strata based on VSP P-S waves, which uses VSP P-S wave dual-source excitation, joint processing and analysis of P-S wave data, establishes the relationship between reflection characteristics and velocity changes according to the corresponding rules of velocity changes and high-resolution P-S wave data reflection characteristics, and realizes fine prediction of the velocity of un-drilled strata downhole through P-S wave joint inversion.

[0004] The application is implemented by the following technical solutions:

[0005] A method for predicting the velocity of un-drilled strata based on VSP P-S waves, comprising:

[0006] Using VSP P-S wave dual-source excitation and three-component geophone synchronous reception, original VSP P-S wave data is obtained;

[0007] The original VSP P-S wave data is subjected to benchmarking and synchronous processing to obtain P-S wave uplink reflection wave field, corridor stack profile and velocity parameters;

[0008] The upgoing reflection wave field of the P-S wave, the formation velocity variation and the lithology profile are combined, the reflection characteristics and the velocity variation are comprehensively analyzed, and a corresponding relationship of VSP P-S wave reflection characteristics-lithology-velocity is obtained.

[0009] Based on the corresponding relationship of VSP P-S wave reflection characteristics-lithology-velocity, VSP P-S wave joint inversion is performed to realize accurate prediction of the formation velocity of the un-drilled formation.

[0010] In some embodiments, the synchronization processing of the original VSP P-S wave data includes:

[0011] The original VSP P-S wave data is pre-processed to obtain the de-interference P-wave Z component and the de-interference S-wave R component;

[0012] The first arrival of the P-wave Z component and the S-wave R component is picked up respectively;

[0013] The corresponding amplitude compensation factors are obtained according to the first arrival picking results of the P-wave Z component and the S-wave R component respectively, and the spherical divergence compensation is performed on the P-wave Z component and the S-wave R component respectively by using the corresponding amplitude compensation factors;

[0014] The deconvolution processing is performed on the compensated P-wave Z component and the S-wave R component respectively;

[0015] The wave field separation is performed on the deconvolution-processed P-wave Z component and S-wave R component respectively to obtain the P-wave upgoing reflection wave field and the S-wave upgoing reflection wave field;

[0016] The NMO correction is performed on the P-wave upgoing reflection wave field and the S-wave upgoing reflection wave field respectively to obtain the P-wave flattened profile and the S-wave flattened profile;

[0017] The P-wave corridor stack profile and the S-wave corridor stack profile are obtained by cutting off the corridor data of the narrow time window near the well on the P-wave flattened profile and the S-wave flattened profile respectively.

[0018] In some embodiments, the combination of the upgoing reflection wave field of the P-S wave, the formation velocity variation and the lithology profile, and the comprehensive analysis of the reflection characteristics and the velocity variation include:

[0019] The logging data of the target well is obtained to determine the lithology interface of the formation, and the surface seismic data of the region where the target well is located is obtained;

[0020] The P-S wave corridor position is determined through well-to-surface joint calibration, and the VSP P-S wave data on the well is accurately matched with the surface seismic data;

[0021] The lithology and the VSP velocity are corresponded to the VSP P-S wave data to determine the reflection characteristics;

[0022] By analyzing the difference between the P-wave and S-wave velocities in different lithological strata, a corresponding relationship between lithology and velocity is established;

[0023] By corresponding reflection characteristics, a corresponding relationship between VSP P-wave and S-wave reflection characteristics, lithology and velocity is established.

[0024] In some embodiments, the VSP P-wave and S-wave joint inversion based on the corresponding relationship between VSP P-wave and S-wave reflection characteristics, lithology and velocity includes:

[0025] The VSP P-wave and S-wave corridor stack section is quality controlled, and then time window selection is performed. The principle of time window selection is that the complete interval from the bottom of the well to the predicted level should be covered;

[0026] Based on the corresponding relationship between VSP P-wave and S-wave reflection characteristics, lithology and velocity, an initial velocity model is constructed;

[0027] Based on the VSP P-wave and S-wave corridor stack section below the bottom of the well obtained by synchronous processing, an inversion wavelet is generated;

[0028] The initial velocity model is iteratively inverted using the inversion wavelet to obtain a final velocity model. According to the velocity value and time predicted by the final velocity model, the corresponding depth value is obtained;

[0029] The predicted depth-velocity value is verified.

[0030] In some embodiments, the construction process of the initial velocity model includes:

[0031] The measured acoustic logging velocity above the bottom of the well and the VSP velocity are extrapolated to the predicted interval below the bottom of the well according to the corresponding relationship between VSP P-wave and S-wave reflection characteristics, lithology and velocity;

[0032] Using VSP P-wave and S-wave first arrival constraints, the layer velocity of each layer above the bottom of the well is calculated, which is cross-verified with the logging velocity to ensure that the consistency between the velocity calculated by the initial velocity model and the measured data is greater than a threshold value;

[0033] Equal time interval gridding is adopted, and the time step is consistent with the VSP P-wave and S-wave data sampling rate;

[0034] Gaussian smoothing is performed on the initial velocity model;

[0035] The top boundary of the velocity model below the bottom of the well is set as a fixed constraint, and the bottom boundary is set as a gradual constraint, which conforms to the natural change rule of stratum velocity.

[0036] In some embodiments, the generation process of the inversion wavelet includes:

[0037] The extracted wavelet is weighted and averaged for each trace to generate a final inversion wavelet.

[0038] The extracted wavelet is weighted and averaged for each trace to generate a final inversion wavelet.

[0039] In some embodiments, the iterative inversion of the initial velocity model using the inversion wavelet comprises:

[0040] A target function is constructed using the least square method, and the time window of the initial velocity model is iteratively corrected to perform iterative inversion until the error between the corridor stack section obtained using the inversion velocity and the true corridor data is minimized, and the iteration is stopped to obtain a final velocity model.

[0041] And / or, the verification of the predicted depth-velocity value comprises:

[0042] The predicted depth-velocity value is first internally verified, and the P-S wave corridor stack section generated based on the final velocity model is compared with the true VSP P-S wave corridor data to determine whether the correlation coefficient is greater than a preset threshold value, and if so, it is qualified.

[0043] Then, external verification is performed to verify whether the predicted velocity is within a reasonable range in combination with regional geological rules.

[0044] Finally, joint P-S wave verification is performed to calculate the ratio of the predicted P wave and S wave velocities and compare it with the known velocity ratio of the stratum.

[0045] In a second aspect, the present application provides a VSP P-S wave based un-drilled stratum velocity prediction system, comprising:

[0046] A collection unit is configured to obtain original VSP P-S wave data by using VSP P-S wave dual-source excitation and three-component geophone synchronous reception.

[0047] A processing unit is configured to perform synchronous processing on the original VSP P-S wave data to obtain P-S wave uplink reflection wave field, corridor stack section, and velocity parameter.

[0048] A joint analysis unit is configured to combine the P-S wave uplink reflection wave field, stratum velocity variation, and lithology section to comprehensively analyze the relationship between reflection characteristics and velocity variation, and obtain a corresponding relationship of VSP P-S wave reflection characteristics-lithology-velocity.

[0049] A joint inversion unit is configured to perform VSP P-S wave joint inversion based on the corresponding relationship of VSP P-S wave reflection characteristics-lithology-velocity to realize accurate prediction of un-drilled stratum velocity.

[0050] In a third aspect, the present application provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any of the above-mentioned methods for predicting formation velocity of un-drilled layer.

[0051] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement any of the above-mentioned methods for predicting formation velocity of un-drilled layer.

[0052] The present application provides a method for predicting formation velocity of un-drilled layer based on VSP longitudinal and transverse waves. The method establishes the relationship between reflection characteristics and velocity variation by joint analysis of VSP longitudinal and transverse wave data, aiming at the corresponding rules of velocity variation and high-resolution longitudinal and transverse wave data reflection characteristics. The method accurately predicts the velocity of un-drilled layer below the well bottom by means of joint inversion of longitudinal and transverse waves, solves the problem of inaccurate prediction of un-drilled layer velocity below the well bottom in existing technologies, and leads to high cost of invalid drilling, high exploration and development risk and cost. The prediction method can provide timely, efficient and accurate velocity data below the well bottom for subsequent drilling and scheme adjustment, and greatly reduces the exploration and development risk and drilling cost.

[0053] Correspondingly, the present application also provides a system for predicting formation velocity of un-drilled layer based on VSP longitudinal and transverse waves, an electronic device and a computer readable storage medium, which have the same technical effects as described above. BRIEF DESCRIPTION OF DRAWINGS

[0054] The accompanying drawings, which are included to provide a further understanding of the embodiments of the present application and constitute a part of the present application, do not limit the embodiments of the present application. In the drawings:

[0055] Figure 1 The prediction method flowchart provided by the embodiments of the present application;

[0056] Figure 2 The target synchronous processing flowchart of the embodiments of the present application;

[0057] Figure 3 The prediction system principle block diagram provided by the embodiments of the present application;

[0058] Figure 4 The electronic device schematic diagram provided by the embodiments of the present application;

[0059] Figure 5 The computer readable storage medium schematic diagram provided by the embodiments of the present application;

[0060] Figure 6 The VSP longitudinal and transverse wave double-source synchronous excitation schematic diagram;

[0061] Figure 7A VSP P-S and P-SV reflection characteristic and formation velocity variation relationship analysis chart;

[0062] Figure 8 A VSP P-S and P-SV joint inversion high-precision prediction of un-drilled layer velocity process chart.

[0063] Figure 9 A VSP P-S and P-SV joint inversion prediction velocity verification analysis chart.

[0064] Reference signs and corresponding component names:

[0065] 300 - prediction system, 301 - acquisition unit, 302 - processing unit, 303 - joint analysis unit, 304 - joint inversion unit, 400 - electronic device, 410 - memory, 420 - processor, 411 - computer program A, 500 - computer readable storage medium, 511 - computer program B. DETAILED DESCRIPTION

[0066] Hereinafter, the term "include" or "may include" used in various embodiments of the present application indicates the existence of the invented function, operation, or element, and does not limit one or more functions, operations, or elements from being added. Also, as used in various embodiments of the present application, the terms "include", "have", and their conjugates merely indicate the presence of the mentioned features, numbers, steps, operations, elements, components, or combinations thereof, and should not be construed as excluding the possibility of the presence or addition of one or more other features, numbers, steps, operations, elements, components, or combinations thereof.

[0067] In various embodiments of the present application, the expression "or" or "at least one of A or / and B" includes any combination of the listed terms or all combinations thereof. For example, the expression "A or B" or "at least one of A or / and B" can include A, can include B, or can include both A and B.

[0068] The expressions (such as "first", "second", etc.) used in various embodiments of the present application can modify various constituent elements in various embodiments, but can not limit the corresponding constituent elements. For example, the above expressions do not limit the order and / or importance of the elements. The above expressions are used only for the purpose of distinguishing one element from other elements. For example, the first user device and the second user device indicate different user devices, although both are user devices. For example, the first element can be called the second element, and likewise, the second element can be called the first element without departing from the scope of various embodiments of the present application.

[0069] It should be noted that if a description connects one component element to another component element, the first component element can be directly connected to the second component element, and a third component element can be connected between the first component element and the second component element. Conversely, when one component element is directly connected to another component element, it can be understood that there is no third component element between the first component element and the second component element.

[0070] The terms used in the various embodiments of the present application are for the purpose of describing particular embodiments only and are not intended to limit the various embodiments of the present application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of the present application belong. The terms (such as terms defined in a generally used dictionary) will be interpreted as having the same meaning as the contextual meaning in the relevant technical field and will not be interpreted as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of the present application.

[0071] In order to make the purposes, technical solutions and advantages of the present application clearer, further detailed description of the present application is made below in combination with embodiments and drawings, the illustrative embodiments of the present application and their descriptions are only used to explain the present application and do not limit the present application.

[0072] At present, in oil and gas exploration and development, the existing technology has low accuracy in predicting the velocity of un-drilled formation below the well bottom, resulting in high cost of ineffective drilling, high exploration and development risk and cost. In view of the above problems, the embodiment of the present application proposes an un-drilled formation velocity prediction method based on VSP P and S waves. The method is excited by VSP P and S wave double sources, and the downgoing wave and upgoing wave are directly received by the geophone arranged in the well, so that high-resolution time-depth relationship and interval velocity information can be obtained, including high-resolution reflection characteristics of deep underground, which provides a reliable starting point for velocity prediction below the well bottom. Then, according to the corresponding rules of velocity change and high-resolution P and S wave data reflection characteristics, the relationship between reflection characteristics and velocity change is established, and the un-drilled formation velocity below the well is finely predicted by joint inversion means, which provides more real and reliable data basis for exploration and development research below the well bottom, and greatly reduces the exploration and development risk and drilling cost.

[0073] As shown in Figure 1 The prediction method proposed by the embodiment of the present application includes the following steps:

[0074] Step 1, using VSP P and S wave double source excitation and three-component geophone synchronous reception, obtaining high-fidelity original VSP P and S wave data;

[0075] Step 2, the original VSP P-S wave data is processed by synchronization marking to obtain high-resolution and high-fidelity P-S wave uplink reflection wave field, corridor stack section and accurate velocity parameter;

[0076] Step 3, the high-resolution and high-fidelity P-S wave uplink reflection wave field is combined with the stratum velocity variation and lithology section to comprehensively analyze the reflection characteristic and velocity variation relationship to obtain the corresponding relationship of VSP P-S wave reflection characteristic-lithology-velocity;

[0077] Step 4, the VSP P-S wave joint inversion is carried out based on the corresponding relationship of VSP P-S wave reflection characteristic-lithology-velocity to realize the accurate prediction of the un-drilled stratum velocity.

[0078] Further, in step 1 of the embodiment of the application, the P-S wave vibrator is used to excite P wave and S wave respectively, and the high-fidelity original P-S wave data (including VSP P wave data and VSP S wave data) is obtained by the synchronous receiving of the three-component geophone installed in the well. In the embodiment of the application, the SVP double vibrator is used for accurate acquisition, which can directly obtain reliable P-S wave data, break through the limitation of single waveform and multi-solution, and lay a reliable foundation for accurate velocity prediction. The specific engineering implementation process mainly includes the following stages:

[0079] The early construction preparation stage (about 1 day before construction) includes well condition survey and evaluation, technical scheme preparation and disclosure, organization of technical disclosure of construction team and equipment entry and debugging;

[0080] The on-site deployment stage (on the day of construction) includes equipment installation and calibration, mainly including geophone string lowering and depth calibration to ensure that the depth positioning of the cable is accurate, the P-S wave vibrator is arranged at a point distance of less than 150m from the wellhead, and the synchronous GPS system is erected for time synchronization calibration;

[0081] The parameter debugging and test acquisition stage mainly includes excitation parameter experiment (analysis and confirmation of the output, scan frequency, scan length and consistency of the P-S wave vibrator through signal test, and production acquisition after passing the test), and receiving parameter examination (examination according to industry standards to ensure no error);

[0082] The formal data acquisition stage mainly includes normal excitation of the vibrator to ensure the fidelity of the data quality, real-time quality monitoring to ensure the reliability of the received data, and on-site quality control to ensure the quality of the acquired data;

[0083] The construction finishing stage mainly includes geophone recovery and equipment arrangement, and data preliminary processing and delivery.

[0084] The embodiment of the application obtains accurate high-precision original data of pure P wave and pure S wave through P-S wave double vibrator acquisition, which lays a fidelity foundation for the next step of P-S wave joint processing.

[0085] Further, as shown in Figure 2 Step 2 of the embodiment of the present application specifically includes the following steps:

[0086] Pretreatment of original VSP P-S wave data: The P-S wave data is respectively decoded and the information of the beginning of the trace is checked. The P-S wave data is first rotated by three-component polarization, that is, the X component (horizontal component) of the P-S wave is polarized to the R component (rotated horizontal component). Compared with the original three components, a plurality of groups of down-going P-S waves with relatively strong energy can be seen on the R component, the characteristics of the up-going reflection wave group are good, and the up-going wave reflection event is continuous. After spherical diffusion compensation, the reflection energy of the middle-deep layer of the wave field is reasonably compensated. The P-S wave data is respectively subjected to deinterference processing. Specifically, median filtering + radial polarization filtering + FK filtering (frequency-wave number domain filtering) can be used to suppress interference such as casing wave and wellbore wave; random noise is suppressed by multi-channel coherent filtering, and the signal-to-noise ratio is greatly improved. It can be understood that the filtering method (combination) can be selected according to actual needs for deinterference removal, and there is no sequence between the P-S wave data pretreatment step and the three-component polarization rotation processing step, that is, the pretreatment can be performed first and then the rotation processing, or the rotation processing can be performed first and then the pretreatment.

[0087] Through the pretreatment of this step, the P-wave Z component (vertical component) with interference removed can be obtained from the original data, and the rotated P-S wave R component with interference removed is obtained, which provides a high-fidelity data basis for subsequent first arrival picking.

[0088] Respectively picking the P-wave Z component first arrival and the P-S wave R component first arrival: In order to ensure high picking accuracy, the embodiment of the present application uses a man-machine interactive amplification method to pick the first arrival. The P-wave Z component and the P-S wave R component obtained through the above steps are respectively used to finely pick the P-S wave first arrival, and the P-S wave first arrival is picked while being mutually quality controlled. The variation trend of the P-S wave velocity is basically consistent with that of the P-wave velocity, and the details vary. By using this feature, the picked first arrivals can be mutually quality controlled to ensure the picking accuracy, and the similarities and differences between the P-S wave velocity and the P-wave velocity can be found out to lay a foundation for subsequent analysis. That is, the P-S wave velocity is relatively strong in response to the strong reflection interface, and the accurate velocity obtained lays a faithful and accurate foundation for subsequent processing velocity analysis and corridor stacking.

[0089] Spherical diffusion compensation: The energy change of VSP data first break window can accurately reflect the change rule of seismic wave energy with time and depth in the propagation process, so the embodiment of the application uses the first break energy change of P and S waves to obtain Tar factor (amplitude compensation factor) and compensates the ground seismic amplitude, which can effectively eliminate the amplitude change caused by spherical diffusion and other factors of seismic wave, quantize the amplitude processing process and improve the fidelity of processing. After obtaining the Tar factor, the amplitude of all data can be recovered. Since the overall recovery factor is independent of single channel data, it is very beneficial to improve the fidelity of data. By comparing the Tar factors of P and S wave data, the compensation effect is comprehensively determined and analyzed, the best compensation value is determined, and high-quality data basis is provided for subsequent deconvolution.

[0090] P and S wave joint deconvolution: VSP deconvolution first obtains pure downgoing wave field through wave field separation, and then obtains downgoing wavelet by averaging the depth section with good data in the separated downgoing wave field. The downgoing wavelet is used as expected input, the main frequency of the downgoing wavelet is analyzed, and the Ricker wavelet is selected as expected output, so as to extract the deconvolution operator. The deconvolution operator is used for deconvolution to compress seismic wavelet and improve resolution. The length of the final deconvolution operator is determined through experiment and comparison (the final deconvolution operator is determined by comparing the compression resolution effects of deconvolution operators corresponding to multiple wave groups). The P wave Z component and the S wave R component after spherical diffusion compensation are deconvoluted by using the final deconvolution operator. Compared with the wave field before deconvolution, the seismic wavelet is well compressed, the downgoing multiple is effectively suppressed, and the data resolution is improved. The frequency spectrum before and after deconvolution also changes obviously. The high frequency component in the wave field after deconvolution is obviously improved, which has a positive effect on improving the resolution of VSP processing results, and various waves are more clearly distinguished in the frequency spectrum. That is, the P and S wave deconvolution is synchronously processed, the size of the deconvolution operator is compared and analyzed, the difference is analyzed, and the final used parameter is ensured to be the best value.

[0091] P and S wave joint wave field separation: The methods of removing background interference noise first, then using velocity filtering elimination method and median filtering method, and combining FK filtering are used to separate the upgoing and downgoing wave fields of P wave Z component and S wave R component respectively, so as to finally obtain the P wave upgoing reflection wave field and the S wave upgoing reflection wave field, which provides reliable wave field for subsequent processing. In the separation process, the P and S wave data use method can be used for mutual reference, benchmark processing and optimization of separation method, and the same and different parameter values are analyzed to determine the best separation parameter, so as to ensure that the quality of the separated waveform data is optimal, and the processing time can be greatly saved, the whole research progress can be accelerated, and time and other costs can be saved.

[0092] Upgoing wave fluctuation correction and flattening: high-precision upgoing wave fields separated from P-wave and S-wave are subjected to NMO correction and flattening, and the first arrival is used to establish a fine velocity model (according to the first arrival picking result, the P-wave and S-wave time-depth relationship is calculated, the P-wave and S-wave interval velocity is calculated according to the P-wave and S-wave time-depth relationship, and the P-wave and S-wave velocity model is established according to the P-wave and S-wave interval velocity), the P-wave and S-wave difference is jointly analyzed, the most suitable model data is obtained for application, and high-precision P-wave and S-wave flattened profiles are obtained after flattening

[0093] P-wave and S-wave joint corridor stack: on the P-wave and S-wave flattened profile, the corridor data of a narrow time window near the well are cut off to obtain a P-wave and S-wave corridor stack profile, the wave group characteristics of the corridor stack are avoided from being destroyed by interference waves, and the fidelity of the VSP P-wave and S-wave result data is improved. The P-wave and S-wave corridor is used for comparative analysis to determine that the reflection characteristics of the marker layer and the large set of reflection layers are consistent, and the details and local changes are caused by the different characteristics of the P-wave and S-wave reflecting strata, such as the coal seam and other strong reflection strata interfaces. The P-wave is more sensitive to the reflection, the velocity is lower, and the reflection axis is wider. Under the premise of determining the data fidelity, a good foundation is laid for subsequent P-wave and S-wave joint inversion and other researches.

[0094] Through the VSP P-wave and S-wave joint fidelity processing, high-precision and accurate pure P-wave and pure S-wave upgoing reflection wave fields and corridor stack profiles and accurate velocity parameters are obtained, which lay a fidelity foundation for the relationship between the P-wave and S-wave reflection characteristics and the stratum velocity variation.

[0095] Further, in step 3 of the embodiment of the application, the analysis process of the reflection characteristics and the velocity variation relationship comprises:

[0096] Data preparation and classification integration of the target well: according to the VSP P-wave and S-wave data body (separated P-wave reflection data), accurate time-depth relationship P-wave and S-wave velocity, VSP P-wave and S-wave corridor stack profile and other fidelity data obtained in step 2; collecting well logging data of the target well, including acoustic time difference, density and gamma curves, and clearly defining the stratum lithology interface (such as sand-shale interface and carbonate reservoir top and bottom interface); and obtaining surface seismic data of the region where the target well is located, including the columnar chart of the target well, the surface seismic data line passing through the well, and geological stratification.

[0097] VSP P-wave and S-wave corridor-well-ground joint calibration: the P-wave and S-wave corridor position is determined through well-ground joint calibration, the VSP P-wave and S-wave data on the well are accurately matched with the surface seismic data, an accurate and reliable real environment background is laid for subsequent un-drilled stratum velocity prediction, and the P-wave and S-wave data are specially focused on the tiny differences.

[0098] VSP P-S wave data-lithology-velocity correlation analysis: the lithology and VSP velocity are corresponded to P-S wave data to determine the reflection characteristics. By analyzing the difference of P-S wave velocity in different lithology strata, the corresponding relationship between lithology and velocity can be established: such as high velocity to low velocity-gray siltstone-strong peak reflection characteristics, low velocity to high velocity-mudstone-valley reflection characteristics, on the strong reflection interface of coal seam, the S wave reflection is more obvious, the velocity low value response, etc. Through these corresponding characteristics, the corresponding relationship between VSP P-S wave reflection characteristics-lithology-velocity is established, the multi-solution of prediction is reduced, and the prediction accuracy is improved.

[0099] Further, in step 4 of the embodiment of the application, the VSP P-S wave joint inversion process comprises:

[0100] Data screening: the VSP P-S wave corridor data is quality controlled, and before the time window selection, the original P-S wave VSP corridor stack data is subjected to basic quality control to ensure data reliability; the time window selection needs to cover the complete interval of "below the well bottom-predicted horizon", and the inversion efficiency and accuracy are taken into account.

[0101] Initial velocity model construction: firstly, the measured sonic logging velocity above the well bottom and the VSP velocity are extrapolated to the predicted horizon below the well bottom according to the corresponding relationship between VSP P-S wave reflection characteristics-lithology-velocity; then the initial velocity model is constructed by using the VSP P-S wave first arrival constraint to calculate the interval velocity of each layer above the well bottom, which is cross-verified with the logging velocity to ensure that the consistency of the initial velocity model with the measured data is ≥90%; the equal time interval gridding is adopted, and the time step is consistent with the VSP P-S wave sampling rate; the initial velocity model is subjected to Gaussian smoothing to eliminate local mutation points and avoid oscillation in the inversion iteration process; the top boundary (the well bottom position) of the velocity model below the well bottom is set as a fixed constraint (the velocity value is equal to the measured velocity at the well bottom), and the bottom boundary is a gradual constraint, which conforms to the natural change law of stratum velocity.

[0102] Wavelet extraction and optimization: based on the original VSP P-S wave data below the well bottom, the VSP P-S wave corridor stack profile below the well bottom is obtained by using the synchronous processing process described in step 2, and the wavelet is directly extracted from the VSP P-S wave faithful corridor stack profile. In order to improve the stability of the wavelet, the wavelet consistency is verified by cross-correlation analysis, that is, the wavelet is extracted from the multi-channel data of the VSP P-S wave corridor, and the wavelets extracted from each channel are weighted and averaged (the weight is positively correlated with the signal-to-noise ratio) to generate the inversion wavelet of the final P-S wave data, which is used as the wavelet input of the subsequent P-S wave joint inversion velocity model.

[0103] Iterative velocity inversion: the objective function is constructed by using the least square method, the time window of the initial velocity model is corrected by iteration, and the VSP P-wave and S-wave data are respectively iteratively inverted until the error between the synthetic record produced by the inverted velocity and the real P-wave and S-wave corridor data is the smallest, the iteration is stopped, the final inverted P-wave and S-wave velocity results are obtained, and the depth value is calculated according to the velocity and time to obtain the predicted P-wave and S-wave depth-velocity value.

[0104] Velocity accurate prediction: the depth-velocity values obtained by respectively inverting the VSP P-wave and S-wave data are compared and jointly analyzed, mutually quality controlled, verified and analyzed to determine the final prediction result, greatly reducing the prediction multi-solution and improving the prediction accuracy. Specifically, first, internal verification is performed, the synthetic record generated by the final inverted velocity model is compared with the real VSP P-wave and S-wave corridor data in all directions, including amplitude, phase, and phase axis shape, and the correlation coefficient is greater than or equal to 0.9; then, external verification is performed, the reflection feature-lithology-velocity relationship is combined with the regional geological law to verify whether the inverted velocity is within a reasonable range; finally, P-wave and S-wave joint verification is performed, the Vp / Vs ratio is calculated and compared with the known stratum Vp / Vs characteristics to verify the reliability and practicability of the velocity. If the above method does not pass the verification, optimization is started from the time window selection in the data screening and re-inversion verification is performed; if the above method passes the verification, the prediction result can be determined, and timely, reliable and accurate velocity parameters of un-drilled strata are provided for exploration and development and geological research, etc., playing an important role in reducing cost and risk and increasing efficiency.

[0105] The prediction method proposed in the embodiments of the present application adopts a complete fidelity technical chain of "P-wave and S-wave double-source acquisition-P-wave and S-wave correlation fidelity processing-P-wave and S-wave joint velocity analysis-P-wave and S-wave inversion velocity accurate prediction", realizes timely, efficient, accurate and low-cost prediction of the velocity of un-drilled strata below the well bottom, provides a reliable data basis for subsequent drilling and scheme adjustment implementation, and greatly reduces the exploration and development risk and drilling cost.

[0106] In order to verify the timeliness of the prediction method proposed in the embodiments of the present application, the present application takes a certain drilling as an example for description. First, according to the data acquisition mode shown in step 1, VSP P-wave and S-wave double-source synchronous excitation is adopted, as shown in Figure 6 the directions of the forces generated by the P-wave and S-wave sources are different, pure P-wave data and pure S-wave data can be obtained; then, the processing procedures of steps 2 and 3 are used to obtain the corresponding variation law of the VSP P-wave and S-wave reflection feature-lithology-velocity, as shown in Figure 7 ; finally, the VSP P-wave and S-wave joint inversion process of step 4 is performed, as shown in Figure 8 ; and the reliability and practicability of the velocity are verified by the VSP P-wave and S-wave velocity ratio method, as shown in Figure 9As shown, the final implementation realizes the accurate prediction of the un-drilled formation velocity.

[0107] Based on the same technical concept, the embodiment of the present application also proposes a VSP longitudinal and transverse wave-based un-drilled formation velocity prediction system, as shown in the figure. Figure 3 As shown, the prediction system 300 comprises:

[0108] The acquisition unit 301 is configured to obtain high-fidelity original VSP longitudinal and transverse wave data by using VSP longitudinal and transverse wave double-source excitation and three-component receiver synchronous reception. The specific data acquisition method is as described in the above step 1, and will not be repeated here.

[0109] The processing unit 302 is configured to obtain high-resolution high-fidelity longitudinal and transverse wave upgoing reflection wave field, corridor stack profile and accurate velocity parameter by performing the benchmarking synchronous processing on the original VSP longitudinal and transverse wave data. The specific benchmarking synchronous processing process is as described in the above step 2, and will not be repeated here.

[0110] The joint analysis unit 303 is configured to obtain the corresponding relationship of VSP longitudinal and transverse wave reflection characteristics-lithology-velocity by combining the high-resolution high-fidelity longitudinal and transverse wave upgoing reflection wave field with the formation velocity variation and the lithology profile, and comprehensively analyzing the reflection characteristics and the velocity variation relationship. The specific analysis process is as described in the above step 3, and will not be repeated here.

[0111] In addition, the joint inversion unit 304 is configured to perform VSP longitudinal and transverse wave joint inversion based on the corresponding relationship of VSP longitudinal and transverse wave reflection characteristics-lithology-velocity, so as to realize the accurate prediction of the un-drilled formation velocity. The specific joint inversion process is as described in the above step 4, and will not be repeated here.

[0112] Based on the same technical concept, the embodiment of the present application also proposes an electronic device, as shown in the figure. Figure 4 As shown, the electronic device 400 comprises a memory 410, a processor 420, and a computer program A 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program A 411, the following steps are implemented:

[0113] High-fidelity original VSP longitudinal and transverse wave data is obtained by using VSP longitudinal and transverse wave double-source excitation and three-component receiver synchronous reception;

[0114] High-resolution high-fidelity longitudinal and transverse wave upgoing reflection wave field, corridor stack profile and accurate velocity parameter are obtained by performing benchmarking synchronous processing on the original VSP longitudinal and transverse wave data;

[0115] The corresponding relationship of VSP longitudinal and transverse wave reflection characteristics-lithology-velocity is obtained by combining the high-resolution high-fidelity longitudinal and transverse wave upgoing reflection wave field with the formation velocity variation and the lithology profile, and comprehensively analyzing the reflection characteristics and the velocity variation relationship.

[0116] Based on the corresponding relationship of VSP longitudinal and transverse wave reflection characteristics-lithology-velocity, VSP longitudinal and transverse wave joint inversion is carried out to realize accurate prediction of the velocity of un-drilled formation.

[0117] Optionally, when the processor 420 executes the computer program A411, any implementation in the corresponding embodiments of the above prediction method can be realized.

[0118] It should be noted that the electronic device proposed in the embodiments of the present application is a device used to implement the above prediction method, and therefore based on the above prediction method proposed in the embodiments of the present application, those skilled in the art can understand the specific implementation of the electronic device of the embodiments of the present application and its various forms of changes, so here the specific implementation of the electronic device to implement the above prediction method is not introduced in detail, as long as the electronic device used to implement the above prediction method is implemented by those skilled in the art, it belongs to the scope of protection of the present application.

[0119] Based on the same technical concept, the embodiments of the present application also propose a computer readable storage medium, as shown in the figure, the computer readable storage medium 500 stores a computer program B511, and the computer program B511 is executed by a processor to realize the following steps: Figure 5 The computer readable storage medium 500 stores a computer program B511, and the computer program B511 is executed by a processor to realize the following steps:

[0120] High-fidelity original VSP longitudinal and transverse wave data is obtained by using VSP longitudinal and transverse wave double-source excitation and three-component receiver synchronous reception;

[0121] High-resolution high-fidelity longitudinal and transverse wave uplink reflection wave field, corridor stack profile and accurate velocity parameters are obtained by performing benchmarking synchronous processing on the original VSP longitudinal and transverse wave data;

[0122] The high-resolution high-fidelity longitudinal and transverse wave uplink reflection wave field is combined with the formation velocity variation and the lithology profile, the relationship between the reflection characteristics and the velocity variation is comprehensively analyzed, and the corresponding relationship of VSP longitudinal and transverse wave reflection characteristics-lithology-velocity is obtained;

[0123] Based on the corresponding relationship of VSP longitudinal and transverse wave reflection characteristics-lithology-velocity, VSP longitudinal and transverse wave joint inversion is carried out to realize accurate prediction of the velocity of un-drilled formation.

[0124] Optionally, the computer program B511 can realize any implementation in the corresponding embodiments of the above prediction method when executed by the processor.

[0125] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0126] Those skilled in the art will appreciate that embodiments of the application can be readily used as software, hardware, or a combination of software and hardware. In one

[0127] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or a combination of flowcharts and / or blocks in the flowcharts can be implemented by computer program instructions. Figure 1 means for carrying out functions specified in the flowchart block or blocks.

[0128] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or a combination of flowcharts and / or blocks in the flowcharts can be implemented by computer program instructions. Figure 1 means for carrying out functions specified in the flowchart block or blocks.

[0129] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or a combination of flowcharts and / or blocks in the flowcharts can be implemented by computer program instructions. Figure 1 means for carrying out functions specified in the flowchart block or blocks.

[0130] The above detailed description has shown, described, and pointed out the aspects of the application in sufficient detail that others skilled in the art can, by applying the knowledge of those skilled in the art, readily make and use the application. Those skilled in the art will further appreciate that the present application can be practiced with embodiments other than those described, which will occur to those skilled in the art, having the benefit of the present disclosure. What is claimed is:

Claims

1. A method for predicting un-drilled formation velocity based on VSP P-waves and S-waves, characterized in that, include: The raw VSP P- and S-wave data were obtained by using dual-source excitation of VSP P- and S-waves and synchronous reception of three-component detectors. The original VSP P-wave and S-wave data were subjected to calibration and synchronization processing to obtain the P-wave and S-wave up-reflection wavefield, corridor superposition profile, and velocity parameters. By combining the P-wave and S-wave upward reflection wavefield, formation velocity variation and lithological profile, the relationship between reflection characteristics and velocity variation is comprehensively analyzed to obtain the correspondence between VSP P-wave and S-wave reflection characteristics, lithology and velocity. Based on the correspondence between the VSP P- and S-wave reflection characteristics, lithology, and velocity, VSP P- and S-wave joint inversion is performed to achieve accurate prediction of un-drilled formation velocities.

2. The method for predicting un-drilled formation velocity based on VSP P- and S-waves according to claim 1, characterized in that, The aforementioned calibration and synchronization processing of the original VSP P-wave and S-wave data includes: The original VSP P-wave and S-wave data are preprocessed to obtain the interference-free P-wave Z-component and S-wave R-component. The initial arrivals of the longitudinal wave Z component and the transverse wave R component are picked up respectively; Based on the initial arrival picking results of the longitudinal wave Z component and the transverse wave R component, the corresponding amplitude compensation factors are obtained respectively, and the corresponding amplitude compensation factors are used to perform spherical diffusion compensation on the longitudinal wave Z component and the transverse wave R component respectively. The compensated longitudinal wave Z component and transverse wave R component are deconvolved respectively. Wavefield separation is performed on the longitudinal wave Z component and the transverse wave R component after deconvolution processing to obtain the longitudinal wave upward reflection wavefield and the transverse wave upward reflection wavefield. The longitudinal wave upward reflection field and the transverse wave upward reflection field are dynamically corrected and flattened respectively to obtain longitudinal wave flattened profiles and transverse wave flattened profiles. On the P-wave flattened profile and the S-wave flattened profile, respectively, corridor data with narrow time windows near the well perimeter are superimposed to obtain the P-wave corridor superimposed profile and the S-wave corridor superimposed profile.

3. The method for predicting un-drilled formation velocity based on VSP P- and S-waves according to claim 1, characterized in that, The aforementioned method of combining the upward reflection wavefields of P-waves and S-waves, formation velocity variations, and lithological profiles to comprehensively analyze the relationship between reflection characteristics and velocity variations includes: Obtain logging data from the target well to identify formation lithological interfaces; and obtain surface seismic data for the area where the target well is located. The location of the P-wave and S-wave corridors is determined by well-to-surface joint calibration, and the well VSP P-wave and S-wave data are accurately matched with the surface seismic data. By mapping lithology and VSP velocity to VSP P- and S-wave data, reflection characteristics were determined. By analyzing the differences in P-wave and S-wave velocities in strata with different lithologies, a correspondence between lithology and velocity is established. By establishing the corresponding reflection characteristics, the relationship between VSP P-wave and S-wave reflection characteristics, lithology, and velocity is established.

4. A method for predicting un-drilled formation velocity based on VSP P- and S-waves according to any one of claims 1-3, characterized in that, The aforementioned VSP P- and S-wave joint inversion based on the correspondence between VSP P- and S-wave reflection characteristics, lithology, and velocity includes: The VSP P-wave and S-wave corridor superimposed profile is quality controlled, and then a time window is selected. The time window selection principle is: it should cover the complete interval from the bottom of the well to the prediction layer. Based on the correspondence between the VSP P-wave and S-wave reflection characteristics, lithology, and velocity, an initial velocity model is constructed. Based on the superimposed profile of VSP P- and S-wave corridors below the well bottom obtained by benchmarking synchronous processing, inverted wavelets are generated. The initial velocity model is iteratively inverted using the inversion wavelet to obtain the final velocity model. Based on the velocity and time predicted by the final velocity model, the corresponding depth value is obtained. The predicted depth-velocity values ​​were verified.

5. The method for predicting un-drilled formation velocity based on VSP P- and S-waves according to claim 4, characterized in that, The process of constructing the initial velocity model includes: The measured acoustic logging velocities and VSP velocities above the well bottom are extrapolated to the predicted layers below the well bottom according to the correspondence between VSP P-wave and S-wave reflection characteristics, lithology, and velocity. Using VSP P-wave and S-wave first arrival constraints, the layer velocities of each segment above the bottom of the well are calculated and cross-validated with the logging velocities to ensure that the velocities calculated by the initial velocity model are consistent with the measured data to a greater than a threshold. Equal-time gridding is adopted, with the time step consistent with the sampling rate of the VSP P-wave and S-wave data; Gaussian smoothing was applied to the initial velocity model; The top boundary of the velocity model below the well bottom is set as a fixed constraint, and the bottom boundary is set as a gradually changing constraint, which conforms to the natural variation law of formation velocity.

6. The method for predicting un-drilled formation velocity based on VSP P- and S-waves according to claim 4, characterized in that, The generation process of the inversion wavelet includes: Wavelet extraction was performed using multichannel data from the VSP P- and S-wave corridor superimposed profile below the well bottom; The extracted wavelets from each channel are weighted and averaged to generate the final inversion wavelet.

7. The method for predicting un-drilled formation velocity based on VSP P- and S-waves according to claim 4, characterized in that, The iterative inversion of the initial velocity model using the inversion wavelet includes: The objective function is constructed using the least squares method. The time window of the initial velocity model is iteratively corrected, and iterative inversion is performed until the error between the corridor overlay profile obtained by using the inverted velocity and the real corridor data is minimized. The iteration is then stopped, and the final velocity model is obtained. And / or, the verification of the predicted depth-velocity values ​​includes: The predicted depth-velocity values ​​are first internally verified. The P-wave and S-wave corridor superimposed profiles generated based on the velocity predicted by the final velocity model are compared with the actual VSP P-wave and S-wave corridor data to determine whether the correlation coefficient is greater than the preset threshold. If it is, it is qualified. Then, external verification is conducted, taking into account regional geological patterns, to verify whether the predicted speed is within a reasonable range; Finally, a joint verification of P-waves and S-waves was performed, and the ratio of the predicted velocities of P-waves and S-waves was calculated and compared with the velocity ratios of known formations.

8. A system for predicting un-drilled formation velocity based on VSP (Vertical and Spherical Spindle Waves), characterized in that, include: The acquisition unit is used to obtain raw VSP P- and S-wave data by using dual VSP P- and S-wave sources for excitation and synchronous reception by a three-component detector. The processing unit is used to perform calibration and synchronization processing on the original VSP P-wave and S-wave data to obtain the P-wave and S-wave up-reflection wavefield, corridor superposition profile and velocity parameters. The joint analysis unit is used to combine the P-wave and S-wave up-reflection wavefield, formation velocity variation and lithological profile, and comprehensively analyze the relationship between reflection characteristics and velocity variation to obtain the correspondence between VSP P-wave and S-wave reflection characteristics, lithology and velocity. In addition, a joint inversion unit is used to perform joint VSP P- and S-wave inversion based on the correspondence between the VSP P- and S-wave reflection characteristics, lithology, and velocity, so as to achieve accurate prediction of undrilled formation velocity.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the un-drilled formation velocity prediction method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the un-drilled formation velocity prediction method according to any one of claims 1-7.

Images