Method and device for carrying out Q offset processing by utilizing well-ground joint data

Abstract

The invention discloses a method and device for performing Q offset processing by using well-ground joint data, and the technical scheme is as follows: obtaining in-well DAS data and ground three-dimensional seismic data; according to the in-well DAS data and the ground three-dimensional seismic data, calculating a Q-value curve from shallow to deep at the shaft position; performing Q value precision correction on the ground Q value curve by using the in-well Q value curve; horizon information is picked up along a strong energy event in the ground three-dimensional seismic data, and a spatial three-dimensional Q body is calculated by using the ground three-dimensional seismic data; calculating a precision correction factor by using the in-well DAS data with different offsets; the method comprises the following steps: establishing a high-precision three-dimensional Q body combined with two kinds of data information by using well DAS and ground three-dimensional seismic data received in a homologous manner, and synchronously optimizing a speed model; and inputting a high-precision three-dimensional Q body and a speed model, performing Q migration processing on the ground seismic data, and improving the imaging precision and resolution of the seismic data. The method has the beneficial effect that the method for performing Q offset processing by using the well-ground joint data is provided.

Description

Technical Field

[0001] The present invention relates to the field of oil and gas geophysical exploration and development, and in particular to a method and device for Q offset processing using well-ground combined data. Background Art

[0002] With the deepening of exploration and development, the high-quality resources that are easy to mine are constantly decreasing, and the exploration and development of complex geological targets are becoming more and more difficult. Due to the constraints of instrument equipment and construction costs, seismic data have the problems of low deep imaging accuracy and large well-seismic errors, and it is urgent to carry out joint well-ground exploration. Three-dimensional seismic is to obtain effective information of underground seismic waves by exciting artificial seismic sources and receiving them by ground detectors. VSP (vertical seismic profile) is to place detectors in the well and stimulate artificial seismic sources on the ground. Because the underground strata are non-completely elastic media, they will absorb and attenuate seismic waves, causing the amplitude energy, frequency, phase, etc. of seismic waves to attenuate or distort, and there are also various noise interferences, which reduce the resolution of seismic data and affect the fine characterization and identification of thin reservoirs. Therefore, how to accurately extract the formation absorption and attenuation factor, establish an accurate velocity model, and perform Q-offset processing is an effective technical means to improve the imaging accuracy and resolution of seismic data.

[0003] The high-precision three-dimensional Q body (quality factor) can be used for Q migration processing, which can greatly improve the imaging accuracy of seismic data and at the same time improve the resolution of seismic data. When calculating the Q value, the Q value calculation method is classified according to the type of data used, including: calculating the Q value using near-surface micro-logging data, calculating the Q value using ground three-dimensional seismic data, and calculating the Q value using vertical seismic profile (Vertical Seismic Profile, VSP) data.

[0004] Conventional ground 3D seismic mainly uses reflection waves to image the stratigraphic structure. When the amplitude of the reflection wave is used to calculate the Q (quality factor) value, due to noise interference, amplitude distortion, phase distortion and other problems, the calculated Q value has poor stability, low reliability and singular value interference. It is difficult to effectively obtain a high-accuracy 3D Q body by relying solely on conventional ground 3D seismic data. How to calculate an accurate Q body to achieve fine exploration and development is an urgent problem to be solved. VSP (vertical seismic profile) is to place a detector in the well and excite an artificial source on the ground. Due to the limited number of detectors in the well, multiple source excitations are required on the ground, and the detectors are constantly moving in the well to complete the acquisition of the entire well section. The Q value is calculated using the first arrival wave of the VSP data. Due to the influence of different source excitations, there is a problem of sub-wave inconsistency, which affects the accuracy of Q value calculation. The well detector cannot withstand the high temperature in the deep underground, resulting in the inability to collect VSP data in the deep layer, resulting in a lack of deep data, and the inability to calculate the deep Q value, resulting in unsatisfactory deep Q value compensation effect.

[0005] In order to solve the above problems, a Q migration processing method using well-ground joint data was developed. Summary of the invention

[0006] The purpose of the present invention is to provide a method and device for Q-offset processing using well-ground joint data, specifically: taking advantage of the DAS data in the well and the three-dimensional seismic data on the ground to achieve accurate establishment of a three-dimensional Q-body; after obtaining an accurate three-dimensional Q-body, synchronously inputting an accurate velocity model, and through Q-offset processing of seismic data, achieving effective compensation for formation absorption attenuation, and simultaneously improving the imaging accuracy and resolution of seismic data.

[0007] The present invention is achieved by the following measures: A Q offset processing method using well-ground joint data mainly includes the following steps:

[0008] Step 1: Obtain the well DAS data and ground 3D seismic data under the same source signal in the work area;

[0009] The DAS in the well and the ground 3D seismic receive the signals from the same source, and the two have the same source characteristics, which ensures the accuracy of Q value calculation. The data format is segy format. The optical fiber DAS is arranged from the wellhead to the bottom of the well, and the detectors are buried on the ground according to the designed observation system. The artificial source is excited on the ground using explosives, controllable vibrators, heavy hammers, etc. When the conditions for in-well excitation are met, the source should be excited in the well synchronously, and the DAS in the well and the ground detectors receive synchronously to ensure the consistency of the source characteristics.

[0010] Distributed acoustic sensing (DAS) can be deployed in the entire well section from the wellhead to the bottom of the well at one time. It only needs to excite the source once on the ground to realize data collection in the entire well section, reducing the impact of different source excitations.

[0011] Step 2: Calculate the Q value using the attenuation method of the combined amplitude, frequency and phase, and calculate the Q value curves from shallow to deep at the wellbore location based on the DAS data in the well and the 3D seismic data on the ground.

[0012] The fine Q value curve QDAS at the wellbore position is calculated based on the DAS data in the well using the attenuation method of amplitude, frequency and phase. well (i), i = 1, 2, 3 ... N, i is the depth sampling interval, N is the depth value, unit is m. The fine Q value curve calculated using the DAS data in the well has high accuracy and precision, and can more finely describe the Q value from shallow to deep in the wellbore, with an accuracy of up to 1m.

[0013] The rough Q value curve Q3D at the wellbore location is calculated based on the ground 3D seismic data using the attenuation method of amplitude, frequency and phase. well (j), j = 1, 2, 3 ... M, j is the depth sampling interval, M is the depth value, unit is m. Limited by the ground three-dimensional seismic data, the accuracy of the rough Q value curve is lower than that of the fine Q value curve. The Q value from shallow to deep in the wellbore is not fine enough, the Q value has poor stability and low reliability, there is singular value interference, and the accuracy is about 10-100m.

[0014] Step 3: Taking advantage of the respective advantages of the two types of data, use the fine Q value curve in the well to calibrate the Q value accuracy of the rough Q value curve on the ground, and conduct detailed layered evaluation and analysis.

[0015] Through the similarity analysis of the Q value curves at the two wellbore locations, the Q value accuracy correction factor QCor of the wellbore joint is calculated. well , using the wellbore joint Q value accuracy correction factor QCor well Correct the rough Q value curve to achieve the consistency of the Q value depth domain between the well data and the ground data at the wellbore position. The rough Q value curve after correction at the wellbore position is Q3D well *QCor well (k), where: Q3D well is the rough Q value curve at the wellbore position; QCor well is the precision correction factor of the well-ground joint Q value in the wellbore; k=1,2,3......X, k is the depth sampling interval, X is the depth value, unit is m.

[0016] Through the layered accuracy analysis of the two Q value curves, the layered factor QLay of the wellbore joint Q value matching is calculated. well , using the wellbore joint Q value to match the stratification factor QLay well The rough Q value curve after correction is layered. The Q value layering model at the wellbore position is Q3D well *QCor well *QLay well (h), where: Q3D well is the rough Q value curve at the wellbore position; QCor well QLay is the Q value accuracy correction factor of the wellbore joint well and ground; well It is the stratification factor of the joint Q value matching of the wellbore; h = 1, 2, 3...L, h is the model stratification number, L is the total number of model layers, dimensionless unit.

[0017] The similarity judgment analysis is to achieve the approximation of the two Q value curves by extracting the accuracy correction factor, square wave the fine Q value curve, and interpolate the rough Q value curve. After the accuracy of the two Q value curves reaches one order of magnitude, the two are matched by the frequency division normalized cross-correlation method, which improves the accuracy of the Q value calculated by ground three-dimensional seismic. The layered accuracy judgment analysis is to use the fine Q value curve as the layered guidance parameter after the accuracy of the two Q value curves reaches one order of magnitude, and layer the corrected rough Q value curve, which not only ensures the stability of the results, but also achieves fine layering.

[0018] Step 4: Pick up the layer information along the strong energy phase axis in the ground three-dimensional seismic data, and use the ground three-dimensional seismic data to calculate the spatial three-dimensional Q body.

[0019] When picking 3D layers based on ground 3D seismic data, the wellbore joint Q value at the wellbore position is matched with the layering factor QLay well As a picking quantity version, it improves the reliability and refinement of layer picking and obtains the spatial three-dimensional layering factor QLay area .

[0020] According to the spatial three-dimensional layering factor QLay area , using the ground 3D seismic data to calculate the Q value of each layer, to achieve the Q value filling of the 3D layered model, and obtain the Q volume Q3D of the 3D seismic data area In the process of calculating the three-dimensional Q body in space, the Q value accuracy correction factor QCor is used to correct the wellbore joint Q value. well Improve the accuracy of the spatial three-dimensional Q body. Establish the initial layered model Q3D of the spatial three-dimensional Q body of the work area area *QCor well *QLay area (h), where: Q3D area QCor is the Q volume of 3D seismic data; well QLay is the Q value accuracy correction factor of the wellbore joint well and ground; area is the three-dimensional spatial stratification factor; h = 1, 2, 3...L, h is the model stratification number, L is the total number of model layers, dimensionless unit.

[0021] Through the wellbore joint Q value accuracy correction factor QCor well It can improve the accuracy of the spatial three-dimensional Q body, but the correction factor has a higher accuracy at the wellbore position. At the position far away from the wellbore, the accuracy will be reduced, and the underground stratigraphic structure is constantly changing. A three-dimensional correction factor is needed to further improve the accuracy of the three-dimensional Q body layered initial model.

[0022] Step 5: Stimulate seismic sources at different locations on the ground, and use the DAS data in the well at different offset distances to calculate the accuracy correction factor to improve the accuracy of the initial model of the Q body layer.

[0023] In the Q-body layered initial model, the propagation paths of DAS data in wells with different offsets are calculated respectively, so as to obtain the correction factor in three-dimensional space. When artificial seismic sources are excited on the ground, seismic waves propagate from the ground to the underground, passing through various strata from shallow to deep in sequence. The number of layers passed by the near-offset data is small, and the number of layers passed by the far-offset data is large. The wave equation is combined with ray tracing to ensure the stability and reliability of the propagation path.

[0024] According to the propagation path of DAS data in wells with different offsets, the initial model of Q body stratification is corrected. From near offset to far offset, the Q value calculation error is gradually eliminated; from shallow to deep layers, correction is made in sequence to achieve layer-by-layer stripping of Q value fine calculation. Based on the Q value calculation and layer stripping rules from near to far and from shallow to deep, the three-dimensional well-ground joint Q value accuracy correction factor QCor is finally obtained. area , achieving further improvement in the accuracy of the Q-body stratified initial model.

[0025] Step 6: Using the well DAS and ground 3D seismic data received from the same source, a high-precision 3D Q-body is established by combining the two types of data information, and the velocity model is optimized simultaneously.

[0026] The 3D Q-body makes full use of the two data types, DAS in the well and 3D seismic on the ground. The advantage of DAS in the well in calculating the Q value accurately is brought into play at the wellbore. The 3D Q-body layered initial model is established using the 3D seismic data on the ground. The Q value accuracy is then improved using DAS data in the well at different offsets. The final 3D Q-body is Q3D area *QCor area *QLay area (h), where: Q3D area QCor is the Q volume of 3D seismic data; area QLay is the Q value accuracy correction factor of the three-dimensional well-ground joint; area is the three-dimensional spatial stratification factor; h = 1, 2, 3...L, h is the model stratification number, L is the total number of model layers, dimensionless unit.

[0027] At the same time, the velocity model is optimized according to the established three-dimensional Q body, laying the foundation for the subsequent migration processing. The optimized velocity model is V3D(h), h = 1, 2, 3...L, h is the model layer number, L is the total number of model layers, dimensionless unit.

[0028] Step 7: Input high-precision three-dimensional Q-body and velocity model, perform Q-migration processing on ground seismic data, and simultaneously improve the imaging accuracy and resolution of seismic data.

[0029] Based on the high-precision 3D Q-body and the velocity model jointly established by the DAS in the well and the 3D seismic on the ground, Q migration imaging is performed layer by layer from shallow to deep. area (h), input three-dimensional Q body Q3D area *QCor area *QLay area (h), and the optimized three-dimensional velocity model V3D(h), Q migration depth imaging is performed on the seismic data layer by layer, and the amplitude, frequency and phase of the seismic data are simultaneously recovered layer by layer, where: Q3D area QCor is the Q volume of 3D seismic data; area QLay is the Q value accuracy correction factor of the three-dimensional well-ground joint; area is the three-dimensional spatial stratification factor; h = 1, 2, 3...L, h is the model stratification number, L is the total number of model layers, dimensionless unit.

[0030] The final output is the seismic data after Q compensation processing, which simultaneously improves the resolution of seismic data and the accuracy of deep imaging. The data format is segy.

[0031] The embodiment of the present application provides a device for performing Q offset processing using well-ground joint data, characterized in that it includes:

[0032] Data acquisition module, used to acquire the well DAS data and ground 3D seismic data under the same source signal in the work area;

[0033] The Q value calculation module is used to calculate the Q value curves from shallow to deep at the wellbore position according to the DAS data in the well and the ground three-dimensional seismic data;

[0034] The correction analysis module is used to use the Q value curve in the well to calibrate the Q value accuracy of the surface Q value curve, and perform detailed layered evaluation and analysis;

[0035] A spatial three-dimensional Q-body calculation module is used to pick up layer information along the strong energy event axis in the ground three-dimensional seismic data and calculate the spatial three-dimensional Q-body using the ground three-dimensional seismic data;

[0036] The precision correction factor calculation module excites the seismic source at different locations on the ground and calculates the precision correction factor using the DAS data in the well at different offset distances;

[0037] The optimization module uses the well DAS and ground 3D seismic data received from the same source to establish a high-precision 3D Q-body that combines the two types of data information and simultaneously optimizes the velocity model;

[0038] The processing module inputs high-precision three-dimensional Q-body and velocity model, performs Q-migration processing on ground seismic data, and simultaneously improves the imaging accuracy and resolution of seismic data.

[0039] An embodiment of the present application also provides an electronic device, characterized in that it includes: a processor and a memory, wherein the processor is used to execute a program stored in the memory for performing Q offset processing using well-ground combined data, so as to implement the Q offset processing method using well-ground combined data.

[0040] An embodiment of the present application also provides a storage medium, characterized in that the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the Q offset processing method using well-ground joint data.

[0041] The technical solution provided by the embodiment of the present invention has the following beneficial effects: taking advantage of the two data types, the DAS in the well and the 3D seismic data on the ground, the DAS in the well is used to perform precision correction and matching stratification on the 3D seismic Q value curve on the ground at the wellbore position, and a 3D Q body stratification initial model with high precision is established. Taking advantage of the DAS data in the well at different offset distances, based on the calculation rules from near to far and from front to deep, the accuracy of the Q body stratification initial model is further improved.

[0042] The DAS in the well can realize the layout of the whole well section at one time. It only needs to be excited once on the ground to realize the acquisition of the whole well section. The DAS data in the well has very good sub-wave consistency. The fine Q value curve can be calculated at the wellbore position. The Q value calculated by the three-dimensional seismic data is corrected according to the fine Q value curve, which greatly improves the reliability of the calculation results. The DAS in the well has the characteristics of high temperature resistance. It can realize the whole acquisition from the wellhead to the bottom of the well without data loss. It can realize the fine calculation of the deep Q value. The final three-dimensional Q body contains all the information of the shallow, middle and deep layers. According to the propagation law of seismic waves that attenuate layer by layer from shallow to deep, based on the three-dimensional Q body and velocity model jointly established by the well and the ground, Q migration processing is performed layer by layer, eliminating the adverse effects of the absorption and attenuation of the formation, and simultaneously improving the imaging accuracy and resolution of seismic data, reducing well-seismic errors, and improving the ability to identify thin layers. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings used in the embodiments. Obviously, the drawings listed below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 A technical flow chart of an embodiment of the present invention;

[0045] Figure 2 It is the DAS data in the well;

[0046] Figure 3 is the calculated three-dimensional quality factor body;

[0047] Figure 4 is the seismic section after Q migration;

[0048] Figure 5 It is a structural schematic diagram of a device for performing Q offset processing using well-ground joint data in an embodiment of the present invention;

[0049] Figure 6 The figure is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. Of course, the specific embodiments described here are only used to explain the present invention and are not used to limit the present invention.

[0051] Embodiment 1:

[0052] See also Figure 1-Figure 4 A Q migration processing method using well-ground joint data mainly includes the following steps:

[0053] Step 1: Obtain the well DAS data and ground 3D seismic data under the same source signal in the work area;

[0054] The DAS in the well and the ground 3D seismic receive the signals from the same source, and the two have the same source characteristics, which ensures the accuracy of Q value calculation. The data format is segy format. The optical fiber DAS is arranged from the wellhead to the bottom of the well, and the detectors are buried on the ground according to the designed observation system. The artificial source is excited on the ground using explosives, controllable vibrators, heavy hammers, etc. When the conditions for in-well excitation are met, the source should be excited in the well synchronously, and the DAS in the well and the ground detectors receive synchronously to ensure the consistency of the source characteristics.

[0055] Distributed acoustic sensing (DAS) can be deployed in the entire well section from the wellhead to the bottom of the well at one time. It only needs to excite the source once on the ground to realize data collection in the entire well section, reducing the impact of different source excitations.

[0056] Step 2: Calculate the Q value using the attenuation method of the combined amplitude, frequency and phase, and calculate the Q value curves from shallow to deep at the wellbore location based on the DAS data in the well and the 3D seismic data on the ground.

[0057] The fine Q value curve QDAS at the wellbore position is calculated based on the DAS data in the well using the attenuation method of amplitude, frequency and phase. well (i), i = 1, 2, 3 ... N, i is the depth sampling interval, N is the depth value, unit is m. The fine Q value curve calculated using the DAS data in the well has high accuracy and precision, and can more finely describe the Q value from shallow to deep in the wellbore, with an accuracy of up to 1m.

[0058] The rough Q value curve Q3D at the wellbore location is calculated based on the ground 3D seismic data using the attenuation method of amplitude, frequency and phase. well (j), j = 1, 2, 3 ... M, j is the depth sampling interval, M is the depth value, unit is m. Limited by the ground three-dimensional seismic data, the accuracy of the rough Q value curve is lower than that of the fine Q value curve. The Q value from shallow to deep in the wellbore is not fine enough, the Q value has poor stability and low reliability, there is singular value interference, and the accuracy is about 10-100m.

[0059] Step 3: Taking advantage of the respective advantages of the two types of data, use the fine Q value curve in the well to calibrate the Q value accuracy of the rough Q value curve on the ground, and conduct detailed layered evaluation and analysis.

[0060] Through the similarity analysis of the Q value curves at the two wellbore locations, the Q value accuracy correction factor QCor of the wellbore joint is calculated. well , using the wellbore joint Q value accuracy correction factor QCor well Correct the rough Q value curve to achieve the consistency of the Q value depth domain between the well data and the ground data at the wellbore position. The rough Q value curve after correction at the wellbore position is Q3D well *QCor well (k), where: Q3D well is the rough Q value curve at the wellbore position; QCor well is the precision correction factor of the well-ground joint Q value in the wellbore; k=1,2,3......X, k is the depth sampling interval, X is the depth value, unit is m.

[0061] Through the layered accuracy analysis of the two Q value curves, the layered factor QLay of the wellbore joint Q value matching is calculated. well , using the wellbore joint Q value to match the stratification factor QLay well The rough Q value curve after correction is layered. The Q value layering model at the wellbore position is Q3D well *QCor well *QLay well (h), where: Q3D wellis the rough Q value curve at the wellbore position; QCor well QLay is the Q value accuracy correction factor of the wellbore joint well and ground; well It is the stratification factor of the joint Q value matching of the wellbore; h = 1, 2, 3...L, h is the model stratification number, L is the total number of model layers, dimensionless unit.

[0062] The similarity judgment analysis is to achieve the approximation of the two Q value curves by extracting the accuracy correction factor, square wave the fine Q value curve, and interpolate the rough Q value curve. After the accuracy of the two Q value curves reaches one order of magnitude, the two are matched by the frequency division normalized cross-correlation method, which improves the accuracy of the Q value calculated by ground three-dimensional seismic. The layered accuracy judgment analysis is to use the fine Q value curve as the layered guidance parameter after the accuracy of the two Q value curves reaches one order of magnitude, and layer the corrected rough Q value curve, which not only ensures the stability of the results, but also achieves fine layering.

[0063] Step 4: Pick up the layer information along the strong energy phase axis in the ground three-dimensional seismic data, and use the ground three-dimensional seismic data to calculate the spatial three-dimensional Q body.

[0064] When picking 3D layers based on ground 3D seismic data, the wellbore joint Q value at the wellbore position is matched with the layering factor QLay well As a picking quantity version, it improves the reliability and refinement of layer picking and obtains the spatial three-dimensional layering factor QLay area .

[0065] According to the spatial three-dimensional layering factor QLay area , using the ground 3D seismic data to calculate the Q value of each layer, to achieve the Q value filling of the 3D layered model, and obtain the Q volume Q3D of the 3D seismic data area In the process of calculating the three-dimensional Q body in space, the Q value accuracy correction factor QCor is used to correct the wellbore joint Q value. well Improve the accuracy of the spatial three-dimensional Q body. Establish the initial layered model Q3D of the spatial three-dimensional Q body of the work area area *QCor well *QLay area (h), where: Q3D area QCor is the Q volume of 3D seismic data; well QLay is the Q value accuracy correction factor of the wellbore joint well and ground; area is the three-dimensional spatial stratification factor; h = 1, 2, 3...L, h is the model stratification number, L is the total number of model layers, dimensionless unit.

[0066] Through the wellbore joint Q value accuracy correction factor QCor wellIt can improve the accuracy of the spatial three-dimensional Q body, but the correction factor has a higher accuracy at the wellbore position. At the position far away from the wellbore, the accuracy will be reduced, and the underground stratigraphic structure is constantly changing. A three-dimensional correction factor is needed to further improve the accuracy of the three-dimensional Q body layered initial model.

[0067] Step 5: Stimulate seismic sources at different locations on the ground, and use the DAS data in the well at different offset distances to calculate the accuracy correction factor to improve the accuracy of the initial model of the Q body layer.

[0068] In the Q-body layered initial model, the propagation paths of DAS data in wells with different offsets are calculated respectively, so as to obtain the correction factor in three-dimensional space. When artificial seismic sources are excited on the ground, seismic waves propagate from the ground to the underground, passing through various strata from shallow to deep in sequence. The number of layers passed by the near-offset data is small, and the number of layers passed by the far-offset data is large. The wave equation is combined with ray tracing to ensure the stability and reliability of the propagation path.

[0069] According to the propagation path of DAS data in wells with different offsets, the initial model of Q body stratification is corrected. From near offset to far offset, the Q value calculation error is gradually eliminated; from shallow to deep layers, correction is made in sequence to achieve layer-by-layer stripping of Q value fine calculation. Based on the Q value calculation and layer stripping rules from near to far and from shallow to deep, the three-dimensional well-ground joint Q value accuracy correction factor QCor is finally obtained. area , achieving further improvement in the accuracy of the Q-body stratified initial model.

[0070] Step 6: Using the well DAS and ground 3D seismic data received from the same source, a high-precision 3D Q-body is established by combining the two types of data information, and the velocity model is optimized simultaneously.

[0071] The 3D Q-body makes full use of the two data types, DAS in the well and 3D seismic on the ground. The advantage of DAS in the well in calculating the Q value accurately is brought into play at the wellbore. The 3D Q-body layered initial model is established using the 3D seismic data on the ground. The Q value accuracy is then improved using DAS data in the well at different offsets. The final 3D Q-body is Q3D area *QCor area *QLay area (h), where: Q3D area QCor is the Q volume of 3D seismic data; area QLay is the Q value accuracy correction factor of the three-dimensional well-ground joint; area is the three-dimensional spatial stratification factor; h = 1, 2, 3...L, h is the model stratification number, L is the total number of model layers, dimensionless unit.

[0072] At the same time, the velocity model is optimized according to the established three-dimensional Q body, laying the foundation for the subsequent migration processing. The optimized velocity model is V3D(h), h = 1, 2, 3...L, h is the model layer number, L is the total number of model layers, dimensionless unit.

[0073] Step 7: Input high-precision three-dimensional Q-body and velocity model, perform Q-migration processing on ground seismic data, and simultaneously improve the imaging accuracy and resolution of seismic data.

[0074] Based on the high-precision 3D Q-body and the velocity model jointly established by the DAS in the well and the 3D seismic on the ground, Q migration imaging is performed layer by layer from shallow to deep. area (h), input three-dimensional Q body Q3D area *QCor area *QLay area (h), and the optimized three-dimensional velocity model V3D(h), Q migration depth imaging is performed on the seismic data layer by layer, and the amplitude, frequency and phase of the seismic data are simultaneously recovered layer by layer, where: Q3D area QCor is the Q volume of 3D seismic data; area QLay is the Q value accuracy correction factor of the three-dimensional well-ground joint; area is the three-dimensional spatial stratification factor; h = 1, 2, 3...L, h is the model stratification number, L is the total number of model layers, dimensionless unit.

[0075] The final output is the seismic data after Q compensation processing, which simultaneously improves the resolution of seismic data and the accuracy of deep imaging. The data format is segy.

[0076] Embodiment 2

[0077] See also Figure 5 In this embodiment, a device for Q offset processing using well-ground joint data is provided, which is characterized by comprising:

[0078] Data acquisition module, used to acquire the well DAS data and ground 3D seismic data under the same source signal in the work area;

[0079] The Q value calculation module is used to calculate the Q value curves from shallow to deep at the wellbore position according to the DAS data in the well and the ground three-dimensional seismic data;

[0080] The correction analysis module is used to use the Q value curve in the well to calibrate the Q value accuracy of the surface Q value curve, and perform detailed layered evaluation and analysis;

[0081] A spatial three-dimensional Q-body calculation module is used to pick up layer information along the strong energy event axis in the ground three-dimensional seismic data and calculate the spatial three-dimensional Q-body using the ground three-dimensional seismic data;

[0082] The precision correction factor calculation module excites the seismic source at different locations on the ground and calculates the precision correction factor using the DAS data in the well at different offset distances;

[0083] The optimization module uses the well DAS and ground 3D seismic data received from the same source to establish a high-precision 3D Q-body that combines the two types of data information and simultaneously optimizes the velocity model;

[0084] The processing module inputs high-precision three-dimensional Q-body and velocity model, performs Q-migration processing on ground seismic data, and simultaneously improves the imaging accuracy and resolution of seismic data.

[0085] For detailed description of the functions of each module, please refer to the relevant description corresponding to the above method embodiment, which will not be repeated here.

[0086] Embodiment three:

[0087] See also Figure 6 In this embodiment, an electronic device is provided, characterized in that it includes: a processor and a memory, wherein the processor is used to execute a program stored in the memory for performing Q offset processing using well-ground combined data, so as to implement the method for performing Q offset processing using well-ground combined data.

[0088] Figure 5 The electronic device 1700 shown includes: at least one processor 1701, a memory 1702, at least one network interface 1704 and other user interfaces 1703. The various components in the electronic device 1700 are coupled together via a bus system 1705. It is understood that the bus system 1705 is used to achieve connection and communication between these components. In addition to the data bus, the bus system 1705 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, the bus system 1705 is not described in detail. Figure 5 Various buses are labeled as bus system 1705.

[0089] Among them, the user interface 1703 may include a display, a keyboard or a pointing device (for example, a mouse, a trackball, a touch pad or a touch screen, etc. It can be understood that the memory 1702 in the embodiment of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories.

[0090] In the embodiment of the present invention, by calling the program or instruction stored in the memory 1702, specifically, the program or instruction stored in the application 17022, the processor 1701 is used to execute the method steps provided by each method embodiment.

[0091] In some embodiments, the memory 1702 stores the following elements, executable units or data structures, or a subset thereof, or an extended set thereof: an operating system 17021 and an application program 17022 .

[0092] The operating system 17021 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., which are used to implement various basic services and process hardware-based tasks. The application 17022 includes various application programs, such as a media player (Media Player), a browser (Browser), etc., which are used to implement various application services. The program for implementing the method of the embodiment of the present invention can be included in the application 17022.

[0093] Embodiment 4:

[0094] In this embodiment, a storage medium is provided, characterized in that the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the Q offset processing method using well-ground joint data.

[0095] The method steps described in conjunction with the first embodiment disclosed herein may be implemented using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0096] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A Q-offset processing method using well-ground joint data, characterized in that: Specifically include: Obtain the well DAS data and ground 3D seismic data under the same source signal in the work area; The Q value curves from shallow to deep in the wellbore are calculated based on the DAS data in the well and the 3D seismic data on the ground; Use the Q value curve in the well to calibrate the Q value accuracy of the surface Q value curve, and conduct detailed layered evaluation and analysis; Pick up the layer information along the strong energy phase axis in the ground three-dimensional seismic data, and use the ground three-dimensional seismic data to calculate the spatial three-dimensional Q volume; The seismic source is excited at different locations on the ground, and the precision correction factor is calculated using the DAS data in the well at different offset distances; Using the well DAS and surface 3D seismic data received from the same source, a high-precision 3D Q-body is established by combining the two types of data information, and the velocity model is optimized simultaneously; High-precision 3D Q-body and velocity model are input to perform Q-migration processing on ground seismic data, thereby simultaneously improving the imaging accuracy and resolution of seismic data.

2. The Q-offset processing method using well-ground joint data according to claim 1, characterized in that: The Q value curves from shallow to deep at the wellbore location are calculated based on the DAS data in the well and the 3D seismic data on the ground, including: The fine Q value curve QDAS at the wellbore position is calculated based on the DAS data in the well using the attenuation method of amplitude, frequency and phase. well (i), i = 1, 2, 3...N, i is the depth sampling interval, N is the depth value, unit is m; The rough Q value curve Q3D at the wellbore location is calculated based on the ground 3D seismic data using the attenuation method of amplitude, frequency and phase. well (j), j = 1, 2, 3...M, j is the depth sampling interval, M is the depth value, unit is m.

3. The Q-offset processing method using well-ground joint data according to claim 2 is characterized in that: The Q value curve in the well is used to calibrate the Q value accuracy of the surface Q value curve, and a detailed layered evaluation and analysis is performed, including: By analyzing the similarity of the Q value curves at two wellbore locations; The precision correction factor of the well-ground joint Q value at the wellbore is calculated; The rough Q value curve is corrected using the wellbore joint Q value accuracy correction factor; Through the analysis of hierarchical accuracy judgment of two Q value curves; The well-ground joint Q value matching stratification factor at the wellbore is calculated; The corrected rough Q value curve is stratified using the wellbore joint Q value matching stratification factor.

4. The Q-offset processing method using well-ground joint data according to claim 3 is characterized in that: Pick up layer information along the strong energy phase axis in the ground 3D seismic data, and use the ground 3D seismic data to calculate the spatial 3D Q volume, including: The well-ground joint Q value matching stratification factor at the wellbore position is used as the picking quantity plate to obtain the spatial three-dimensional stratification factor; According to the spatial three-dimensional stratification factor, the Q value of each layer is calculated using the ground three-dimensional seismic data to achieve the Q value filling of the three-dimensional stratified model and obtain the Q volume Q3D of the three-dimensional seismic data. area ; In the process of calculating the three-dimensional Q body in space, the Q value accuracy correction factor QCor is used to correct the wellbore joint Q value. well Improve the accuracy of spatial three-dimensional Q-body; Establish an initial stratified three-dimensional Q-body model of the work area space.

5. The Q-offset processing method using well-ground joint data according to claim 4 is characterized in that: The seismic source is excited at different locations on the ground, and the precision correction factors are calculated using the DAS data in the well at different offsets, including: In the Q-body layered initial model, the propagation paths of DAS data in wells with different offsets are calculated respectively, so as to obtain the correction factors in three-dimensional space; Stimulate artificial seismic sources on the ground, so that seismic waves propagate from the ground to the underground, passing through various strata from shallow to deep in sequence; The initial model of Q-body stratification is corrected according to the propagation path of DAS data in wells with different offsets; Based on the Q value calculation from near to far and from shallow to deep and the layer stripping rule, the three-dimensional well-ground joint Q value accuracy correction factor is obtained.

6. The Q-offset processing method using well-ground joint data according to claim 5 is characterized in that: Using the well DAS and ground 3D seismic data received from the same source, a high-precision 3D Q-body is established by combining the two types of data information, and the velocity model is optimized simultaneously, including: The 3D Q-body makes full use of both the DAS data in the well and the 3D seismic data on the ground. The advantage of the DAS data in the well in calculating the Q value accurately is brought into play at the wellbore, and the 3D seismic data on the ground is used to establish the initial layered model of the 3D Q-body. Then the Q value accuracy is improved through DAS data in wells with different offset distances; At the same time, the velocity model is optimized based on the established three-dimensional Q-body.

7. The Q-offset processing method using well-ground joint data according to claim 5 is characterized in that: Input high-precision 3D Q-body and velocity model to perform Q-migration processing on ground seismic data, and simultaneously improve the imaging accuracy and resolution of seismic data, including: Based on the high-precision 3D Q-body and the velocity model jointly established by the DAS in the well and the 3D seismic on the ground, Q migration imaging is performed layer by layer from shallow to deep. According to the spatial three-dimensional layering factor, the three-dimensional Q volume and the optimized three-dimensional velocity model are input to perform Q migration depth imaging on the seismic data layer by layer, and the amplitude, frequency and phase of the seismic data are synchronously restored layer by layer; The final output is the seismic data after Q compensation processing, which simultaneously improves the resolution of seismic data and the accuracy of deep imaging.

8. A device for Q-shift processing using well-ground joint data, characterized in that: include: Data acquisition module, used to acquire the well DAS data and ground 3D seismic data under the same source signal in the work area; The Q value calculation module is used to calculate the Q value curves from shallow to deep at the wellbore position according to the DAS data in the well and the ground three-dimensional seismic data; The correction analysis module is used to use the Q value curve in the well to calibrate the Q value accuracy of the surface Q value curve, and perform detailed layered evaluation and analysis; A spatial three-dimensional Q-body calculation module is used to pick up layer information along the strong energy event axis in the ground three-dimensional seismic data and calculate the spatial three-dimensional Q-body using the ground three-dimensional seismic data; The precision correction factor calculation module excites the seismic source at different locations on the ground and calculates the precision correction factor using the DAS data in the well at different offset distances; The optimization module uses the well DAS and ground 3D seismic data received from the same source to establish a high-precision 3D Q-body that combines the two types of data information and simultaneously optimizes the velocity model; The processing module inputs high-precision three-dimensional Q-body and velocity model, performs Q-migration processing on ground seismic data, and simultaneously improves the imaging accuracy and resolution of seismic data.

9. An electronic device, characterized in that: include: A processor and a memory, wherein the processor is used to execute a program stored in the memory for performing Q offset processing using well-ground combined data, so as to implement the Q offset processing method using well-ground combined data as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the Q offset processing method using well-ground joint data as described in any one of claims 1 to 7.

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