A frequency division and zone identification method for complex formations

Abstract

The present invention discloses a frequency division and zone identification method for complex strata, including the steps of: S10, predicting the formation distribution; S20, calibrating the well-seismic synthetic record; S30, forward modeling analysis; S40, reconstructing the frequency-weighted seismic data; S50, automatically tracking and interpreting by frequency division and zone: according to the formation distribution prediction result, applying different frequency data volumes based on the well-seismic calibration result and the forward modeling analysis result to achieve automatic horizon tracking and identification. The present invention can reduce the identification error and cope with the accurate identification of complex strata.

Description

Technical Field

[0001] The present invention belongs to the technical field of formation detection, and particularly relates to a frequency division and zone identification method for complex formations. Background Art

[0002] Regarding the stratigraphic contact types of unconformities, due to the variable lithology of the underlying strata of the unconformity, the diverse lithological combination types in contact with the upper and lower parts of the unconformity, and the complex impedance interfaces, the characteristics of the stratigraphic interfaces are not obvious in seismic responses, the reflection interfaces are not clear, and it is difficult to ensure the accuracy of seismic interpretation.

[0003] Taking the Qixia Formation in the GST area as an example, the Liangshan Formation (P1l) and Qixia Formation (P1q) of the Lower Permian in the GST area directly cover the strata of different ages such as the Cambrian (ε), Ordovician (O), and Silurian (S). And from the southeast to the northwest, the strata show a distribution characteristic of getting older from new. Under this paleogeomorphic background, a large-scale marine transgression occurred in the Permian, and the deposition of the Liangshan Formation and Qixia Formation began. Due to the complex distribution and variable lithology of the underlying strata of the Qixia Formation in the study area, the characteristics of the internal small layer interfaces of Qixia are not obvious in seismic responses, the reflection interfaces are not clear, and it is difficult to make a fine interpretation of the bottom of Qixia and the bottom of the second member of Qixia. The calibration results show that the calibration positions of the bottom of Qixia vary greatly, which can change from the trough to - / + zero point, and some are peaks. The calibration positions are controlled by the changes in the contact strata with the underlying strata. Currently, the seismic interpretation for this area is completely based on the method of tracing seismic data reflection isochrones, thus ignoring the well-seismic error. Since the reflection interface is quite different from the actual stratigraphic interface, obvious errors exist in the later paleogeomorphic research, which in turn affects the reliability of the later well location target optimization. Summary of the Invention

[0004] In order to solve the above problems, the present invention proposes a frequency division and zone identification method for complex formations, which can reduce the identification error and achieve accurate identification of complex formations.

[0005] To achieve the above object, the technical solution adopted by the present invention is: a frequency division and zone identification method for complex formations, including the steps of:

[0006] S10, Formation distribution prediction: According to the drilled wells, single-well sequence division and cross-well formation correlation interpretation, determine the formation and lithological combination types in different well areas, and obtain the formation distribution prediction result;

[0007] S20, Well-seismic synthetic record calibration: According to the formation distribution prediction result, determine the impedance interfaces for different formation and lithological contact relationships; according to different impedance interfaces, carry out variable wavelet synthetic record calibration for each well, determine the sensitive frequencies and corresponding seismic reflection characteristics under different formation contact relationships and their corresponding lithological combinations and impedance interface conditions, and obtain the well-seismic calibration result;

[0008] S30, Forward modeling analysis: Based on the prediction results of formation distribution and well-seismic calibration results, establish a geological model of formation and lithology contacts. According to the velocity and density parameters of different lithologies, further verify the contact relationships of different formations, their corresponding lithology combinations, and the sensitive frequencies and corresponding seismic reflection characteristics under impedance interface conditions through forward modeling, and obtain the forward modeling analysis results;

[0009] S40, Seismic data frequency-divided body reconstruction: It includes spectral decomposition to form multiple frequency-divided bodies by wavelet frequency division of seismic data, and frequency-divided reconstruction to form seismic data with bandwidth and main frequency through characteristic reconstruction analysis of multiple frequency-divided bodies, and obtain different frequency data volumes;

[0010] S50, Automatic tracking and interpretation by area and frequency division: For the prediction results of formation distribution, apply different frequency data volumes according to well-seismic calibration results and forward modeling analysis results to realize automatic horizon tracking and identification.

[0011] Furthermore, according to the drilled wells, single-well sequence division and cross-well formation correlation and interpretation, determine the formation and lithology combination types in different well areas, including the steps:

[0012] Based on the determined drilled wells, divide the formation into different sequence units according to sedimentary characteristics and geological records, and clarify the identification marks of different sequence boundaries;

[0013] Single-well sequence division: Starting from downhole data, use the lithology combination of the formation, stratigraphic markers, core observations, and well logging interpretation analysis. Through factors such as electrical properties, lithology, and lithofacies changes, based on sequence stratigraphic analysis of the natural gamma curve and resistivity curve in the single-well well logging curve, establish a sequence stratigraphic division scheme, and clarify the formation, lithology change characteristics, and reservoir development intervals;

[0014] Cross-well formation correlation: On the basis of single-well sequence division, sort out the curve characteristics of single-well sequence boundaries of all wells, summarize the comparability of the natural gamma curve and resistivity curve of the sequence boundary in the whole area, and establish a sequence stratigraphic framework accordingly. Determine the lateral correlation characteristics of each formation horizontally. At the same time, according to the results of cross-well sequence correlation analysis, adjust the wells with unreasonable single-well sequence division.

[0015] Furthermore, according to the prediction results of formation distribution, determine the impedance interface for different formation and lithology contact relationships, including the steps:

[0016] Analysis of lithology contact relationships at sequence boundaries: According to the results of single-well sequence division and cross-well sequence correlation, sort out the lithology characteristics of the overlying and underlying formations at the Permian formation boundaries of different wells, obtain the types of lithology contact relationships at the Permian formation boundaries in the identification area, and the planar distribution ranges of single wells with different lithology combinations;

[0017] Analysis of sequence interfaces and impedance interfaces: Based on the analysis of lithological differences at sequence interfaces in different well areas, impedance values of different lithologies are statistically analyzed according to well logging data, so as to further classify sequence interfaces from the perspective of impedance changes.

[0018] Furthermore, for each well, variable wavelet synthetic record calibration is carried out according to different impedance interfaces to determine different stratigraphic contact relationships, their corresponding lithological combinations, sensitive frequencies and corresponding seismic reflection characteristics under impedance interface conditions, including the steps:

[0019] For the classification results of lithology and impedance at sequence interfaces, well-seismic synthetic record calibration is carried out by dividing regions and frequencies to clarify sensitive frequencies and corresponding seismic reflection characteristics under impedance interface conditions corresponding to different lithological combinations.

[0020] Furthermore, according to the prediction results of stratigraphic distribution and well-seismic calibration results, a geological model of stratigraphic and lithological contacts is established, including the steps:

[0021] According to the stratigraphic contact types revealed by all wells in the study area, including lithology, thickness, contact relationship, P-wave velocity, S-wave velocity and density, a geological model is established based on the actual drilled wells.

[0022] Furthermore, according to velocity and density parameters of different lithologies, the sensitive frequencies and corresponding seismic reflection characteristics under different stratigraphic contact relationships, their corresponding lithological combinations and impedance interface conditions are further verified through forward modeling, including the steps: Establish a geological model based on the actual drilled wells, and according to the analysis results of different lithological contact types and their corresponding sensitive frequencies of impedance interfaces, carry out forward modeling analysis on the corresponding geological model using this frequency to further clarify the seismic reflection characteristics of stratigraphic interfaces under different model conditions.

[0023] Furthermore, spectral decomposition includes the steps: Convert seismic data from the time domain to the frequency domain through wavelet transform, decompose the seismic data into tuning bodies in different frequency domains, and the generated amplitude spectrum can identify the time thickness changes of the strata, and the phase spectrum detects the geological discontinuities in the lateral direction of the geological body; Use the tuning frequency amplitude data volume slice to determine the spatio-temporal distribution of anomalies; Use the tuning frequency instantaneous phase data volume slice to determine the boundaries of anomalies;

[0024] Frequency division reconstruction analyzes seismic data, selects frequency division data volumes that can reflect different geological targets, and then reconstructs the frequency division data volumes in the frequency domain to finally form seismic data with bandwidth and dominant frequency.

[0025] Furthermore, automatic tracking and interpretation by dividing regions and frequencies: For the prediction results of stratigraphic distribution, according to well-seismic calibration results and forward modeling analysis results, different frequency data volumes are applied to realize automatic horizon tracking and identification, including the steps:

[0026] Based on the comprehensively determined sensitive frequencies corresponding to different lithology combinations and their impedance interfaces, as well as the seismic reflection characteristics of the formation interfaces, the frequency-divided reconstructed data are optimized, and the formation tracking scheme is calibrated and determined.

[0027] For the well areas with different lithology combinations and their impedance interface distributions, the corresponding sensitive frequency-divided reconstructed data are selected to carry out seed point interpretation.

[0028] Based on the seed points, the automatic tracking algorithm is applied to track each formation interface with the formation distribution range as the boundary.

[0029] Horizon splicing: For the interpretation results of different well areas and different data volumes, according to the formation distribution range, the interpretation results of each formation interface are spliced to form the interpretation results of the whole area.

[0030] Beneficial effects of adopting this technical solution:

[0031] The present invention proposes a frequency-divided and area-divided interpretation scheme for complex formations, complex lithologies, and complex impedance contact formation interfaces, effectively improving the accuracy of horizon interpretation, thereby further improving the accuracy of late paleogeomorphic characterization and reservoir prediction results, effectively improving the success rate of well location deployment, and reducing production costs.

[0032] The present invention is based on the genetic method. By analyzing well data, the reasons for the complexity of the seismic reflection characteristics of the formation are clarified. Starting from this, through comprehensive calibration and forward modeling, the seismic response characteristics of stable and traceable formation interfaces are clarified. By using the automatic tracking technology method, the uncertainty of the interpretation results caused by manual intervention is effectively reduced, and the interpretation results are more objective. Brief Description of the Drawings

[0033] Figure 1 It is a schematic flow chart of a frequency-divided and area-divided identification method for complex formations according to the present invention;

[0034] Figure 2 It is a schematic diagram of sequence stratigraphic division of Well X in the embodiment of the present invention;

[0035] Figure 3 It is a schematic diagram of sequence stratigraphic division of Well Y in the embodiment of the present invention;

[0036] Figure 4 It is a schematic diagram of the parameters and formation structure type of Model 1 in the embodiment of the present invention;

[0037] Figure 5 It is a schematic diagram of the parameters and formation structure type of Model 2 in the embodiment of the present invention;

[0038] Figure 6 It is a schematic diagram of the parameters and formation structure type of Model 3 in the embodiment of the present invention;

[0039] Figure 7This is a schematic flowchart of the processing procedure for frequency division reconstruction in an embodiment of the present invention. Detailed implementation manners

[0040] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described below with reference to the accompanying drawings.

[0041] In this embodiment, referring to Figure 1 as shown, the present invention proposes a method for frequency division and zone identification for complex strata, including the steps of:

[0042] S10, Formation distribution prediction: According to the drilled wells, single-well sequence division and cross-well formation correlation and interpretation, determine the formation and lithology combination types in different well areas, and obtain the formation distribution prediction result;

[0043] S20, Well-seismic synthetic record calibration: According to the formation distribution prediction result, determine the impedance interfaces for different formation and lithology contact relationships; according to different impedance interfaces, conduct variable wavelet synthetic record calibration for each well to determine the sensitive frequencies and corresponding seismic reflection characteristics under different formation contact relationships and their corresponding lithology combinations and impedance interface conditions, and obtain the well-seismic calibration result;

[0044] S30, Forward modeling analysis: According to the formation distribution prediction result and the well-seismic calibration result, establish a geological model of formation and lithology contact. According to different lithology velocity and density parameters, further verify the sensitive frequencies and corresponding seismic reflection characteristics under different formation contact relationships and their corresponding lithology combinations and impedance interface conditions through forward modeling, and obtain the forward modeling analysis result;

[0045] S40, Seismic data frequency division and weight reconstruction: including spectral decomposition to form multiple frequency division bodies by wavelet frequency division of seismic data, and frequency division reconstruction to form seismic data with bandwidth and main frequency by characteristic reconstruction analysis of multiple frequency division bodies, and obtain different frequency data volumes;

[0046] S50, Automatic tracking and interpretation of zone and frequency division: For the formation distribution prediction result, according to the well-seismic calibration result and the forward modeling analysis result, apply different frequency data volumes to realize automatic horizon tracking and identification.

[0047] As an optimized solution of the above embodiment, according to the drilled wells, single-well sequence division and cross-well formation correlation and interpretation, determining the formation and lithology combination types in different well areas includes the steps of:

[0048] According to the determined drilled wells, divide the formation into different sequence units according to sedimentary characteristics and geological records, and clarify the identification marks of different formation series interfaces.

[0049] Taking the Lower Permian in the GST area as an example:

[0050] Based on the regional weathering crust caused by the Yunnan Movement, the top and bottom interfaces of the Lower Permian Liangshan Formation (P1l) were formed with the transgression of seawater from the northwest and southeast directions of the basin, resulting in the Liangshan Formation strata mainly composed of coal-bearing clastic rock deposits, covering the Lower Silurian Longmaxi Formation (S1l), Middle Ordovician Baota Formation (Q2b), Shizipu Formation (Q2s), Lower Ordovician Meitan Formation (Q1m), Honghuayuan Formation (Q1h) and Tongzi Formation (Q1t), or older Cambrian (∈) strata within the working area. It is the product of the land-to-sea conversion in the initial stage of transgression.

[0051] The angular unconformity interface between the Lower Permian Liangshan Formation and the underlying strata is a typical first-order sequence interface. This interface is a diachronous stratigraphic surface, covering multiple strata including the Silurian, Ordovician, and Cambrian. With the rise of sea level, the inundation range of seawater expanded, and the sedimentary environment changed to the broad carbonate platform deposition of the Qixia Formation. The clastic sedimentary argillaceous limestone and calcareous shale of the Liangshan Formation gradually transitioned upward to the platform carbonate rock deposition of the Qixia Formation, which is the product of a continuous transgression process. Therefore, the interface between the Liangshan Formation and the Qixia Formation is not a third-order sequence interface.

[0052] Interface between the Lower Permian Qixia Formation and the first member of the Maokou Formation:

[0053] Within the Lower Permian Qixia Formation, in strata where the unconformity surface is not well-developed or difficult to identify, the key to dividing and correlating sequence stratigraphy is to accurately identify the lithology-lithofacies conversion surface. Through comprehensive comparison of various types of logging curves, it is found that using a logging response sequence mainly based on the natural gamma (GR) curve, combined with the resistivity (RT) curve and the flushed zone resistivity (RXO) curve, can more accurately divide and correlate the sequence stratigraphy within the Qixia Formation in the working area. The Qixia Formation changes from the bottom with micritic limestone and grain limestone with a relatively high clay content to dolomite and grain limestone in the upper part, forming a lithology-lithofacies conversion surface within the Qixia Formation. This conversion surface is marked by the appearance of dolomite in most wells. Between the Qixia Formation and the Maokou Formation, there is a second lithology-lithofacies conversion surface, which is manifested as the light gray grain limestone of the Qixia Formation changing to the "oolitic" limestone with a relatively high clay content developed in the first member of the Maokou Formation, and the two are in a parallel unconformity contact.

[0054] Single-well sequence division: Starting from downhole data, using the lithological combination of strata, stratigraphic markers, core observations, and logging interpretation analysis, through factors such as electrical properties, lithology, and lithofacies changes, based on the sequence stratigraphic analysis of the natural gamma curve and resistivity curve in the single-well logging curve, establish a sequence stratigraphic division scheme to clarify the characteristics of stratigraphic and lithological changes and the reservoir development intervals.

[0055] Taking Well X and Well Y as examples ( Figure 2 、 Figure 3), the GR of the first section of the Liangshan Formation + the Qixia Formation shows a continuous decreasing trend, and the RT / RXO curve is bell-shaped; the GR curve of the second section of the Qixia Formation changes to a smooth tooth-like low value, and the RT / RXO curve shows a finger-like high value. The overall electrical characteristics show that the GR curve decreases from the first section to the second section of the Qixia Formation; the lithology of the high GR and low resistivity section at the bottom is dark gray mud-crystal limestone, which is a deep-water low-energy sedimentary environment. Petrological signs: The lithology of each cycle gradually changes from mud-crystal bioclastic limestone to bright crystal granular limestone from bottom to top, and the lithology changes at the cycle interface are clear. Logging signs: The GR of each cycle shows a box-like feature of relatively high values changing from fingers to low values, and the resistivity gradually decreases from bottom to top. Geochemical signs: Both carbon isotopes and trace elements near the interface have mutation characteristics.

[0056] Well-connected stratigraphic comparison: Based on the single-well sequence division, the characteristics of the sequence interface curves of all wells are sorted out, and the comparability of the natural gamma curves and resistivity curves of the sequence interface in the entire area are summarized. Based on this, a sequence stratigraphic framework is established to determine the lateral comparison characteristics of each stratum. At the same time, according to the results of the sequence well-connected comparison analysis, adjustments are made to the wells with unreasonable single-well sequence divisions.

[0057] As an optimization scheme of the above embodiment, according to the formation distribution prediction result, the impedance interface is determined for different formations and lithology contact relationships, including the following steps:

[0058] Analysis of lithologic contact relationship of sequence interface: Based on the results of single well sequence division and well-connected sequence comparison, the lithologic characteristics of the overlying and underlying strata of the Permian stratigraphic interface of different wells are sorted out to obtain the lithologic contact relationship type of the Permian stratigraphic interface in the identified area, as well as the plane distribution range of single wells with different lithologic combination types;

[0059] Taking the GST area as an example, the types are divided into five categories according to the different underlying contact strata of the Permian, namely, contact Longmaxi Formation mudstone, Pagoda Formation-Shizipu Formation limestone, Meitan Formation mudstone, limestone contact, Tongzi Formation-Honghuayuan Formation limestone and Cambrian dolomite.

[0060] Sequence interface impedance analysis: Based on the analysis of lithology differences at sequence interfaces in different well areas, the impedance values of different lithologies are statistically analyzed according to logging data, so as to further classify the sequence interfaces from the perspective of impedance changes.

[0061] According to the impedance relationship of different lithological interfaces, they are combined into two categories: the first category is that the Qixia Formation limestone contacts the Liangshan Formation thin mudstone and the Silurian mudstone, and the impedance interface is high impedance contact and low impedance, and the impedance difference is large; the second category is that the Qixia Formation limestone contacts the Liangshan Formation thin mudstone and the Ordovician Meitan Formation limestone, showing the characteristics of high impedance contact and medium-low impedance, and the impedance interface is relatively large; the third category is that the Qixia Formation limestone contacts the Ordovician or Cambrian thick limestone, showing high impedance contact and high impedance, and the impedance difference is small.

[0062] As an optimized solution for the above embodiments, according to different impedance interfaces, variable wavelet synthetic record calibration is carried out for each well to determine the sensitive frequencies and corresponding seismic reflection characteristics under different formation contact relationships, their corresponding lithologic combinations and impedance interface conditions, including the steps:

[0063] For the lithology and impedance classification results of sequence interfaces, well-seismic synthetic record calibration is carried out by dividing regions and frequencies to clarify the sensitive frequencies and corresponding seismic reflection characteristics under the impedance interface conditions corresponding to different lithologic combinations.

[0064] (1) Analysis of high impedance / low impedance interface characteristics:

[0065] Taking the Lower Silurian Longmaxi Formation shale underlying the Permian as an example, a total of 8 wells of this type have been drilled. For each well, synthetic records are made using sonic curves and density curves. The main frequency of the synthetic record wavelet is of the Ricker wavelet type, gradually changing from 20 Hz to 45 Hz. The formation interface characteristics under different frequency conditions are analyzed and summarized to optimize the most sensitive frequency. Under this frequency condition, the Qibi and Qier bottoms are the most stable and can be traced. The analysis results show that the sensitive frequency of Qibi is 45 Hz, with a trough reflection; the sensitive frequency of Qier bottom is 45 Hz, showing a zero-phase reflection under the peak.

[0066] (2) Analysis of high impedance / mid-low impedance interface characteristics:

[0067] For the underlying contact formation of the Permian being the Meitan Formation mudstone or marlstone, a total of 35 wells of this type have been drilled. For these 35 wells of this type, variable wavelet synthetic record calibration and comparison are carried out according to sonic curves and density curves. The most sensitive frequencies of the Qibi and Qier bottoms of the 35 wells and the most stable seismic reflection characteristics under the corresponding conditions are statistically analyzed and optimized, so as to achieve automatic tracking. The calibration results show that when the underlying contact formation of the Qixia Formation is the Meitan Formation mudstone or marlstone, the sensitive frequencies of both Qibi and Qier bottom are 40 Hz - 55 Hz.

[0068] (3) Analysis of high impedance / high impedance interface characteristics:

[0069] When the underlying contact formation of the Permian is the limestone of the Baota Formation, Shizipu Formation, Tongzi Formation and Honghuayuan Formation or the Cambrian dolomite, the impedance interface type is the high impedance and high impedance docking mode. Using the same method, variable wavelet synthetic record calibration is carried out for 36 wells of this type; the results show that when the main frequency of the seismic wavelet is 15 Hz - 20 Hz, the bottom of Qixia shows a zero-phase on the peak, and as the seismic main frequency increases, the bottom of Qixia gradually shifts towards the trough; when the main frequency of the seismic wavelet is 40 Hz - 55 Hz, the bottom of the second member of Qixia shows a zero-phase under the peak and is relatively stable. It shows that when the underlying contact formation of the Permian is limestone and the impedance interface is high impedance / high impedance, the sensitive frequency of Qibi is 20 Hz, while the sensitive frequency of Qier bottom is 40 Hz - 45 Hz.

[0070] As an optimized solution of the above embodiments, according to the formation distribution prediction results and well-seismic calibration results, a geological model of formation and lithology contact is established, including the steps:

[0071] According to the formation contact types revealed by all wells in the study area, including lithology, thickness, contact relationship, P-wave velocity, S-wave velocity and density, a geological model is established based on the actual drilled wells.

[0072] Taking the GST area as an example, the following three geological models are proposed:

[0073] Model 1: The underlying formation contacts the P1l thin-layer mudstone and the S1l mud shale or directly contacts the S1l mud shale. The formations of Mao 2, Mao 3, Mao 1, Qi 2 and Qi 1 are all conformably contacted. The contacts between Qi 1 and Liangshan Formation, Qi 1 and Longmaxi Formation, and Liangshan and Longmaxi are all unconformably contacted. See the relevant thickness, velocity and density parameters in Figure 4 .

[0074] Model 2: The underlying formation contacts the P1l thin-layer mudstone and the O1m limestone or directly contacts the O1m mudstone. See the contact mode and relevant velocity and density parameters in Figure 5 .

[0075] Model 3: The underlying formation contacts the P1l thin-layer mudstone and the O1t / O1h / O3b / O2s limestone and Cambrian dolomite. See the contact mode and relevant velocity and density parameters in Figure 6 .

[0076] As an optimized solution of the above embodiments, according to the velocity and density parameters of different lithologies, through forward modeling, the different formation contact relationships and their corresponding lithology combinations and sensitive frequencies and corresponding seismic reflection characteristics under impedance interface conditions are further verified, including the steps: Establish a geological model based on the actual drilled wells. According to the different lithology contact types and the analysis results of the sensitive frequencies of the corresponding impedance interfaces, apply this frequency to carry out forward modeling analysis for the corresponding geological model, and further clarify the seismic reflection characteristics of the formation interfaces under different model conditions.

[0077] Based on the above two major categories and five sub-categories of formation forward models, it is shown again that when the underlying formation is a high-impedance limestone area and the seismic main frequency is 20 Hz, the bottom of Qi can be better identified, showing zero-phase on the wave peak; the bottom of Qi 2 can be better identified on the seismic data of 45 Hz, showing zero-phase under the wave peak. When the underlying formation is a low-impedance mudstone area and the seismic main frequency is 45 Hz, the bottom of Qi and the bottom of Qi 2 can be better identified, showing trough reflection and zero-phase reflection under the wave peak respectively.

[0078] As an optimized solution of the above embodiments, such as Figure 7As shown in the figure, spectral decomposition includes the steps of: converting seismic data from the time domain to the frequency domain through wavelet transform, decomposing the seismic data into tuning bodies in different frequency domains, and then the generated amplitude spectrum can identify the change in the time thickness of the formation, and the phase spectrum can detect the geological discontinuity in the lateral direction of the geological body; using the slice of the tuning frequency amplitude data volume to determine the spatio-temporal distribution of the abnormal body; using the slice of the tuning frequency instantaneous phase data volume to determine the boundary of the abnormal body.

[0079] Frequency division reconstruction analyzes seismic data, selects frequency division data volumes that can reflect different geological targets, and then reconstructs the frequency division data volumes in the frequency domain to finally form seismic data with bandwidth and main frequency.

[0080] As an optimized solution of the above embodiment, partitioned frequency division automatic tracking interpretation: For the prediction result of formation distribution, according to the well-seismic calibration result and the forward modeling analysis result, different frequency data volumes are applied to realize automatic horizon tracking and identification, including the steps of:

[0081] Comprehensively determine the different lithology combinations, the sensitive frequencies corresponding to their impedance interfaces, and the seismic reflection characteristics of the formation interfaces, optimize the frequency division reconstruction data, calibrate and determine the formation tracking scheme;

[0082] For well areas with different lithology combinations and their impedance interface distributions, select the corresponding sensitive frequency division reconstruction data and carry out seed point interpretation;

[0083] Based on the seed points, apply the automatic tracking algorithm and track each formation interface with the formation distribution range as the boundary;

[0084] Horizon splicing: For the interpretation results of different well areas and different data volumes, according to the formation distribution range, splice the interpretation results of each formation interface to form the interpretation result of the whole area.

[0085] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A frequency division and zone identification method for complex formations, characterized in that Including the steps: S10, Formation distribution prediction: Based on the drilled wells, single-well sequence division and cross-well formation correlation and interpretation, determine the formation and lithology combination types in different well areas to obtain the formation distribution prediction results; S20, Well-seismic synthetic record calibration: According to the formation distribution prediction results, determine the impedance interfaces for different formation and lithology contact relationships; for each well, carry out variable wavelet synthetic record calibration based on different impedance interfaces to determine the sensitive frequencies and corresponding seismic reflection characteristics under different formation contact relationships and their corresponding lithology combinations and impedance interface conditions to obtain the well-seismic calibration results; S30, Forward modeling analysis: According to the formation distribution prediction results and well-seismic calibration results, establish a geological model of formation and lithology contacts. Based on different lithology velocity and density parameters, further verify the sensitive frequencies and corresponding seismic reflection characteristics under different formation contact relationships and their corresponding lithology combinations and impedance interface conditions through forward modeling to obtain the forward modeling analysis results; S40, Seismic data frequency-divided body reconstruction: including spectral decomposition to form multiple frequency-divided bodies by wavelet frequency division of seismic data, and frequency-divided reconstruction to form seismic data with bandwidth and dominant frequency through characteristic reconstruction analysis of multiple frequency-divided bodies to obtain different frequency data bodies; S50, Zone-based and frequency-divided automatic tracking and interpretation: For the formation distribution prediction results, apply different frequency data bodies according to the well-seismic calibration results and forward modeling analysis results to achieve automatic horizon tracking and identification.

2. The frequency division and zone identification method for complex formations according to claim 1, wherein Based on the drilled wells, single-well sequence division and cross-well formation correlation and interpretation, determine the formation and lithology combination types in different well areas, including the steps: According to the determined drilled wells, divide the formation into different sequence units based on sedimentary characteristics and geological records, and clarify the identification marks of different formation system interfaces; Single-well sequence division: Starting from downhole data, using the lithology combination of the formation, stratigraphic markers, core observations, and well logging interpretation analysis, through several factors such as electrical properties, lithology, and lithofacies changes, based on the sequence stratigraphic analysis of the natural gamma curve and resistivity curve in the single-well well logging curve, establish a sequence stratigraphic division scheme, and clarify the formation and lithology change characteristics and reservoir development intervals; Cross-well formation correlation: On the basis of single-well sequence division, sort out the curve characteristics of single-well sequence interfaces of all wells, summarize the comparability of the natural gamma curve and resistivity curve of the sequence interface in the whole area, and accordingly establish a sequence stratigraphic framework to determine the lateral correlation characteristics of each formation horizontally. At the same time, according to the cross-well sequence correlation analysis results, adjust the wells with unreasonable single-well sequence division.

3. A frequency division and zone identification method for complex formations according to claim 2, characterized in that, According to the formation distribution prediction results, determine the impedance interfaces for different formation and lithology contact relationships, including the steps: Analysis of lithology contact relationships at sequence interfaces: According to the single-well sequence division and cross-well sequence correlation results, sort out the lithology characteristics of the overlying and underlying formations at the Permian formation interfaces in different wells to obtain the lithology contact relationship types at the Permian formation interfaces in the identification area, as well as the planar distribution ranges of single wells with different lithology combination types; Analysis of impedance interfaces at sequence interfaces: On the basis of the lithology difference analysis of sequence interfaces in different well areas, statistically analyze the impedance values of different lithologies according to well logging data, so as to further classify the sequence interfaces from the perspective of impedance changes.

4. The frequency division and zone identification method for complex formations according to claim 3, characterized in that For each well, variable wavelet synthetic record calibration is carried out according to different impedance interfaces to determine different stratigraphic contact relationships, their corresponding lithologic combinations, sensitive frequencies and corresponding seismic reflection characteristics under impedance interface conditions, including the steps: For the lithology and impedance classification results of sequence interfaces, well-seismic synthetic record calibration is carried out by region and frequency to clarify the sensitive frequencies and corresponding seismic reflection characteristics under impedance interface conditions corresponding to different lithologic combinations.

5. A frequency division and zone identification method for complex formations according to claim 4, characterized in that According to the formation distribution prediction results and well-seismic calibration results, a geological model of stratigraphic and lithologic contacts is established, including the steps: According to the stratigraphic contact types revealed by all wells in the study area, including lithology, thickness, contact relationship, P-wave velocity, S-wave velocity and density, a geological model is established based on the actual drilled wells.

6. The frequency division and zone identification method for complex formations according to claim 5, wherein, According to the velocity and density parameters of different lithologies, the sensitive frequencies and corresponding seismic reflection characteristics under different stratigraphic contact relationships, their corresponding lithologic combinations and impedance interface conditions are further verified through forward modeling, including the steps: A geological model is established based on the actual drilled wells. According to the analysis results of sensitive frequencies of different lithologic contact types and their corresponding impedance interfaces, forward modeling analysis is carried out on the corresponding geological model using this frequency to further clarify the seismic reflection characteristics of stratigraphic interfaces under different model conditions.

7. A frequency division and zone identification method for complex formations according to claim 1, characterized in that Spectrum decomposition includes the steps: The seismic data is transformed from the time domain to the frequency domain through wavelet transform, and the seismic data is decomposed into tuning bodies in different frequency domains. The amplitude spectrum generated after transformation can identify the time thickness changes of the formation, and the phase spectrum detects the geological discontinuities in the lateral direction of the geological body; Using the tuning frequency amplitude data volume slice, the spatio-temporal distribution of abnormal bodies is determined; Using the tuning frequency instantaneous phase data volume slice, the boundaries of abnormal bodies are determined; Frequency-divided reconstruction selects the frequency-divided data volume that can reflect different geological targets through the analysis of seismic data, and then reconstructs the frequency-divided data volume in the frequency domain to finally form seismic data with bandwidth and dominant frequency.

8. A frequency division and zone identification method for complex formations according to claim 1, characterized in that Region and frequency automatic tracking interpretation: For the formation distribution prediction results, according to the well-seismic calibration results and forward modeling analysis results, different frequency data volumes are applied to realize automatic horizon tracking and identification, including the steps: Comprehensively determine the sensitive frequencies corresponding to different lithologic combinations and their impedance interfaces, as well as the seismic reflection characteristics of stratigraphic interfaces, optimize the frequency-divided reconstruction data, calibrate and determine the stratigraphic tracking scheme; For the well areas with different lithologic combinations and their impedance interface distributions, select the corresponding sensitive frequency-divided reconstruction data and carry out seed point interpretation; Based on the seed points, apply the automatic tracking algorithm to track each stratigraphic interface with the formation distribution range as the boundary; Horizon splicing: For the interpretation results of different well areas and different data volumes, according to the formation distribution range, splice the interpretation results of each stratigraphic interface to form the interpretation results of the whole area.

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