Method, device and storage medium for predicting remaining oil and gas in oil and gas field

Abstract

The present disclosure provides a method, device and storage medium for predicting remaining oil and gas in an oil and gas field, belonging to the technical field of oil and gas exploration and development. The method comprises: determining a target interval of the oil and gas field by calibrating well-seismic synthetic record of three-dimensional seismic data of each oil and gas well at different acquisition times in the oil and gas field; determining a sensitive frequency band of seismic wave absorbed by oil and gas in the target interval based on a seismic trace or a cross-well seismic profile beside a target oil and gas well in the target interval; determining a target frequency band data volume corresponding to the sensitive frequency band at different acquisition times based on the three-dimensional seismic data of each oil and gas well at different acquisition times and the sensitive frequency band; determining an amplitude difference attribute of the target interval based on the target frequency band data volume corresponding to the sensitive frequency band at different acquisition times; and predicting the remaining oil and gas in the oil and gas field based on the amplitude difference attribute of the target interval. The present disclosure improves the accuracy of the prediction result of the remaining oil and gas in the oil and gas field.

Description

Technical Field

[0001] This disclosure relates to the field of oil and gas exploration and development technology, and in particular to a method, apparatus and storage medium for predicting the remaining oil and gas in an oil and gas field. Background Technology

[0002] As many oil and gas fields have entered the middle and late stages of development, the overall water cut of these fields is high, production is declining, and the situation for maintaining stable production is quite severe. Therefore, it is necessary to predict the remaining oil and gas in the fields, and then use the prediction results to find the remaining oil and gas enrichment areas, optimize reservoir management, and formulate remedial measures in the oil field development process, so as to optimize oil field development, extend oil field life, and improve recovery rate.

[0003] Currently, four-dimensional seismic data interpretation methods are mainly used to predict the remaining oil and gas in oil and gas fields. However, the application of two-dimensional and four-dimensional seismic data interpretation methods has certain limitations, requiring that the acquisition methods of three-dimensional seismic data collected at different times be identical, and that the oil and gas layer thickness be large. However, many current oil and gas fields have relatively thin oil and gas layers, and due to limitations in industrial capabilities at different times, the acquisition methods of two sets of three-dimensional seismic data collected at different times differ significantly, leading to inaccurate prediction results using four-dimensional seismic data interpretation methods. To improve the accuracy of predictions regarding the remaining oil and gas in oil and gas fields, there is an urgent need to provide a new method for predicting the remaining oil and gas in oil and gas fields. Summary of the Invention

[0004] This disclosure provides a method, apparatus, and storage medium for predicting remaining oil and gas in oil and gas fields, which can improve the accuracy of the prediction results. The technical solution is as follows:

[0005] In a first aspect, a method for predicting the remaining oil and gas in an oil and gas field is provided, the method comprising:

[0006] By performing well-seismic synthesis and calibration on 3D seismic data acquired at different times from various oil and gas wells in the oil and gas field, the target layer of the oil and gas field is determined.

[0007] Based on the seismic traces or through-well seismic profiles near the target oil and gas wells within the target layer, the sensitive frequency range for oil and gas absorption seismic waves within the target layer is determined.

[0008] Based on the three-dimensional seismic data of each oil and gas well acquired at different times and the sensitive frequency bands, the target frequency band data volume corresponding to the sensitive frequency bands acquired at different times is determined;

[0009] Based on the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times, the amplitude difference attribute of the target layer segment is determined;

[0010] Based on the amplitude difference properties of the target layer, the remaining oil and gas in the oil and gas field are predicted.

[0011] In another embodiment of this disclosure, determining the sensitive frequency range of seismic waves absorbed by oil and gas within the target formation based on seismic traces or through-well seismic profiles near the target oil and gas well within the target formation includes:

[0012] By employing Fourier transform, and through spectral analysis and comparison of seismic traces or cross-well seismic profiles near the target oil and gas wells within the target layer, the sensitive frequency range for oil and gas absorption of seismic waves within the target layer is determined.

[0013] In another embodiment of this disclosure, determining the target frequency band data volume corresponding to the sensitive frequency band at different acquisition times based on the three-dimensional seismic data from each oil and gas well at different acquisition times and the sensitive frequency band includes:

[0014] Wavelet decomposition was performed on the three-dimensional seismic data of each oil and gas well at different acquisition times to obtain the wavelet decomposition results corresponding to different acquisition times;

[0015] Based on the sensitive frequency band, the target frequency band data volume corresponding to the sensitive frequency band at different acquisition times is obtained from the wavelet decomposition results corresponding to different acquisition times.

[0016] In another embodiment of this disclosure, determining the amplitude difference attribute of the target layer segment based on the target frequency band data volume corresponding to sensitive frequency bands with different acquisition times includes:

[0017] The amplitude difference attribute of the target layer segment is obtained by subtracting the target frequency band data volume corresponding to each frequency point in the sensitive frequency band at different acquisition times.

[0018] In another embodiment of this disclosure, before determining the amplitude difference attribute of the target layer segment based on the target frequency band data volume corresponding to sensitive frequency bands with different acquisition times, the method further includes:

[0019] Using the grid of 3D seismic data at any acquisition time as the reference grid, the surface cells of the target frequency band data volume corresponding to the sensitive frequency segment at other acquisition times are reset.

[0020] The target frequency band data volume corresponding to the sensitive frequency bands based on different acquisition times is used to determine the amplitude difference attribute of the target layer segment, including:

[0021] Based on the target frequency band data volume of the surface element reset corresponding to different acquisition times, the amplitude difference attribute of the target layer segment is determined.

[0022] In another embodiment of this disclosure, after predicting the remaining oil and gas in the oil and gas field based on the amplitude difference attribute of the target layer, the method further includes:

[0023] The first and second remaining oil and gas plane distributions of the target layer of the oil and gas field are obtained. The first remaining oil and gas plane distribution is determined based on the well-seismic composite record of three-dimensional seismic data from each oil and gas well at different acquisition times. The second remaining oil and gas plane distribution is determined based on the amplitude difference attribute of the target layer.

[0024] Based on the first and second remaining oil and gas plane distributions, the prediction results are qualitatively determined.

[0025] The prediction results are quantitatively determined based on the cumulative oil production of each oil and gas well in the oil and gas field and the amplitude difference attribute of the target layer.

[0026] The prediction results are evaluated by combining the qualitative and quantitative judgment results.

[0027] Secondly, an apparatus for predicting remaining oil and gas in an oil and gas field is provided, the apparatus comprising:

[0028] The first determining module is used to determine the target layer of the oil and gas field by performing well-seismic synthesis record calibration on three-dimensional seismic data acquired at different times from various oil and gas wells in the oil and gas field.

[0029] The second determining module is used to determine the sensitive frequency range of seismic waves absorbed by oil and gas in the target layer based on the seismic traces or through-well seismic profiles next to the target oil and gas well in the target layer.

[0030] The third determining module is used to determine the target frequency band data volume corresponding to the sensitive frequency band at different acquisition times based on the three-dimensional seismic data of each oil and gas well at different acquisition times and the sensitive frequency band.

[0031] The fourth determining module is used to determine the amplitude difference attribute of the target layer segment based on the target frequency band data volume corresponding to the sensitive frequency segment at different acquisition times;

[0032] The prediction module is used to predict the remaining oil and gas in the oil and gas field based on the amplitude difference attribute of the target layer.

[0033] In another embodiment of this disclosure, the second determining module is used to determine the sensitive frequency range of seismic waves absorbed by oil and gas in the target layer by performing Fourier transform and comparing the seismic traces or through-well seismic profiles next to the target oil and gas wells in the target layer with frequency spectrum analysis.

[0034] In another embodiment of this disclosure, the third determining module is used to perform wavelet decomposition on the three-dimensional seismic data of each oil and gas well at different acquisition times to obtain wavelet decomposition results corresponding to different acquisition times; based on the sensitive frequency band, the target frequency band data volume corresponding to the sensitive frequency band at different acquisition times is obtained from the wavelet decomposition results corresponding to different acquisition times.

[0035] In another embodiment of this disclosure, the fourth determining module is used to subtract the target frequency band data volume corresponding to each frequency point in the sensitive frequency band at different acquisition times to obtain the amplitude difference attribute of the target layer segment.

[0036] In another embodiment of this disclosure, the apparatus further includes:

[0037] The reset module is used to reset the surface cells of the target frequency band data volume corresponding to the sensitive frequency band of other acquisition times, using the grid of the 3D seismic data at any acquisition time as the reference grid.

[0038] The fourth determining module is used to determine the amplitude difference attribute of the target layer segment based on the target frequency band data volume of the surface element reset corresponding to different acquisition times.

[0039] In another embodiment of this disclosure, the apparatus further includes:

[0040] The acquisition module is used to acquire the first and second remaining oil and gas plane distributions of the target layer of the oil and gas field. The first remaining oil and gas plane distribution is determined based on the well-seismic composite record of three-dimensional seismic data from each oil and gas well at different acquisition times. The second remaining oil and gas plane distribution is determined based on the amplitude difference attribute of the target layer.

[0041] The first determination module is used to make a qualitative determination on the prediction results based on the first and second remaining oil and gas plane distributions.

[0042] The second determination module is used to quantitatively determine the prediction results based on the cumulative oil production of each oil and gas well in the oil and gas field and the amplitude difference attribute of the target layer.

[0043] The evaluation module is used to evaluate the prediction results by combining qualitative and quantitative judgment results.

[0044] Thirdly, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one piece of program code, which is loaded and executed by the processor to implement the method for predicting remaining oil and gas in an oil and gas field as described in the first aspect.

[0045] Fourthly, a computer-readable storage medium is provided, wherein at least one piece of program code is stored therein, the at least one piece of program code being loaded and executed by a processor to implement the method for predicting remaining oil and gas in an oil and gas field as described in the first aspect.

[0046] Fifthly, a computer program product is provided, the computer program product including computer program code stored in a computer-readable storage medium, a processor of an electronic device reading the computer program code from the computer-readable storage medium, the processor executing the computer program code, causing the electronic device to perform the method for predicting remaining oil and gas in an oil and gas field as described in the first aspect.

[0047] The beneficial effects of the technical solutions provided in this disclosure are:

[0048] By identifying the sensitive frequency bands for seismic wave absorption in the target stratigraphic intervals of an oil and gas field, and then determining the target frequency band data volumes corresponding to these sensitive frequency bands based on 3D seismic data acquired at different times from various oil and gas wells, the remaining oil and gas in the field is predicted. This method primarily relies on the amplitude difference attributes of the target stratigraphic intervals for prediction and does not limit the acquisition methods or oil and gas layer thicknesses for the 3D seismic resource data acquired at different times. Therefore, it yields good prediction results for both oil and gas fields with large oil and gas layer thicknesses and identical acquisition methods for 3D seismic data acquired at different times, and oil and gas fields with small oil and gas layer thicknesses and different acquisition methods for 3D seismic data acquired at different times. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a flowchart of a method for predicting the remaining oil and gas in an oil and gas field, provided by an embodiment of this disclosure;

[0051] Figure 2 This is a flowchart of another method for predicting remaining oil and gas in oil and gas fields provided in this disclosure embodiment;

[0052] Figure 3 This is a calibration diagram of the well seismic composite record of well A provided in this embodiment of the disclosure;

[0053] Figure 4 This is a calibration diagram of the well seismic composite record of well B provided in this embodiment of the disclosure;

[0054] Figure 5 This is a spectral profile of the initial exploration of Well C provided in this embodiment of the disclosure;

[0055] Figure 6 This is a spectral profile of the secondary development of Well C provided in an embodiment of this disclosure;

[0056] Figure 7 This is a reconstructed seismic profile from the initial exploration provided in this embodiment of the disclosure;

[0057] Figure 8 This is a reconstructed seismic profile provided in the embodiments of this disclosure;

[0058] Figure 9 This is a cross-sectional view of the amplitude difference in the advantageous frequency band provided in the embodiments of this disclosure;

[0059] Figure 10 This is a cross-plot of the cumulative oil production of a single well in a clastic rock oilfield and the volume amplitude difference of the target frequency band, provided in an embodiment of this disclosure.

[0060] Figure 11 This is a schematic diagram of the device structure for predicting remaining oil and gas in oil and gas fields provided in an embodiment of this disclosure;

[0061] Figure 12 A structural block diagram of an electronic device 1200 provided in an exemplary embodiment of the present disclosure is shown. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of this disclosure clearer, the embodiments of this disclosure will be described in further detail below with reference to the accompanying drawings.

[0063] It is understood that the terms "each," "multiple," and "any," etc., used in the embodiments of this disclosure, include "multiple" (two or more), "each" (each of the corresponding multiples), and "any" (any one of the corresponding multiples). For example, multiple words include 10 words, and "each word" refers to each of the 10 words, while "any word" refers to any one of the 10 words.

[0064] The information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, data stored, data displayed, etc.) and signals involved in this disclosure are all authorized by the user or fully authorized by the parties, and the collection, use and processing of the relevant data shall comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0065] This disclosure provides a method for predicting remaining oil and gas in oil and gas fields. (See also...) Figure 1 The method flow provided in this disclosure includes:

[0066] 101. By calibrating the well-seismic composite records of 3D seismic data from various oil and gas wells at different acquisition times within the oil and gas field, the target stratigraphic interval of the oil and gas field is determined.

[0067] 102. Based on the seismic traces or through-well seismic profiles near the target oil and gas wells within the target stratigraphic interval, determine the sensitive frequency range of seismic waves absorbed by oil and gas within the target stratigraphic interval.

[0068] 103. Based on the 3D seismic data and sensitive frequency bands acquired at different times from various oil and gas wells, determine the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times.

[0069] 104. Based on the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times, determine the amplitude difference attributes of the target layer segment.

[0070] 105. Based on the amplitude difference attributes of the target layer, predict the remaining oil and gas in the oil and gas field.

[0071] The method provided in this disclosure determines the sensitive frequency bands for oil and gas absorption of seismic waves in the target stratigraphic segment of an oil and gas field. Then, based on the 3D seismic data and sensitive frequency bands acquired at different times from various oil and gas wells, it determines the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times. Finally, based on the amplitude difference attributes of the target stratigraphic segment determined by the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times, it predicts the remaining oil and gas in the oil and gas field. This method mainly relies on the amplitude difference attributes of the target stratigraphic segment for prediction and does not limit the acquisition method of the 3D seismic resource data acquired at different times or the thickness of the oil and gas layer. Therefore, it has good prediction results for oil and gas fields with large oil and gas layer thicknesses and the same acquisition method for 3D seismic data acquired at different times, as well as oil and gas fields with small oil and gas layer thicknesses or different acquisition methods for 3D seismic data acquired at different times.

[0072] In another embodiment of this disclosure, based on seismic traces or through-well seismic profiles near target oil and gas wells within the target formation, the sensitive frequency range for oil and gas absorption seismic waves within the target formation is determined, including:

[0073] By employing Fourier transform, the sensitive frequency range for oil and gas absorption seismic waves in the target layer is determined through spectral analysis and comparison of seismic traces or cross-well seismic profiles near the target oil and gas wells within the target layer.

[0074] In another embodiment of this disclosure, based on the three-dimensional seismic data and sensitive frequency bands acquired at different times from various oil and gas wells, the target frequency band data volume corresponding to the sensitive frequency bands acquired at different times is determined, including:

[0075] Wavelet decomposition was performed on the 3D seismic data from various oil and gas wells at different acquisition times to obtain the wavelet decomposition results corresponding to different acquisition times;

[0076] Based on the sensitive frequency band, the target frequency band data volume corresponding to the sensitive frequency band at different acquisition times is obtained from the wavelet decomposition results corresponding to different acquisition times.

[0077] In another embodiment of this disclosure, the amplitude difference attribute of the target layer segment is determined based on the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times, including:

[0078] The amplitude difference attribute of the target layer segment is obtained by subtracting the target frequency band data volume corresponding to each frequency point in the sensitive frequency band at different acquisition times.

[0079] In another embodiment of this disclosure, before determining the amplitude difference attribute of the target layer segment based on the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times, the method further includes:

[0080] Using the grid of 3D seismic data at any acquisition time as the reference grid, the surface cells of the target frequency band data volume corresponding to the sensitive frequency segment at other acquisition times are reset.

[0081] Based on the target frequency band data volumes corresponding to sensitive frequency segments acquired at different times, the amplitude difference attributes of the target layer segments are determined, including:

[0082] Based on the target frequency band data volume of the surface element reset corresponding to different acquisition times, the amplitude difference attribute of the target layer segment is determined.

[0083] In another embodiment of this disclosure, after predicting the remaining oil and gas in the oil and gas field based on the amplitude difference attributes of the target layer, the method further includes:

[0084] The first and second remaining oil and gas plane distributions of the target layer in the oil and gas field are obtained. The first remaining oil and gas plane distribution is determined based on the well-seismic composite record of three-dimensional seismic data acquired at different times from each oil and gas well. The second remaining oil and gas plane distribution is determined based on the amplitude difference attribute of the target layer.

[0085] The prediction results are qualitatively determined based on the first and second remaining oil and gas plane distributions.

[0086] Based on the cumulative oil production of each oil and gas well in the oil and gas field and the amplitude difference of the target layer, the prediction results are quantitatively determined.

[0087] The prediction results are evaluated by combining the qualitative and quantitative judgment results.

[0088] All of the above-mentioned optional technical solutions can be combined in any way to form optional embodiments of this disclosure, and will not be described in detail here.

[0089] This disclosure provides a method for predicting remaining oil and gas in an oil and gas field. Taking an electronic device as an example, this electronic device can be a terminal with certain computing capabilities, such as a smartphone, laptop, or desktop computer, or it can be a server. The server can be a single physical server, or a cluster or distributed system composed of multiple physical servers. See also... Figure 2 The method flow provided in this disclosure includes:

[0090] 201. By calibrating the well-seismic composite records of three-dimensional seismic data acquired at different times from various oil and gas wells in the oil and gas field, the target layer and the first remaining oil and gas plane distribution of the oil and gas field are determined.

[0091] In this context, oil and gas wells within an oil and gas field are categorized into old wells and new wells based on their production time. Old wells are those with a longer production time and a higher degree of oil (gas)-water replacement, while new wells are those with a shorter production time and a lower degree of oil (gas)-water replacement. It should be noted that the different acquisition times in this embodiment primarily refer to the acquisition times during initial exploration and secondary development, while the 3D seismic data used for well-seismic synthesis recording is generally 3D seismic data from secondary development.

[0092] The creation of well-seismic composite records is a simplified one-dimensional forward modeling process. Well-seismic composite records are obtained by convolving the reflection coefficients with a given seismic wavelet. Since well-seismic composite records are a theoretical study, the aforementioned seismic wavelet can be a Yuzlich wavelet, a Lake wavelet, etc., and the dominant frequency of the wavelet can be set according to the dominant frequency of actual data. Figure 3 This is the composite seismic record of well A. Well A is an older well with a high degree of oil-water replacement. Figure 4 This is the well seismic composite record of Well B, which is a new well with a low degree of oil-water replacement.

[0093] Let the well-seismic composite record be S(t), the seismic wavelet be W(t), and the reflection coefficient be R(t), then the well-seismic composite record can be expressed as:

[0094] S(t)=W(t)*R(t)

[0095] Electronic equipment can determine the longitudinal location and seismic reflection horizon of the target layer in an oil and gas field by performing well-seismic synthesis recording and calibration of three-dimensional seismic data from various oil and gas wells at different acquisition times (mainly secondary development).

[0096] Because of the mismatch between logging time and seismic acquisition time, older wells with high oil (gas)-water replacement (acquisition time comparable to the initial exploration 3D seismic data acquisition time) may have poor oil and gas layer calibration results, while new wells with low oil (gas)-water replacement (acquisition time comparable to the secondary development 3D seismic data acquisition time) may have good oil and gas layer calibration results. Therefore, once the vertical position and seismic reflection horizon of the target layer are determined, the electronic equipment acquires the fine calibration results of all oil and gas wells. Based on this, it is checked whether the 3D seismic data of the secondary development of the oil and gas well truly contains identifiable oil (gas)-water replacement information. If the 3D seismic data of the secondary development contains identifiable oil (gas)-water replacement information, the first remaining oil and gas planar distribution is initially determined from point to area. This first remaining oil and gas planar distribution is usually only a rough outline.

[0097] 202. Based on the seismic traces or through-well seismic profiles near the target oil and gas wells within the target stratigraphic interval, determine the sensitive frequency range of seismic waves absorbed by oil and gas within the target stratigraphic interval.

[0098] Among them, target oil and gas wells refer to older wells with a long production history and a high degree of oil (gas)-water replacement. A seismic profile, also called a seismic record profile, is a seismic data map that marks a specific seismic line. Based on the different physical dimensions used for the vertical axis, seismic record profiles can be divided into two types: time profiles and depth profiles.

[0099] The specific process by which electronic equipment determines the sensitive frequency range of seismic waves absorbed by oil and gas within the target formation based on seismic traces or through-well seismic profiles near the target oil and gas wells is as follows: Using Fourier transform, the sensitive frequency range of seismic waves absorbed by oil and gas within the target formation is determined through spectral analysis and comparison of the seismic traces or through-well seismic profiles near the target oil and gas wells. Here, Fourier transform represents the ability to express a function satisfying certain conditions as a linear combination of trigonometric functions (sine and / or cosine functions) or their integrals.

[0100] In practical applications, older wells with early production dates (comparable to the initial exploration 3D seismic data acquisition time), long production times (well shutdown time not much earlier than the secondary development 3D seismic data acquisition time), large cumulative oil (gas) production, and high oil (gas)-water replacement levels are typically selected for the target layer. Fourier transform is used to perform spectral analysis and comparison of seismic traces or through-well seismic profiles near these older wells. This determines the approximate frequency variation sensitive range of 3D seismic data acquired at different times from the initial exploration to the secondary development 3D seismic data acquisition interval, as the high degree of oil (gas)-water replacement is completed. This is the sensitive frequency range for oil (gas) absorption of seismic waves. For example, Figure 5 This is the initial 3D seismic data for well C. Figure 6 The 3D seismic data for the secondary development of Well C were compared. Figure 5 and Figure 6 Identify the frequency ranges with significant frequency variations; these are the sensitive frequency ranges.

[0101] 203. Based on the 3D seismic data and sensitive frequency bands acquired at different times from various oil and gas wells, determine the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times.

[0102] When electronic devices determine the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times based on 3D seismic data and sensitive frequency bands from various oil and gas wells, the following method can be used:

[0103] 2031. Wavelet decomposition was performed on the 3D seismic data of each oil and gas well at different acquisition times to obtain the wavelet decomposition results corresponding to different acquisition times.

[0104] Wavelet decomposition refers to the process of decomposing a seismic trace into a combination of seismic wavelets with different dominant frequencies.

[0105] 2032. Based on the sensitive frequency band, obtain the target frequency band data volume corresponding to the sensitive frequency band at different acquisition times from the wavelet decomposition results corresponding to different acquisition times.

[0106] Based on the wavelet decomposition results of 3D seismic data acquired at different times, seismic wavelet information corresponding to sensitive frequency bands at different acquisition times is obtained, resulting in target frequency band data volumes for the sensitive frequency bands at different acquisition times. This target frequency band data volume can highlight the differences between seismic data before and after oil (gas)-water replacement. See details... Figure 7 and Figure 8 The attached diagram is shown.

[0107] 204. Based on the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times, determine the amplitude difference attributes of the target layer segment.

[0108] In one possible implementation, the electronic device subtracts the target frequency band data volume corresponding to each frequency point in the sensitive frequency band at different acquisition times to obtain the amplitude difference attribute of the target layer segment.

[0109] In another possible implementation, considering that the mesh of 3D seismic data acquired at different times may differ, this embodiment of the present disclosure uses the mesh of 3D seismic data acquired at any given time as the reference mesh. The target frequency band data volumes corresponding to sensitive frequency segments acquired at other times are then re-scaled using surface cells. Based on the re-scaled target frequency band data volumes corresponding to different acquisition times, the amplitude difference attributes of the target layer are determined. In practical applications, the mesh of the initial 3D seismic data is typically used as the reference mesh.

[0110] 205. Based on the amplitude difference attribute of the target layer, predict the remaining oil and gas in the oil and gas field.

[0111] Based on the amplitude difference attributes of the target formation, and according to the calibration results of the well seismic composite record, an appropriate time window is selected to extract the amplitude difference attributes of the target formation. Then, based on these amplitude difference attributes, the remaining oil and gas in the oil and gas field is predicted. A larger amplitude difference attribute indicates a higher degree of oil (gas)-water replacement and less remaining oil (gas); conversely, a smaller amplitude difference attribute indicates a lower degree of (gas)-water replacement and more remaining oil (gas). This embodiment of the disclosure, by analyzing the amplitude difference attributes of the target formation, can delineate the enrichment areas of remaining oil and gas, for example... Figure 9 Oil reservoir area in the middle.

[0112] 206. Evaluate the prediction results.

[0113] After predicting the remaining oil and gas in an oil and gas field based on the amplitude difference attributes of the target layer, this embodiment of the disclosure will also evaluate the prediction results. Specifically, the following methods can be used for evaluation:

[0114] 2061. Obtain the first and second remaining oil and gas plane distributions of the target stratigraphic interval in the oil and gas field.

[0115] The first remaining oil and gas planar distribution is determined based on well-seismic composite records of 3D seismic data from various oil and gas wells acquired at different times (mainly secondary development). The second remaining oil and gas planar distribution is determined based on the amplitude difference attributes of the target layer.

[0116] 2062. Based on the first and second remaining oil and gas plane distributions, the prediction results are qualitatively determined.

[0117] In this embodiment of the disclosure, when qualitatively determining the prediction results based on the first and second remaining oil and gas plane distributions, the following two steps are performed:

[0118] First, compare and analyze whether the outlines of the first and second remaining oil and gas planar distributions are roughly the same, so as to ensure that there are not too much difference between them macroscopically.

[0119] Secondly, check whether most of the current production wells, especially the relatively high-yield wells, are located within the predicted remaining oil and gas enrichment areas.

[0120] 2063. Based on the cumulative oil production of each oil and gas well in the oil and gas field and the amplitude difference attribute of the target layer, the prediction results are quantitatively determined.

[0121] Under relatively stable lateral variations in clastic reservoirs, theoretically, the greater the crude oil (gas) production, the higher the degree of oil (gas)-water replacement, and the greater the amplitude difference; conversely, the smaller the crude oil (gas) production, the lower the degree of oil (gas)-water replacement, and the smaller the amplitude difference. In other words, there is a certain positive correlation between cumulative oil (gas) production and amplitude difference (this positive correlation is not necessarily linear). This correlation can be found in [reference needed]. Figure 10 The attached figures are shown. Based on the above analysis, this embodiment of the present disclosure can extract the amplitude difference value of the historical production well point location based on the second remaining oil and gas plane distribution, and then perform cross-analysis with the cumulative oil (gas) production of a single well. If there is a good positive correlation between the two, it indicates that the prediction result is reliable; otherwise, it indicates that the prediction accuracy is low.

[0122] 2064. Evaluate the prediction results by combining the qualitative and quantitative judgment results.

[0123] Based on the qualitative and quantitative judgment results described above, this embodiment of the disclosure will comprehensively evaluate the prediction results. If the qualitative judgment result is unreliable and the quantitative judgment result is also unreliable, then the comprehensive evaluation result is unreliable; if the qualitative judgment result is reliable and the quantitative judgment result is also reliable, then the comprehensive evaluation result is reliable.

[0124] Furthermore, if the overall evaluation result is unreliable, this embodiment of the present disclosure will require fine-tuning the sensitive frequency range of oil (gas) absorption of seismic waves, and then, based on the fine-tuning of the sensitive frequency range of oil (gas) absorption of seismic waves, predicting the second remaining oil and gas planar distribution again until the overall evaluation result is relatively reliable.

[0125] A study of the clastic oilfield H (developed for over 20 years) in the Tarim Basin platform area revealed that the current mainstream four-dimensional seismic interpretation method yielded low accuracy in predicting remaining oil and gas, failing to provide a constructive basis for adjusting the deployment of oil and gas wells for secondary development. However, the method provided in this disclosure significantly improved the accuracy of remaining oil and gas prediction, increasing it from 61% to 82%. This provides strong support for extending the lifespan of clastic oil and gas reservoirs, improving recovery rates, and achieving profitable development.

[0126] The method provided in this disclosure determines the sensitive frequency bands for oil and gas absorption of seismic waves in the target stratigraphic segment of an oil and gas field. Then, based on the 3D seismic data and sensitive frequency bands acquired at different times from various oil and gas wells, it determines the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times. Finally, based on the amplitude difference attributes of the target stratigraphic segment determined by the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times, it predicts the remaining oil and gas in the oil and gas field. This method mainly relies on the amplitude difference attributes of the target stratigraphic segment for prediction and does not limit the acquisition method of the 3D seismic resource data acquired at different times or the thickness of the oil and gas layer. Therefore, it has good prediction results for oil and gas fields with large oil and gas layer thicknesses and the same acquisition method for 3D seismic data acquired at different times, as well as oil and gas fields with small oil and gas layer thicknesses or different acquisition methods for 3D seismic data acquired at different times.

[0127] See Figure 11 This disclosure provides an apparatus for predicting remaining oil and gas in an oil and gas field, the apparatus comprising:

[0128] The first determining module 1101 is used to determine the target layer of the oil and gas field by performing well-seismic synthesis record calibration on three-dimensional seismic data acquired at different times from various oil and gas wells in the oil and gas field.

[0129] The second determining module 1102 is used to determine the sensitive frequency range of oil and gas absorption seismic waves in the target layer based on the seismic traces or through-well seismic profiles next to the target oil and gas well in the target layer.

[0130] The third determination module 1103 is used to determine the target frequency band data volume corresponding to the sensitive frequency band at different acquisition times based on the three-dimensional seismic data and sensitive frequency bands of each oil and gas well at different acquisition times.

[0131] The fourth determination module 1104 is used to determine the amplitude difference attribute of the target layer segment based on the target frequency band data volume corresponding to the sensitive frequency segment at different acquisition times.

[0132] The prediction module 1105 is used to predict the remaining oil and gas in the oil and gas field based on the amplitude difference attribute of the target layer.

[0133] In another embodiment of this disclosure, the second determining module 1102 is used to determine the sensitive frequency range of seismic waves absorbed by oil and gas in the target layer by performing spectral analysis and comparison on the seismic traces or through-well seismic profiles next to the target oil and gas well in the target layer.

[0134] In another embodiment of this disclosure, the third determining module 1103 is used to perform wavelet decomposition on the three-dimensional seismic data of each oil and gas well at different acquisition times to obtain the wavelet decomposition results corresponding to different acquisition times; based on the sensitive frequency band, the target frequency band data volume corresponding to the sensitive frequency band of different acquisition times is obtained from the wavelet decomposition results corresponding to different acquisition times.

[0135] In another embodiment of this disclosure, the fourth determining module 1104 is used to subtract the target frequency band data volume corresponding to each frequency point in the sensitive frequency band at different acquisition times to obtain the amplitude difference attribute of the target layer segment.

[0136] In another embodiment of this disclosure, the device further includes:

[0137] The reset module is used to reset the surface cells of the target frequency band data volume corresponding to the sensitive frequency band of other acquisition times, using the grid of the 3D seismic data at any acquisition time as the reference grid.

[0138] The fourth determination module 1104 is used to determine the amplitude difference attribute of the target layer segment based on the target frequency band data volume reset by the surface element corresponding to different acquisition times.

[0139] In another embodiment of this disclosure, the device further includes:

[0140] The acquisition module is used to acquire the first and second remaining oil and gas plane distributions of the target layer in the oil and gas field. The first remaining oil and gas plane distribution is determined based on the well-seismic composite record of three-dimensional seismic data from different acquisition times of each oil and gas well. The second remaining oil and gas plane distribution is determined based on the amplitude difference attribute of the target layer.

[0141] The first determination module is used to make a qualitative determination on the prediction results based on the first and second remaining oil and gas plane distributions.

[0142] The second judgment module is used to quantitatively judge the prediction results based on the cumulative oil production of each oil and gas well in the oil and gas field and the amplitude difference attribute of the target layer.

[0143] The evaluation module is used to evaluate the prediction results by combining qualitative and quantitative judgment results.

[0144] In summary, the apparatus provided in this disclosure determines the sensitive frequency bands of seismic waves absorbed by oil and gas in the target formation of an oil and gas field. Then, based on the 3D seismic data and sensitive frequency bands acquired at different times from various oil and gas wells, it determines the target frequency band data volumes corresponding to the sensitive frequency bands at different acquisition times. Finally, based on the amplitude difference attributes of the target formations determined by the target frequency band data volumes corresponding to the sensitive frequency bands at different acquisition times, it predicts the remaining oil and gas in the oil and gas field. This method mainly relies on the amplitude difference attributes of the target formations for prediction and does not limit the acquisition methods of the 3D seismic resource data acquired at different times or the thickness of the oil and gas layers. Therefore, it has good prediction results for oil and gas fields with large oil and gas layer thicknesses and the same acquisition methods for 3D seismic data acquired at different times, as well as oil and gas fields with small oil and gas layer thicknesses or different acquisition methods for 3D seismic data acquired at different times.

[0145] Figure 12 This diagram illustrates a structural block diagram of an electronic device 1200 provided in an exemplary embodiment of the present disclosure. Typically, the electronic device 1200 includes a processor 1201 and a memory 1202.

[0146] Processor 1201 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 1201 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 1201 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 1201 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 1201 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0147] The memory 1202 may include one or more computer-readable storage media, which may be non-transitory. The memory 1202 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 1202 is used to store at least one instruction, which is executed by the processor 1201 to implement the method for predicting remaining oil and gas in an oil and gas field provided in the method embodiments of this disclosure.

[0148] In some embodiments, the electronic device 1200 may also optionally include a peripheral device interface 1203 and at least one peripheral device. The processor 1201, memory 1202, and peripheral device interface 1203 can be connected via a bus or signal lines. Each peripheral device can be connected to the peripheral device interface 1203 via a bus, signal lines, or a circuit board. Specifically, the peripheral device includes a power supply 1204.

[0149] Peripheral device interface 1203 can be used to connect at least one I / O (Input / Output) related peripheral device to processor 1201 and memory 1202. In some embodiments, processor 1201, memory 1202 and peripheral device interface 1203 are integrated on the same chip or circuit board; in some other embodiments, any one or two of processor 1201, memory 1202 and peripheral device interface 1203 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0150] Power supply 1204 is used to supply power to various components in electronic device 1200. Power supply 1204 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 1204 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired line, and a wireless rechargeable battery is a battery that is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0151] Those skilled in the art will understand that Figure 12 The structure shown does not constitute a limitation on the electronic device 1200, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0152] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory including instructions, which can be executed by a processor of electronic device 1200 to perform the aforementioned prediction of remaining oil and gas in the oil and gas field. Optionally, the storage medium may be a non-transitory computer-readable storage medium, such as a CD-ROM (Compact Disc Read-Only Memory), ROM, RAM (Random Access Memory), magnetic tape, floppy disk, and optical data storage device.

[0153] This disclosure provides a computer-readable storage medium storing at least one piece of program code, which is loaded and executed by a processor to implement a method for predicting remaining oil and gas in an oil and gas field.

[0154] This disclosure provides a computer program product including computer program code stored in a computer-readable storage medium. A processor of an electronic device reads the computer program code from the computer-readable storage medium and executes the computer program code, causing the electronic device to perform a method for predicting remaining oil and gas in an oil and gas field.

[0155] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0156] The above description is merely an optional embodiment of this disclosure and is not intended to limit this disclosure. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the protection scope of this disclosure.

Claims

1. A method for predicting remaining oil and gas in an oil and gas field, characterized in that, The method includes: By performing well-seismic synthesis and calibration on 3D seismic data acquired at different times from various oil and gas wells in the oil and gas field, the target layer of the oil and gas field is determined. Based on the seismic traces or through-well seismic profiles near the target oil and gas wells within the target layer, the sensitive frequency range for oil and gas absorption seismic waves within the target layer is determined. Based on the three-dimensional seismic data of each oil and gas well acquired at different times and the sensitive frequency bands, the target frequency band data volume corresponding to the sensitive frequency bands acquired at different times is determined; Based on the target frequency band data volume corresponding to the sensitive frequency bands at different acquisition times, the amplitude difference attribute of the target layer segment is determined; Based on the amplitude difference properties of the target layer, the remaining oil and gas in the oil and gas field are predicted; The step of determining the sensitive frequency range of seismic waves absorbed by oil and gas in the target layer based on the seismic traces or through-well seismic profiles near the target oil and gas wells in the target layer includes: using Fourier transform to determine the sensitive frequency range of seismic waves absorbed by oil and gas in the target layer by performing spectral analysis and comparison on the seismic traces or through-well seismic profiles near the target oil and gas wells in the target layer. The step of determining the target frequency band data volume corresponding to the sensitive frequency band at different acquisition times based on the three-dimensional seismic data of each oil and gas well at different acquisition times and the sensitive frequency band includes: performing wavelet decomposition on the three-dimensional seismic data of each oil and gas well at different acquisition times to obtain the wavelet decomposition results corresponding to different acquisition times; and obtaining the target frequency band data volume corresponding to the sensitive frequency band at different acquisition times from the wavelet decomposition results corresponding to different acquisition times based on the sensitive frequency band.

2. The method according to claim 1, characterized in that, The target frequency band data volume corresponding to the sensitive frequency bands based on different acquisition times is used to determine the amplitude difference attribute of the target layer segment, including: The amplitude difference attribute of the target layer segment is obtained by subtracting the target frequency band data volume corresponding to each frequency point in the sensitive frequency band at different acquisition times.

3. The method according to claim 1, characterized in that, Before determining the amplitude difference attribute of the target layer segment based on the target frequency band data volume corresponding to the sensitive frequency bands with different acquisition times, the method further includes: Using the grid of 3D seismic data at any acquisition time as the reference grid, the surface cells of the target frequency band data volume corresponding to the sensitive frequency segment at other acquisition times are reset. The target frequency band data volume corresponding to the sensitive frequency bands based on different acquisition times is used to determine the amplitude difference attribute of the target layer segment, including: Based on the target frequency band data volume of the surface element reset corresponding to different acquisition times, the amplitude difference attribute of the target layer segment is determined.

4. The method according to claim 1, characterized in that, After predicting the remaining oil and gas in the oil and gas field based on the amplitude difference attributes of the target layer, the method further includes: The first and second remaining oil and gas plane distributions of the target layer of the oil and gas field are obtained. The first remaining oil and gas plane distribution is determined based on the well-seismic composite record of three-dimensional seismic data from each oil and gas well at different acquisition times. The second remaining oil and gas plane distribution is determined based on the amplitude difference attribute of the target layer. Based on the first and second remaining oil and gas plane distributions, the prediction results are qualitatively determined. The prediction results are quantitatively determined based on the cumulative oil production of each oil and gas well in the oil and gas field and the amplitude difference attribute of the target layer. The prediction results are evaluated by combining the qualitative and quantitative judgment results.

5. A device for predicting remaining oil and gas in an oil and gas field, characterized in that, The device includes: The first determining module is used to determine the target layer of the oil and gas field by performing well-seismic synthesis record calibration on three-dimensional seismic data acquired at different times from various oil and gas wells in the oil and gas field. The second determining module is used to determine the sensitive frequency range of seismic waves absorbed by oil and gas in the target layer based on the seismic traces or through-well seismic profiles next to the target oil and gas well in the target layer. The third determining module is used to determine the target frequency band data volume corresponding to the sensitive frequency band at different acquisition times based on the three-dimensional seismic data of each oil and gas well at different acquisition times and the sensitive frequency band. The fourth determining module is used to determine the amplitude difference attribute of the target layer segment based on the target frequency band data volume corresponding to the sensitive frequency segment at different acquisition times; The prediction module is used to predict the remaining oil and gas in the oil and gas field based on the amplitude difference attribute of the target layer. Specifically, the second determining module is used to: use Fourier transform to perform spectral analysis and comparison on the seismic traces or through-well seismic profiles next to the target oil and gas wells in the target layer to determine the sensitive frequency range of seismic waves absorbed by oil and gas in the target layer. The third determining module is specifically used for: performing wavelet decomposition on the three-dimensional seismic data of each oil and gas well at different acquisition times to obtain wavelet decomposition results corresponding to different acquisition times; and, based on the sensitive frequency band, obtaining the target frequency band data volume corresponding to the sensitive frequency band at different acquisition times from the wavelet decomposition results corresponding to different acquisition times.

6. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing at least one piece of program code, which is loaded and executed by the processor to implement the method for predicting remaining oil and gas in an oil and gas field as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The storage medium stores at least one piece of program code, which is loaded and executed by a processor to implement the method for predicting the remaining oil and gas in an oil and gas field as described in any one of claims 1 to 4.

8. A computer program product, characterized in that, The computer program product includes computer program code stored in a computer-readable storage medium. The processor of the electronic device reads the computer program code from the computer-readable storage medium and executes the computer program code, causing the electronic device to perform the method for predicting remaining oil and gas in an oil and gas field as described in any one of claims 1 to 4.

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