Fluid detection method and electronic device

Abstract

The application discloses a fluid detection method and an electronic device, and belongs to the technical field of oil and gas exploration. The method comprises the following steps: acquiring a frequency gather corresponding to a target position to be subjected to fluid detection; drawing a target spectral feature curve based on seismic wave data of multiple frequencies included in the frequency gather of the target position; acquiring a target curve segment located in a sensitive frequency segment from the target spectral feature curve; fitting the target curve segment according to a reference fitting mode to obtain multiple fluid parameters corresponding to the target position; selecting a fluid parameter of a reference activity factor type as a target fluid activity factor from the multiple fluid parameters; and determining that a fluid type of the target position is a target fluid type if the target fluid activity factor is located in a fluid activity factor range corresponding to the target fluid type. The fluid detection method provided by the application can improve the accuracy of fluid detection, thereby reducing the risk of drilling failure.

Description

Technical Field

[0001] This application relates to the field of oil and gas exploration technology, and in particular to a fluid detection method and electronic equipment. Background Technology

[0002] In oil and gas exploration and development, to accurately determine the location of oil and gas reservoirs, fluid detection is typically performed using data from drilling, logging, and seismic data. This allows for the prediction of the spatial distribution characteristics of oil and gas and reduces the probability of drilling failure. However, the decreasing accuracy of current fluid detection methods increases the risk of drilling failure. Therefore, improving the accuracy of fluid detection has become an urgent problem to be solved. Summary of the Invention

[0003] This application provides a fluid detection method and electronic device, which can solve the problem of reduced detection accuracy in related technologies. The technical solution is as follows:

[0004] On the one hand, a fluid detection method is provided, the method comprising:

[0005] From the frequency gather data volume corresponding to the target reservoir section in the exploration area, obtain the frequency gather corresponding to the target location to be detected for fluid. The frequency gather data volume includes frequency gathers corresponding to multiple seismic traces, and the frequency gathers include seismic wave data of multiple frequencies of the same seismic trace.

[0006] From the seismic wave data of multiple frequencies included in the frequency gather of the target location, multiple amplitudes located on the reference isochrone are obtained. The multiple amplitudes correspond one-to-one with the multiple frequencies. The reference isochrone is determined based on the location of the target seismic reflection layer and the reference drift time. The target seismic reflection layer refers to the seismic reflection layer that is closest to the target reservoir section.

[0007] Based on the multiple frequencies and multiple amplitudes, plot the target spectral characteristic curve;

[0008] Obtain the target curve segment located within the sensitive frequency range from the target spectral characteristic curve, where the sensitive frequency range refers to the frequency range where oil and gas are sensitive to seismic wave absorption;

[0009] The target curve segment is fitted according to the benchmark fitting method to obtain multiple fluid parameters corresponding to the target position;

[0010] From the plurality of fluid parameters, select the fluid parameter with the parameter type of the reference activity factor type as the target fluid activity factor. The reference activity factor type refers to the type of fluid parameter required to distinguish multiple different types of fluids.

[0011] If the target fluid activity factor is within the range of fluid activity factors corresponding to the target fluid type, then the fluid type at the target location is determined to be the target fluid type, and the target fluid type is one of multiple fluid types.

[0012] On the other hand, an electronic device is provided, the electronic device including a processor, the processor being used for:

[0013] From the frequency gather data volume corresponding to the target reservoir section in the exploration area, obtain the frequency gather corresponding to the target location to be detected for fluid. The frequency gather data volume includes frequency gathers corresponding to multiple seismic traces, and the frequency gathers include seismic wave data of multiple frequencies of the same seismic trace.

[0014] From the seismic wave data of multiple frequencies included in the frequency gather of the target location, multiple amplitudes located on the reference isochrone are obtained. The multiple amplitudes correspond one-to-one with the multiple frequencies. The reference isochrone is determined based on the location of the target seismic reflection layer and the reference drift time. The target seismic reflection layer refers to the seismic reflection layer that is closest to the target reservoir section.

[0015] Based on the multiple frequencies and multiple amplitudes, plot the target spectral characteristic curve;

[0016] Obtain the target curve segment located within the sensitive frequency range from the target spectral characteristic curve, where the sensitive frequency range refers to the frequency range where oil and gas are sensitive to seismic wave absorption;

[0017] The target curve segment is fitted according to the benchmark fitting method to obtain multiple fluid parameters corresponding to the target position;

[0018] From the plurality of fluid parameters, select the fluid parameter with the parameter type of the reference activity factor type as the target fluid activity factor. The reference activity factor type refers to the type of fluid parameter required to distinguish multiple different types of fluids.

[0019] If the target fluid activity factor is within the range of fluid activity factors corresponding to the target fluid type, then the fluid type at the target location is determined to be the target fluid type, and the target fluid type is one of multiple fluid types.

[0020] On the other hand, a fluid detection device is provided, the device comprising:

[0021] The first acquisition module is used to acquire the frequency gather corresponding to the target location to be detected for fluid from the frequency gather data volume corresponding to the target reservoir section in the exploration area. The frequency gather data volume includes frequency gathers corresponding to multiple seismic traces, and the frequency gathers include seismic wave data of multiple frequencies of the same seismic trace.

[0022] The second acquisition module is used to acquire multiple amplitudes located on a reference isochrone from the seismic wave data of multiple frequencies included in the frequency gather of the target location. The multiple amplitudes correspond one-to-one with the multiple frequencies. The reference isochrone is determined based on the location of the target seismic reflection layer and the reference drift time. The target seismic reflection layer refers to the seismic reflection layer that is closest to the target reservoir section.

[0023] A plotting module is used to plot the target spectral characteristic curve based on the multiple frequencies and the multiple amplitudes;

[0024] The third acquisition module is used to acquire the target curve segment located within the sensitive frequency range from the target spectral characteristic curve, wherein the sensitive frequency range refers to the frequency range in which oil and gas are sensitive to the absorption of seismic waves;

[0025] The fitting module is used to fit the target curve segment according to the benchmark fitting method to obtain multiple fluid parameters corresponding to the target position;

[0026] The selection module is used to select a fluid parameter of type reference activity factor from the plurality of fluid parameters as the target fluid activity factor. The reference activity factor type refers to the type of fluid parameter required to distinguish multiple different types of fluids.

[0027] The first determining module is used to determine the fluid type of the target location as the target fluid type if the target fluid activity factor is within the range of fluid activity factors corresponding to the target fluid type, wherein the target fluid type is one of a plurality of fluid types.

[0028] On the other hand, a computer-readable storage medium is provided, wherein a computer program is stored therein, and when the computer program is executed by a processor, it implements the steps of the fluid detection method described above.

[0029] On the other hand, a computer program product containing instructions is provided, which, when executed on a computer, cause the computer to perform the steps of the fluid detection method described above.

[0030] The technical solution provided in this application can bring at least the following beneficial effects:

[0031] This application embodiment determines the target fluid activity factor by fitting the spectral characteristic curve of the sensitive frequency band. Since the target fluid activity factor is obtained through multi-point fitting, it can accurately reflect the characteristics of the fluid type at the target location. Furthermore, because the type of the reference activity factor can distinguish the types of fluid parameters required for multiple different types of fluids, the fluid parameters determined based on the type of the reference activity factor can accurately reflect the differences between different types of fluids. This improves the accuracy of fluid detection, thereby reducing the risk of drilling failure. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of this application, 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 application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a flowchart of a fluid detection method provided in an embodiment of this application;

[0034] Figure 2 This is a schematic diagram of a seismic profile provided in an embodiment of this application;

[0035] Figure 3 This is a schematic diagram of a single-frequency body cross-section provided in an embodiment of this application;

[0036] Figure 4 This is a schematic diagram of a frequency gather and initial spectral characteristic curve provided in an embodiment of this application;

[0037] Figure 5 This is a schematic diagram of another frequency gather and initial spectral characteristic curve provided in an embodiment of this application;

[0038] Figure 6 This is a schematic diagram of a fitting method provided in an embodiment of this application;

[0039] Figure 7 This is a schematic diagram of another fitting method provided in the embodiments of this application;

[0040] Figure 8 This is a schematic diagram of the structure of a fluid detection device provided in an embodiment of this application;

[0041] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0043] Before providing a detailed explanation of the fluid detection method provided in the embodiments of this application, the application scenarios involved in the embodiments of this application will be introduced first.

[0044] When conducting oil and gas exploration and development in an exploration area, it is necessary to determine the reservoir sections for oil and gas based on drilling, logging, geological, and seismic data. Then, based on the seismic and geological data of these reservoir sections, fluid monitoring is conducted in the exploration area to guide well placement and oil and gas development. This exploration area can be a clastic rock area or a carbonate rock area, etc. In the case of a clastic rock area, in addition to large structural traps, there are often hidden traps such as low-amplitude traps, small fault blocks, and even stratigraphic and lithological traps. Because these hidden traps are often structurally complex, it is difficult to effectively monitor their fluid flow using existing methods, thus hindering the optimal well placement and development of these traps. In the case of a carbonate rock area, irregular fracture-vuggy oil and gas reservoirs are often formed. However, due to the complex oil, gas, and water relationships in irregular fractured-vuggy oil and gas reservoirs, and the presence of unpredictable factors such as clay infill, existing methods for fluid detection to guide well location deployment often result in relatively large errors and drilling failures. However, the fluid detection method provided in this application can be applied to both types of exploration areas to detect fluid in the target area. This method not only improves drilling success rates and the proportion of high-efficiency wells but also enables the efficient development of carbonate rocks.

[0045] It should be noted that the two types of regions listed above are only for clearer illustration of the technical solutions of the embodiments of this application and do not constitute a limitation on the technical solutions provided by the embodiments of this application. In practical applications, the fluid detection method provided in this embodiment can also be applied to other similar regions besides the two types of regions listed above, depending on the specific circumstances. The embodiments of this application do not limit this.

[0046] The fluid detection method provided in this application is executed by an electronic device. This electronic device can be any electronic product capable of human-computer interaction with a user through one or more methods such as a keyboard, touchpad, touchscreen, remote control, voice interaction, or handwriting device.

[0047] It should be noted that the application scenarios and execution entities described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the emergence of new application scenarios and electronic devices, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0048] The fluid detection method provided in the embodiments of this application will now be explained in detail.

[0049] Figure 1 This is a flowchart of a fluid detection method provided in an embodiment of this application. Please refer to it. Figure 1 The method includes the following steps.

[0050] Step 101: Obtain the frequency gather corresponding to the target location to be detected for fluid from the frequency gather data volume corresponding to the target reservoir section in the exploration area. The frequency gather data volume includes frequency gathers corresponding to multiple seismic traces, and the frequency gathers include seismic wave data of multiple frequencies of the same seismic trace.

[0051] Since the frequency gather data volume includes frequency gathers corresponding to multiple seismic traces, and the target location and these multiple seismic traces are located in the same exploration area, the target location is one of these multiple seismic traces. In this case, the frequency gather corresponding to the target location can be obtained from the frequency gather data volume corresponding to the target reservoir segment in the exploration area.

[0052] The fluid detection method provided in this application essentially determines the fluid activity factor corresponding to the target location to be detected, and then determines the fluid type of the target location based on the target fluid activity factor. The determination of the target fluid activity factor is based on the frequency gather data volume, reference drift duration, sensitive frequency band, reference fitting method, and reference activity factor type. Furthermore, after determining the target fluid activity factor, it is necessary to further determine the fluid type of the target location based on the target fluid activity factor and the fluid activity factor range corresponding to multiple fluid types. Therefore, in some embodiments, before executing steps 101-107, it is necessary to determine the reference drift duration, sensitive frequency band, reference fitting method, reference activity factor type, and the fluid activity factor range corresponding to multiple fluid types according to the following steps (1)-(2).

[0053] (1) Determine the location of the target seismic reflection layer and the frequency gather data volume corresponding to the target reservoir segment.

[0054] After well-seismic composite record calibration, corresponding geological stratigraphic information can be obtained from the seismic profile. That is, well-seismic composite record calibration establishes the connection between drilling data, logging data, geological data, and seismic reflection waves, thereby enabling the understanding of the geological stratigraphic level, geological age, lithological assemblage, and hydrocarbon-bearing strata corresponding to the seismic reflection waves. This forms the basis for subsequent structural interpretation, stratigraphic interpretation, and reservoir interpretation. Therefore, in some embodiments, well-seismic composite record calibration can be performed on the 3D seismic data of the exploration area using drilling data, logging data, and geological data to determine the location of the target reservoir section and the target seismic reflection layer. Based on the location of the target reservoir section, the reference frequency range, and the reference frequency step size, spectral decomposition is performed on the 3D seismic data located in the target reservoir section of the exploration area to obtain single-frequency volumes of multiple frequencies. Each single-frequency volume includes seismic wave data from multiple seismic traces at the same frequency. The seismic wave data from the same seismic trace in these multiple single-frequency volumes are merged to obtain the frequency gather data volume corresponding to the target reservoir section.

[0055] Optionally, the specific process for calibrating the above-mentioned well-seismic composite record is as follows: using drilling data, well logging data, geological data, and three-dimensional seismic data of the exploration area, calibration is performed to obtain a composite seismic record. The production process of this composite seismic record is a simplified one-dimensional forward modeling process. As an example, the seismic wavelet and reflection coefficient can be convolved according to the following formula (1) to obtain the composite seismic record.

[0056] S(t)=W(t)*R(t) (1)

[0057] In the above formula (1), S(t) represents the synthetic seismic record, W(t) represents the seismic wavelet, and R(t) represents the reflection coefficient.

[0058] It should be noted that the aforementioned seismic wavelet can be a Yu wavelet, a Lake wavelet, etc., and the dominant frequency of the seismic wavelet can be determined based on the dominant frequency of the actual seismic data.

[0059] Since the seismic data in 3D seismic data records signals that change over time, reflecting information in the time domain, the above-mentioned process of well-seismic composite record calibration involves projecting various well information, such as well trajectory, geological stratification, and well fault points, onto the seismic profile. In this seismic profile, the horizontal axis can represent the location on the Earth's surface, and the vertical axis can represent time.

[0060] For example, please refer to Figure 2 , Figure 2 This is a schematic diagram of the seismic profile after well-seismic composite record calibration. After calibration, the location of the target reservoir section and the target seismic reflection layer can be determined.

[0061] Since target reservoirs are often rich in oil and gas, processing the 3D seismic data of the target reservoir is sufficient to discover most of the fluids in the exploration area. Therefore, in some embodiments, the time range corresponding to the target reservoir can be determined based on its location. Then, based on the time range, the 3D seismic data of the target reservoir can be determined. Based on the reference frequency step and the 3D seismic data of the target reservoir, spectral decomposition is performed on the 3D seismic data located in the target reservoir within the exploration area to obtain single-frequency volumes at different frequencies, thereby identifying multiple single-frequency volumes within the reference frequency range.

[0062] Based on the above description, since the seismic data in 3D seismic data reflects information in the time domain, the location of the target reservoir segment determined by well-seismic composite record calibration of the 3D seismic data in the exploration area contains the corresponding time information. Therefore, based on the location of the target reservoir segment, the corresponding time range can be determined, and based on the corresponding time range, the corresponding 3D seismic data can be further determined.

[0063] There are various methods for spectral decomposition of 3D seismic data located in the target reservoir section of the exploration area. In some embodiments, short-time Fourier transform, S-transform, and wavelet transform can be used to perform spectral decomposition of 3D seismic data located in the target reservoir section of the exploration area. Of course, other spectral decomposition methods can also be used to perform spectral decomposition of 3D seismic data in the target reservoir section, and this application embodiment does not limit this method.

[0064] It should be noted that for different spectral decomposition methods, the appropriate analysis window and window function type can be predetermined based on the required resolution. The aforementioned reference frequency step size is preset and is related to the signal-to-noise ratio (SNR) of the seismic data; the higher the SNR, the larger the frequency step size can be. The reference frequency range is preset; for example, it can be set to the effective frequency band of the seismic data. Furthermore, it can be adjusted according to different needs under different circumstances.

[0065] As an example, please refer to Figure 3 , Figure 3 The image shows single-frequency body profiles with frequencies of 5 Hz, 10 Hz, 15 Hz, 20 Hz, 25 Hz, 30 Hz, 35 Hz, 40 Hz, and 45 Hz after spectral decomposition.

[0066] (2) Based on the location of the target seismic reflection layer and the frequency gather data volume corresponding to the target reservoir segment, determine the baseline drift duration, sensitive frequency segment, baseline fitting method, baseline activity factor type and the range of fluid activity factors corresponding to multiple fluid types.

[0067] In some embodiments, frequency gathers corresponding to multiple reference well locations can be obtained from the frequency gather data volume corresponding to the target reservoir segment. These multiple reference well locations correspond to multiple different fluid types. Based on the location of the target seismic reflection layer and the frequency gathers corresponding to the multiple reference well locations, candidate drift durations, candidate frequency segments, and candidate fitting methods are determined. Based on the candidate drift durations, candidate frequency segments, and candidate fitting methods, the reference drift duration, sensitive frequency segment, reference fitting method, reference activity factor type, and fluid activity factor ranges corresponding to multiple fluid types are determined.

[0068] When conducting fluid detection, it is necessary to determine the characteristics of different fluids, and then perform fluid detection at the target location based on these characteristics. Therefore, determining the characteristics of different fluids is fundamental to fluid detection. Since there are multiple developed wells (completed wells) within the exploration area, the fluid types corresponding to these complete wells are defined. These complete wells, corresponding to different fluid types, can be processed to determine the characteristics of the different fluids. Therefore, in some embodiments, the reference well location is the location of a completed well within the exploration area. The frequency gather corresponding to the location of the completed well is obtained from the frequency gather data volume corresponding to the target reservoir section; this completed well location corresponds to multiple different fluid types.

[0069] Based on the above description, the locations of completed wells corresponding to multiple different fluid types within the exploration area can be determined as benchmark well point locations. Of course, in some embodiments, completed wells with high oil or high gas production within the exploration area can also be identified, and the locations of these high-yield and / or high-gas completed wells can be determined as one or two of the benchmark well point locations. That is, the locations of completed wells corresponding to oil and / or gas fluid types can be determined as one or two of the benchmark well point locations, while the locations of completed wells corresponding to other fluid types can be determined as other locations within the benchmark well point locations.

[0070] Since one or two of the benchmark well locations are locations of completed wells with high oil and / or high gas production, the characteristics of the fluid type corresponding to these high-production completed wells will be more significant, which helps to make the subsequently determined benchmark drift time, sensitive frequency range, and benchmark fitting method more accurate.

[0071] It should be noted that the aforementioned fluid type can be water well, dry well, oil well, gas well, etc. Of course, the fluid type can also be other types, and this application embodiment does not limit this.

[0072] Because the target seismic reflector layer has distinct seismic characteristics, the waveform characteristics of the seismic reflected waves generated by the target seismic reflector layer are obvious and stable. Therefore, in some embodiments, an initial isochrone can be determined based on the location of the target seismic reflector layer. Multiple amplitudes located on the initial isochrone are obtained from the frequency gathers corresponding to each reference well point location to obtain multiple initial amplitudes corresponding to each reference well point location. Multiple initial spectral characteristic curves are plotted based on multiple frequencies and multiple initial amplitudes corresponding to each reference well point location. These multiple initial spectral characteristic curves correspond one-to-one with the multiple reference well point locations. The multiple initial spectral characteristic curves are overlaid and displayed. When a frequency band reselection operation is detected, the initial isochrone is re-determined from within the target reservoir segment, and the process returns from each reference well point location. In the corresponding frequency channel set, the steps of acquiring multiple amplitudes located on the initial isochrone are carried out until the frequency segment selection operation is detected. The duration between the last determined initial isochrone and the first determined initial isochrone is determined as the candidate drift duration, and the frequency segment selected by the frequency segment selection operation is determined as the candidate frequency segment. The candidate fitting method is determined based on the last determined multiple initial spectral feature curves and the candidate frequency segment. The reselection operation is triggered when the overlaid initial spectral feature curves are not different, and the frequency segment selection operation is triggered when the overlaid initial spectral feature curves are different.

[0073] Since the seismic reflector layer within the exploration area is not a horizontal plane, the location of the target seismic reflector layer varies depending on the location of the reference well point. Therefore, for any one of the multiple reference well point locations, based on the location of the target seismic reflector layer, the time corresponding to that target seismic reflector layer is determined. The horizontal line corresponding to that time is defined as the initial isochrone for that reference well point location. The frequency gather corresponding to that reference well point location is obtained from the frequency gather data volume. Then, multiple amplitudes located on the initial isochrone are obtained from the frequency gather data of that reference well point location to obtain multiple initial amplitudes corresponding to that reference well point location. Then, based on the multiple frequencies and the initial amplitudes corresponding to those frequencies, an initial spectral characteristic curve corresponding to that reference well point location is plotted, with the horizontal axis representing frequency and the vertical axis representing amplitude. After plotting the corresponding initial spectral characteristic curve for each of the multiple reference well point locations in the same manner, multiple initial spectral characteristic curves can be obtained.

[0074] Similarly, since the seismic data in 3D seismic data reflects information in the time domain, the target seismic reflection layer identified by well-seismic composite record calibration of the 3D seismic data in the exploration area also contains the time information corresponding to that target seismic reflection layer. Therefore, the time corresponding to the target seismic reflection layer can be determined based on the location of the target seismic reflection layer corresponding to the location of the reference well point.

[0075] For any given well location, a frequency gather is provided. This frequency gather contains multiple seismic waves of different frequencies obtained after spectral decomposition of the seismic data corresponding to that well location, as well as the amplitudes of each frequency at different times. Thus, multiple amplitudes and their corresponding frequencies can be determined simultaneously. Therefore, in some embodiments, multiple amplitudes located on an initial isochrone can be obtained, that is, amplitudes corresponding to different frequencies at the same time can be obtained.

[0076] As an example, please refer to Figure 4 , Figure 4 The diagram shows the frequency gathers corresponding to reference well point location A and reference well point location B, as well as the initial spectral characteristic curve A and the initial spectral characteristic curve B. Initial spectral characteristic curve A is plotted based on the initial isochronous line A and the frequency gather corresponding to reference well point location A, while initial spectral characteristic curve B is plotted based on the initial isochronous line B and the frequency gather corresponding to reference well point location B.

[0077] In some embodiments, after the multiple initial spectral characteristic curves are overlaid, a technician can determine whether there are differences between the multiple initial spectral characteristic curves based on the overlaid initial spectral characteristic curve graph. If there are no differences between the multiple initial spectral characteristic curves, the technician can trigger a frequency band reselection operation. If there are differences between the multiple initial spectral characteristic curves, the technician can trigger a frequency band selection operation.

[0078] Since the horizontal axis of the initial spectral characteristic curve is frequency and the vertical axis is amplitude, and the frequencies corresponding to the multiple initial spectral characteristic curves are all within the reference frequency range, the multiple initial spectral characteristic curves can be overlaid and displayed. That is, the multiple initial spectral characteristic curves are displayed in the same frequency range, which is equivalent to drawing the multiple spectral characteristic curves in the same two-dimensional coordinate system.

[0079] Only when the multiple initial spectral characteristic curves show differences can the characteristics of different fluid types be extracted in subsequent steps based on these differences. Therefore, in some embodiments, a technician can determine whether there are differences among the multiple initial spectral characteristic curves based on the overlaid initial spectral characteristic curve diagram. That is, to determine whether the initial spectral characteristic curve corresponding to oil and / or gas has a frequency range sensitive to seismic wave absorption compared to other fluids. If the multiple initial spectral characteristic curves do not show differences, it means that there is no frequency range sensitive to seismic wave absorption, and the initial spectral characteristic curve determined based on the initial isochrone cannot accurately reflect the characteristics of different fluids. Therefore, it is necessary to redetermine the initial isochrone. At this time, the technician can trigger a frequency range reselection operation to reselect the initial isochrone. If the multiple initial spectral characteristic curves show differences, it means that there is a frequency range sensitive to seismic wave absorption, and the initial spectral characteristic curve determined based on the initial isochrone can accurately reflect the characteristics of different fluids. It is not necessary to redetermine the initial isochrone. Therefore, the technician can trigger a frequency range selection operation and select the frequency range sensitive to seismic wave absorption for oil and / or gas.

[0080] If the technician triggers a frequency band reselection operation, the electronic equipment can detect the frequency band reselection operation, redetermine the initial isochrones within the target reservoir segment, and return to the step of obtaining multiple amplitudes located on the initial isochrones from the frequency gathers corresponding to each reference well point location. If the technician performs a frequency band selection operation, the electronic equipment can detect this operation, and then determine the duration between the last determined initial isochrones and the first determined initial isochrones as the candidate drift duration, determine the frequency band selected by the frequency band selection operation as the candidate frequency band, and determine the candidate fitting method based on the multiple initial spectral characteristic curves determined last time and the candidate frequency band.

[0081] As an example, please refer to Figure 5 , Figure 5 The image shows the frequency gather, initial spectral characteristic curve 1, and initial spectral characteristic curve 2 corresponding to the reference well point location C. Initial spectral characteristic curve 1 is plotted based on initial isochronous line 1, and initial spectral characteristic curve 2 is plotted based on initial isochronous line 2. Initial isochronous line 1 is the first determined initial isochronous line, and initial isochronous line 2 is the last determined initial isochronous line. Therefore, the candidate drift duration can be determined as the duration between initial isochronous line 1 and initial isochronous line 2.

[0082] Since the fluid detection method provided in this application embodiment can be used to predict the spatial distribution characteristics of oil and gas, in some embodiments, those skilled in the art can determine the frequency bands that produce high-frequency attenuation and / or low-frequency resonance as the sensitive frequency bands for oil and / or gas absorption of seismic waves. That is, based on the initial spectral characteristic curve displayed by the overlay, the sensitive frequency bands for oil and / or gas absorption of seismic waves are determined, and then the sensitive frequency bands for oil and / or gas absorption of seismic waves are determined as candidate frequency bands.

[0083] It should be noted that for any one of these initial spectral characteristic curves, the frequency corresponding to the peak value of that initial spectral characteristic curve is determined as the dominant frequency. In this case, the aforementioned high-frequency attenuation refers to a decrease in the amplitude of the initial spectral characteristic curve in the range of frequencies greater than the dominant frequency. Low-frequency resonance refers to an increase in the amplitude of the initial spectral characteristic curve in the range of frequencies less than the dominant frequency.

[0084] In some embodiments, curve segments located within candidate frequency ranges are obtained from the last determined plurality of initial spectral feature curves to obtain plurality of candidate curve segments. If the plurality of candidate curve segments do not have frequency traps, the candidate fitting method is determined to be a linear fitting method. The frequency trap refers to the spectral feature curve containing at least two peaks. If the plurality of candidate curve segments have frequency traps, the candidate fitting method is determined to be a quadratic polynomial fitting method.

[0085] To ensure the ability to distinguish different types of fluids on the same dimension, it is necessary to ensure that the fluid parameters corresponding to these different fluid types are consistent when determining the fluid parameters. If the fluid parameters corresponding to these different fluid types are inconsistent, it will be difficult to determine the differences between different fluids based on the different fluid parameters. Therefore, when determining candidate frequency bands, technicians can select curve segments with consistency within the candidate frequency band; that is, multiple curve segments within the candidate frequency band that all have frequency dips or none of them have frequency dips.

[0086] In some embodiments, fluid parameters of all completed wells in the exploration area can be determined based on candidate drift duration, candidate frequency range, and candidate fitting method. The fluid parameters of all completed wells in the exploration area are displayed. When a determination operation is detected, the candidate drift duration, candidate frequency range, and candidate fitting method are determined as the baseline drift duration, sensitive frequency range, and baseline fitting method. This determination operation is triggered when the same fluid parameter in all completed wells has the same pattern. The fluid parameters of all completed wells in the exploration area are plotted into a scatter plot and displayed. The scatter plot includes multiple parameter types. When a parameter selection operation is detected, the parameter type selected by the parameter selection operation is determined as the baseline activity factor type. This parameter selection operation is triggered based on the scatter plot. Based on the baseline activity factor type, the fluid activity factor range corresponding to each of the multiple fluid types is determined.

[0087] If the candidate fitting method is a first-order linear fitting method, the fluid parameters determined by this fitting method are the intercept and gradient. If the candidate fitting method is a second-order linear fitting method, the fluid parameters determined by this fitting method are the quadratic coefficients, the first-order coefficients, and the constant term.

[0088] As an example, please refer to Figure 6 and Figure 7 , Figure 6 The fitting method shown is a linear fitting method. The fluid parameters determined by the linear fitting method are the intercept and the gradient, where the intercept is 200 and the gradient is 140. Figure 7 The fitting method shown is quadratic linear fitting. The fluid parameters determined by quadratic linear fitting are quadratic coefficients, linear coefficients, and constants. The quadratic coefficient is -7.5, the linear coefficient is 365, and the constant is -1300.

[0089] In some embodiments, technicians can determine whether the fluid parameters corresponding to different fluid types have the same pattern based on the fluid parameters of all completed wells in the exploration area. That is, based on the multiple fluid parameters, it is determined whether different fluid types can be distinguished based on the multiple fluid parameters. If the multiple fluid parameters can distinguish different fluid types, it means that the candidate drift duration, candidate frequency range, and candidate fitting method determined in the above steps can extract the characteristics of different fluid types. Therefore, technicians can trigger a determination operation. If the multiple fluid parameters cannot distinguish different fluid types, it means that the candidate drift duration, candidate frequency range, and candidate fitting method determined in the above steps cannot extract the characteristics of different fluid types. Therefore, in some embodiments, technicians can redetermine the initial isochrones from the target reservoir section and return to the step of obtaining multiple amplitudes located on the initial isochrones from the frequency gathers corresponding to each reference well point location, and then redetermine the candidate drift duration, candidate frequency range, and candidate fitting method according to the above steps. In other embodiments, technicians may not redetermine the initial isochrones, but can redetermine the candidate frequency range, and then redetermine the candidate fitting method according to the above steps. At this point, since the initial isochrones remain unchanged, the candidate drift duration also remains unchanged.

[0090] If a technician triggers a determination operation, the electronic equipment can detect this operation and then plot a scatter plot of the fluid parameters for all completed wells in the exploration area. Based on this scatter plot, the technician can determine the parameter types that distinguish different fluid types and trigger a parameter selection operation to choose the parameter type that differentiates them. The electronic equipment can then detect this parameter selection operation and designate the selected parameter type as the baseline activity factor type.

[0091] In some embodiments, based on the baseline activity factor type, baseline activity factors corresponding to multiple completed wells of the same fluid type can be extracted from the fluid parameters of all completed wells in the exploration area. For any one of these fluid types, the maximum value among the baseline activity factors of the multiple completed wells corresponding to that fluid type is determined as the maximum value of the fluid activity factor range corresponding to that fluid type, and the minimum value among the baseline activity factors of the multiple completed wells corresponding to that fluid type is determined as the minimum value of the fluid activity factor range corresponding to that fluid type, thereby obtaining the fluid activity factor range corresponding to that fluid type. The fluid activity factor range corresponding to each of the multiple fluid types can be determined in the same way, thus obtaining the fluid activity factor range corresponding to each of the multiple fluid types.

[0092] Based on the above description, after determining the candidate drift duration, candidate frequency range, and candidate fitting method, these methods can be tested on all completed wells in the exploration area to further determine whether they can withstand the test of most completed wells. That is, based on these candidate drift duration, candidate frequency range, and candidate fitting method, it can be determined whether features of different fluid types can be extracted. If it is determined that the candidate drift duration, candidate frequency range, and candidate fitting method can extract features of different fluid types, then these methods are determined as the baseline drift duration, sensitive frequency range, and baseline fitting method, and subsequent steps are then performed.

[0093] Of course, in other embodiments, the candidate drift duration, candidate frequency range, and candidate fitting method can be directly determined as the baseline drift duration, sensitive frequency range, and baseline fitting method, and then subsequent steps can be performed. This application does not limit this.

[0094] After determining the reference drift duration, sensitive frequency range, and reference fitting method, steps 101-107 can be executed based on the reference drift duration, sensitive frequency range, and reference fitting method to detect the fluid at the target location.

[0095] Based on the above description, before executing steps 101-107, the location of the target seismic reflection layer and the frequency gather data corresponding to the target reservoir segment have been determined. Therefore, in some embodiments, the electronic device pre-stores the frequency gather data corresponding to the target reservoir segment in the exploration area. Thus, the frequency gather data corresponding to the target reservoir segment in the exploration area can be obtained, and then the frequency gather corresponding to the target location to be detected for fluid can be obtained from the frequency gather data corresponding to the target reservoir segment in the exploration area.

[0096] Step 102: Obtain multiple amplitudes located on the reference isochron from the seismic wave data of multiple frequencies included in the frequency gather of the target location. These multiple amplitudes correspond one-to-one with multiple frequencies. The reference isochron is determined based on the location of the target seismic reflection layer and the reference drift time. The target seismic reflection layer refers to the seismic reflection layer that is closest to the target reservoir section.

[0097] Based on the above description, the electronic device predetermines the reference drift time and the location of the target seismic reflection layer. In this way, the electronic device can determine the time corresponding to the target seismic reflection layer based on the location of the target seismic reflection layer. Then, by adding the time corresponding to the target seismic reflection layer to the reference drift time, the time corresponding to the reference isochrone can be obtained.

[0098] Step 103: Plot the target spectral characteristic curve based on multiple frequencies and multiple amplitudes.

[0099] Step 104: Obtain the target curve segment located within the sensitive frequency range from the target spectral characteristic curve. The sensitive frequency range refers to the frequency range in which oil and gas are sensitive to the absorption of seismic waves.

[0100] Based on the above description, the electronic device predetermines the frequency range corresponding to the sensitive frequency band. In this way, the electronic device can obtain the target curve segment located within the sensitive frequency band from the target spectral characteristic curve.

[0101] Step 105: Fit the target curve segment according to the benchmark fitting method to obtain multiple fluid parameters corresponding to the target position.

[0102] Based on the above description, the electronic device predetermines the benchmark fitting method. In this way, the electronic device can fit the target curve segment according to the benchmark fitting method to obtain multiple fluid parameters corresponding to the target position.

[0103] If the baseline fitting method is a first-order linear fitting method, the fluid parameters determined by this fitting method are the intercept and gradient. If the baseline fitting method is a second-order linear fitting method, the fluid parameters determined by this fitting method are the quadratic coefficients, the first-order coefficients, and the constant term.

[0104] Step 106: Select the fluid parameter of the reference activity factor type from multiple fluid parameters as the target fluid activity factor. The reference activity factor type refers to the type of fluid parameter required to distinguish multiple different types of fluids.

[0105] Based on the above description, the electronic device predetermines the reference activity factor type. In this way, the electronic device can select the fluid parameter with the reference activity factor type as the target fluid activity factor from multiple fluid parameters based on the reference activity factor type.

[0106] In some embodiments, if the benchmark fitting method is a first-order linear fitting method, the benchmark activity factor can be at least one of intercept and gradient; if the benchmark fitting method is a second-order linear fitting method, the benchmark activity factor can be at least one of quadratic coefficient, first-order coefficient, and constant term.

[0107] Step 107: If the target fluid activity factor is within the range of fluid activity factors corresponding to the target fluid type, then the fluid type at the target location is determined as the target fluid type, which is one of multiple fluid types.

[0108] Based on the above description, the electronic device predetermines the correspondence between fluid type and fluid activity factor range. In this way, the target fluid activity factor can be compared with each fluid activity factor range in the correspondence. If the target fluid activity factor is within a certain fluid activity factor range, the fluid type corresponding to that fluid activity factor range is taken as the target fluid type, and then the target fluid type is determined as the fluid type of the target location.

[0109] This application embodiment determines the target fluid activity factor by fitting the spectral characteristic curve of the sensitive frequency band. Since this target fluid activity factor is obtained through multi-point fitting, it accurately reflects the characteristics of the fluid type at the target location. Furthermore, because the type of the benchmark activity factor can distinguish the types of fluid parameters required for multiple different types of fluids, the fluid parameters determined based on this benchmark activity factor accurately reflect the differences between different types of fluids. This improves the accuracy of fluid detection, thereby reducing the risk of drilling failure. Moreover, after determining the candidate drift duration, candidate frequency band, and candidate fitting method, this application embodiment can also test these candidate drift duration, candidate frequency band, and candidate fitting method to further ensure that the characteristics of different fluid types can be extracted based on them. This makes the subsequent fluid detection results more accurate.

[0110] Figure 8 This is a schematic diagram of a fluid detection device provided in an embodiment of this application. The fluid detection device can be implemented as part or all of an electronic device through software, hardware, or a combination of both. Please refer to... Figure 8 The device includes: a first acquisition module 801, a second acquisition module 802, a drawing module 803, a third acquisition module 804, a fitting module 805, a selection module 806, and a first determination module 807.

[0111] The first acquisition module 801 is used to acquire the frequency gather corresponding to the target location to be detected for fluid from the frequency gather data volume corresponding to the target reservoir section in the exploration area. The frequency gather data volume includes frequency gathers corresponding to multiple seismic traces, and the frequency gathers include seismic wave data of multiple frequencies from the same seismic trace. For detailed implementation processes, please refer to the corresponding contents in the above embodiments, which will not be repeated here.

[0112] The second acquisition module 802 is used to acquire multiple amplitudes located on a reference isochrone from seismic wave data of multiple frequencies included in the frequency gather at the target location. These multiple amplitudes correspond one-to-one with multiple frequencies. The reference isochrone is determined based on the location of the target seismic reflection layer and the reference drift duration. The target seismic reflection layer refers to the seismic reflection layer closest to the target reservoir section. Detailed implementation processes are described in the corresponding contents of the above embodiments and will not be repeated here.

[0113] The plotting module 803 is used to plot the target spectral characteristic curve based on multiple frequencies and multiple amplitudes. For detailed implementation details, please refer to the corresponding content in the above embodiments; they will not be repeated here.

[0114] The third acquisition module 804 is used to acquire the target curve segment located within the sensitive frequency range from the target spectral characteristic curve. This sensitive frequency range refers to the frequency range where oil and gas are sensitive to seismic wave absorption. For detailed implementation processes, please refer to the corresponding content in the above embodiments; they will not be repeated here.

[0115] The fitting module 805 is used to fit the target curve segment according to the benchmark fitting method to obtain multiple fluid parameters corresponding to the target position. For detailed implementation processes, please refer to the corresponding contents in the above embodiments, which will not be repeated here.

[0116] Selection module 806 is used to select a fluid parameter of type reference activity factor from multiple fluid parameters as the target fluid activity factor. This reference activity factor type refers to the type of fluid parameter required to distinguish between multiple different types of fluids. Detailed implementation processes are described in the corresponding contents of the above embodiments and will not be repeated here.

[0117] The first determining module 807 is used to determine the fluid type at the target location as the target fluid type if the target fluid activity factor is within the range of fluid activity factors corresponding to the target fluid type. The target fluid type is one of multiple fluid types. For detailed implementation processes, please refer to the corresponding contents in the above embodiments, which will not be repeated here.

[0118] Optionally, the device further includes:

[0119] The second determination module is used to determine the location of the target seismic reflection layer and the frequency gather data volume corresponding to the target reservoir segment;

[0120] The third determination module is used to determine the baseline drift duration, sensitive frequency band, baseline fitting method, baseline activity factor type, and fluid activity factor range corresponding to multiple fluid types based on the location of the target seismic reflection layer and the frequency gather data volume corresponding to the target reservoir segment.

[0121] Optionally, the second determining module is specifically used for:

[0122] Using drilling, logging, and geological data from the exploration area, well-seismic composite records are calibrated to determine the location of the target reservoir section and the target seismic reflection layer.

[0123] Based on the location of the target reservoir section, the reference frequency range, and the reference frequency step size, the spectral decomposition of the three-dimensional seismic data located in the target reservoir section in the exploration area is performed to obtain single-frequency volumes of multiple frequencies. Each single-frequency volume includes seismic wave data from multiple seismic traces at the same frequency.

[0124] Seismic wave data from the same seismic trace in multiple single-frequency volumes are merged to obtain the frequency gather data volume corresponding to the target reservoir segment.

[0125] Optionally, the third determining module includes:

[0126] The acquisition unit is used to acquire frequency gathers corresponding to multiple reference well locations from the frequency gather data volume corresponding to the target reservoir section. These multiple reference well locations correspond to multiple different fluid types.

[0127] The first determining unit is used to determine candidate drift duration, candidate frequency band and candidate fitting method based on the location of the target seismic reflection layer and the frequency gathers corresponding to the locations of multiple reference well points.

[0128] The second determining unit is used to determine the baseline drift duration, sensitive frequency range, baseline fitting method, baseline activity factor type, and fluid activity factor range corresponding to multiple fluid types based on the candidate drift duration, candidate frequency range, and candidate fitting method.

[0129] Optionally, the first determining unit includes:

[0130] The first defined sub-unit is used to determine the initial isochrona based on the location of the target seismic reflector layer;

[0131] The sub-unit is used to obtain multiple amplitudes located on the initial isochrona from the frequency gather corresponding to each reference well point location, so as to obtain multiple initial amplitudes corresponding to each reference well point location.

[0132] The drawing sub-unit is used to draw multiple initial spectral characteristic curves based on multiple frequencies and multiple initial amplitudes corresponding to each reference well point position. These multiple initial spectral characteristic curves correspond one-to-one with multiple reference well point positions.

[0133] The display subunit is used to overlay and display multiple initial spectral characteristic curves;

[0134] The second determining subunit is used to redetermine the initial isochrone from the target reservoir segment when a frequency segment reselection operation is detected, and return to the step of obtaining multiple amplitudes located on the initial isochrone from the frequency gather corresponding to each reference well point location, until a frequency segment selection operation is detected. The duration between the last determined initial isochrone and the first determined initial isochrone is then determined as the candidate drift duration, the frequency segment selected by the frequency segment selection operation is determined as the candidate frequency segment, and the candidate fitting method is determined based on the multiple initial spectral characteristic curves and the candidate frequency segment determined in the last time.

[0135] The reselection operation is triggered when the initial spectral characteristic curves of the overlay display are not different, while the frequency band selection operation is triggered when the initial spectral characteristic curves of the overlay display are different.

[0136] Optionally, the second determined subunit is specifically used for:

[0137] From the last determined multiple initial spectral characteristic curves, obtain the curve segments located within the candidate frequency range to obtain multiple candidate curve segments;

[0138] If multiple candidate curve segments do not have frequency traps, then the candidate fitting method is determined to be a linear fitting method. A frequency trap refers to a spectral feature curve that contains at least two peaks.

[0139] If multiple candidate curve segments have frequency traps, then the candidate fitting method is determined to be the quadratic polynomial fitting method.

[0140] Optionally, the second determining unit is specifically used for:

[0141] Based on candidate drift duration, candidate frequency range and candidate fitting method, the fluid parameters of all completed wells in the exploration area are determined;

[0142] Displays fluid parameters for all completed wells in the exploration area;

[0143] When a deterministic operation is detected, the candidate drift duration, candidate frequency range, and candidate fitting method are determined as the baseline drift duration, sensitive frequency range, and baseline fitting method. The deterministic operation is triggered when the same fluid parameter has the same pattern in all completed wells.

[0144] The fluid parameters of all completed wells in the exploration area are plotted as a scatter plot;

[0145] Display a scatter plot that includes multiple parameter types;

[0146] When a parameter selection operation is detected, the parameter type selected in the parameter selection operation is determined as the baseline activity factor type. This parameter selection operation is triggered based on the scatter plot.

[0147] Based on the baseline activity factor type, the range of fluid activity factors corresponding to each fluid type among multiple fluid types is determined.

[0148] This application embodiment determines the target fluid activity factor by fitting the spectral characteristic curve of the sensitive frequency band. Since this target fluid activity factor is obtained through multi-point fitting, it accurately reflects the characteristics of the fluid type at the target location. Furthermore, because the type of the benchmark activity factor can distinguish the types of fluid parameters required for multiple different types of fluids, the fluid parameters determined based on this benchmark activity factor accurately reflect the differences between different types of fluids. This improves the accuracy of fluid detection, thereby reducing the risk of drilling failure. Moreover, after determining the candidate drift duration, candidate frequency band, and candidate fitting method, this application embodiment can also test these candidate drift duration, candidate frequency band, and candidate fitting method to further ensure that the characteristics of different fluid types can be extracted based on them. This makes the subsequent fluid detection results more accurate.

[0149] It should be noted that the fluid detection device provided in the above embodiments is only illustrated by the division of the functional modules described above. In practical applications, the functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the fluid detection device and the fluid detection method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0150] Figure 9 This is a structural block diagram of an electronic device 900 provided in an embodiment of this application. The electronic device 900 can be a portable mobile electronic device, such as a smartphone, tablet computer, laptop computer, or desktop computer. The electronic device 900 may also be referred to as user equipment, portable terminal, laptop terminal, desktop terminal, or other names.

[0151] Typically, electronic device 900 includes a processor 901 and a memory 902.

[0152] Processor 901 may include one or more processing cores, such as a quad-core processor or an octa-core processor. Processor 901 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 901 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 901 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 901 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0153] The memory 902 may include one or more computer-readable storage media, which may be non-transitory. The memory 902 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 902 are used to store at least one instruction, which is executed by the processor 901 to implement the fluid detection method provided in the method embodiments of this application.

[0154] In some embodiments, the electronic device 900 may optionally include a peripheral device interface 903 and at least one peripheral device. The processor 901, memory 902, and peripheral device interface 903 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 903 via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of the following: a radio frequency circuit 904, a touch display screen 905, a camera 906, an audio circuit 907, a positioning component 908, and a power supply 909.

[0155] Peripheral device interface 903 can be used to connect at least one I / O (Input / Output) related peripheral device to processor 901 and memory 902. In some embodiments, processor 901, memory 902 and peripheral device interface 903 are integrated on the same chip or circuit board; in some other embodiments, any one or two of processor 901, memory 902 and peripheral device interface 903 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0156] The radio frequency (RF) circuit 904 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 904 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 904 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. Optionally, the RF circuit 904 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The RF circuit 904 can communicate with other electronic devices through at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 904 may also include circuitry related to NFC (Near Field Communication), which is not limited in this application embodiment.

[0157] Display screen 905 is used to display a UI (User Interface). This UI may include graphics, text, icons, videos, and any combination thereof. When display screen 905 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 901 for processing. In this case, display screen 905 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there may be one display screen 905, which serves as the front panel of electronic device 900; in other embodiments, there may be at least two display screens 905, respectively disposed on different surfaces of electronic device 900 or in a folded design; in still other embodiments, display screen 905 may be a flexible display screen, disposed on a curved or folded surface of electronic device 900. Furthermore, display screen 905 may be configured as a non-rectangular irregular shape, i.e., a non-rectangular screen. Display screen 905 may be made of materials such as LCD (Liquid Crystal Display) or OLED (Organic Light-Emitting Diode).

[0158] The camera assembly 906 is used to acquire images or videos. Optionally, the camera assembly 906 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is located on the front panel of the electronic device, and the rear-facing camera is located on the back of the electronic device. In some embodiments, there are at least two rear-facing cameras, which are any one of a main camera, a depth-sensing camera, a wide-angle camera, and a telephoto camera, to achieve background blurring by fusion of the main camera and the depth-sensing camera, panoramic shooting by fusion of the main camera and the wide-angle camera, VR (Virtual Reality) shooting, or other fusion shooting functions. In some embodiments, the camera assembly 906 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm-light flash and a cool-light flash, which can be used for light compensation at different color temperatures.

[0159] The audio circuit 907 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, converting the sound waves into electrical signals that are input to the processor 901 for processing, or input to the radio frequency circuit 904 for voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, each located in a different part of the electronic device 900. The microphone may also be an array microphone or an omnidirectional microphone. The speaker is used to convert the electrical signals from the processor 901 or the radio frequency circuit 904 into sound waves. The speaker may be a conventional diaphragm speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement. In some embodiments, the audio circuit 907 may also include a headphone jack.

[0160] Positioning component 908 is used to locate the current geographic location of electronic device 900 for navigation or LBS (Location Based Service). Positioning component 908 can be a positioning component based on the US GPS (Global Positioning System), China's BeiDou system, or Russia's Galileo system.

[0161] Power supply 909 is used to supply power to various components in electronic device 900. Power supply 909 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 909 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, while 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.

[0162] Those skilled in the art will understand that Figure 9 The structure shown does not constitute a limitation on the electronic device 900, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0163] In some embodiments, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the steps of the fluid detection method described above. For example, the computer-readable storage medium may be a ROM, RAM, CD-ROM, magnetic tape, floppy disk, or optical data storage device.

[0164] It is worth noting that the computer-readable storage medium mentioned in the embodiments of this application can be a non-volatile storage medium, in other words, it can be a non-transient storage medium.

[0165] It should be understood that all or part of the steps of the above embodiments can be implemented by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented wholly or partially in the form of a computer program product. The computer program product includes one or more computer instructions. The computer instructions can be stored in the above-described computer-readable storage medium.

[0166] That is, in some embodiments, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to perform the steps of the fluid detection method described above.

[0167] It should be understood that "at least one" as mentioned herein refers to one or more, and "multiple" refers to two or more. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B; "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. In addition, in order to clearly describe the technical solutions of the embodiments of this application, the terms "first," "second," etc., are used in the embodiments of this application to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first," "second," etc., do not limit the quantity or execution order, and the terms "first," "second," etc., are not necessarily different.

[0168] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in the embodiments of this application are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the drilling data, well logging data, geological data, and 3D seismic data of the exploration area involved in the embodiments of this application were all obtained with full authorization.

[0169] The above descriptions are embodiments provided in this application and are not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A fluid detection method, characterized in that, The method includes: From the frequency gather data volume corresponding to the target reservoir section in the exploration area, obtain the frequency gather corresponding to the target location to be detected for fluid. The frequency gather data volume includes frequency gathers corresponding to multiple seismic traces, and the frequency gathers include seismic wave data of multiple frequencies of the same seismic trace. From the seismic wave data of multiple frequencies included in the frequency gather of the target location, multiple amplitudes located on the reference isochrone are obtained. The multiple amplitudes correspond one-to-one with the multiple frequencies. The reference isochrone is determined based on the location of the target seismic reflection layer and the reference drift time. The target seismic reflection layer refers to the seismic reflection layer that is closest to the target reservoir section. Based on the multiple frequencies and multiple amplitudes, plot the target spectral characteristic curve; Obtain the target curve segment located within the sensitive frequency range from the target spectral characteristic curve, where the sensitive frequency range refers to the frequency range where oil and gas are sensitive to seismic wave absorption; The target curve segment is fitted according to a benchmark fitting method to obtain multiple fluid parameters corresponding to the target location. The benchmark fitting method is a candidate fitting method when a determination operation is detected. The determination operation is triggered when the same fluid parameter in all completed wells has the same pattern. The candidate fitting method is determined based on the location of the target seismic reflection layer and the frequency gathers corresponding to multiple benchmark well locations. The multiple benchmark well locations correspond to multiple different fluid types. The frequency gathers corresponding to the multiple benchmark well locations are obtained from the frequency gather data volume corresponding to the target reservoir segment. From the plurality of fluid parameters, select the fluid parameter with the parameter type of the reference activity factor type as the target fluid activity factor. The reference activity factor type refers to the type of fluid parameter required to distinguish multiple different types of fluids. If the target fluid activity factor is within the range of fluid activity factors corresponding to the target fluid type, then the fluid type at the target location is determined to be the target fluid type, and the target fluid type is one of multiple fluid types.

2. The method as described in claim 1, characterized in that, Before obtaining the frequency gather corresponding to the target location for fluid detection from the frequency gather data volume corresponding to the target reservoir segment in the exploration area, the method further includes: Determine the location of the target seismic reflection layer and the frequency gather data volume corresponding to the target reservoir segment; Based on the location of the target seismic reflection layer and the frequency gather data volume corresponding to the target reservoir segment, the baseline drift duration, the sensitive frequency band, the baseline fitting method, the baseline activity factor type, and the fluid activity factor range corresponding to the multiple fluid types are determined.

3. The method as described in claim 2, characterized in that, The step of determining the location of the target seismic reflection layer and the frequency gather data volume corresponding to the target reservoir segment includes: Using drilling, logging, and geological data from the exploration area, well-seismic composite records are calibrated for the three-dimensional seismic data of the exploration area to determine the location of the target reservoir section and the location of the target seismic reflection layer. Based on the location of the target reservoir segment, the reference frequency range, and the reference frequency step size, the three-dimensional seismic data located in the target reservoir segment in the exploration area are subjected to spectral decomposition to obtain single-frequency volumes of the multiple frequencies. The single-frequency volume includes seismic wave data of the multiple seismic traces at the same frequency. Seismic wave data from the same seismic trace in the multiple frequency single-frequency volumes are merged to obtain the frequency gather data volume corresponding to the target reservoir segment.

4. The method as described in claim 2, characterized in that, The determination of the reference drift duration, the sensitive frequency band, the reference fitting method, the reference activity factor type, and the fluid activity factor range corresponding to the multiple fluid types based on the location of the target seismic reflection layer and the frequency gather data volume corresponding to the target reservoir segment includes: From the frequency gather data volume corresponding to the target reservoir section, obtain the frequency gathers corresponding to multiple reference well locations, and the multiple reference well locations correspond to multiple different fluid types; Based on the location of the target seismic reflection layer and the frequency gathers corresponding to the locations of the multiple reference well points, candidate drift durations, candidate frequency bands, and candidate fitting methods are determined. Based on the candidate drift duration, the candidate frequency band, and the candidate fitting method, the baseline drift duration, the sensitive frequency band, the baseline fitting method, the baseline activity factor type, and the fluid activity factor range corresponding to the multiple fluid types are determined.

5. The method as described in claim 4, characterized in that, The process of determining candidate drift durations, candidate frequency bands, and candidate fitting methods based on the location of the target seismic reflection layer and the frequency gathers corresponding to the locations of the multiple reference well points includes: Determine the initial isochrones based on the location of the target seismic reflector layer; From the frequency channel set corresponding to each reference well point location, multiple amplitudes located on the initial isochrona are obtained to obtain multiple initial amplitudes corresponding to each reference well point location; Multiple initial spectral feature curves are plotted based on the multiple frequencies and multiple initial amplitudes corresponding to each reference well point position, and the multiple initial spectral feature curves correspond one-to-one with the multiple reference well point positions; The multiple initial spectral feature curves are overlaid and displayed; When a frequency segment reselection operation is detected, the initial isochrone is re-determined from the target reservoir segment, and the steps of obtaining multiple amplitudes located on the initial isochrone from the frequency gather corresponding to each reference well point location are repeated until a frequency segment selection operation is detected. The duration between the last determined initial isochrone and the first determined initial isochrone is then determined as the candidate drift duration, and the frequency segment selected by the frequency segment selection operation is determined as the candidate frequency segment. The candidate fitting method is determined based on the multiple initial spectral feature curves determined last time and the candidate frequency segment. The reselection operation is triggered when the initial spectral characteristic curves of the overlay display are not different, while the frequency band selection operation is triggered when the initial spectral characteristic curves of the overlay display are different.

6. The method as described in claim 5, characterized in that, The step of determining the candidate fitting method based on the last determined multiple initial spectral feature curves and the candidate frequency bands includes: From the last determined plurality of initial spectral feature curves, obtain curve segments located within the candidate frequency range to obtain a plurality of candidate curve segments; If the candidate curve segments do not have frequency traps, then the candidate fitting method is determined to be a linear fitting method, where a frequency trap refers to a spectral feature curve containing at least two peaks. If the multiple candidate curve segments have frequency traps, then the candidate fitting method is determined to be a quadratic polynomial fitting method.

7. The method as described in claim 4, characterized in that, The step of determining the baseline drift duration, the sensitive frequency band, the baseline fitting method, the baseline activity factor type, and the fluid activity factor range corresponding to the multiple fluid types based on the candidate drift duration, the candidate frequency band, and the candidate fitting method includes: Based on the candidate drift duration, the candidate frequency range, and the candidate fitting method, the fluid parameters of all completed wells in the exploration area are determined; Displays the fluid parameters of all completed wells in the exploration area; When a determination operation is detected, the candidate drift duration, the candidate frequency range, and the candidate fitting method are determined as the benchmark drift duration, the sensitive frequency range, and the benchmark fitting method. The determination operation is triggered when the same fluid parameter in all completed wells has the same pattern. The fluid parameters of all completed wells in the exploration area are plotted as a scatter plot; The scatter plot is displayed, and the scatter plot includes multiple parameter types; When a parameter selection operation is detected, the parameter type selected by the parameter selection operation is determined as the baseline activity factor type, and the parameter selection operation is triggered based on the scatter plot; Based on the benchmark activity factor type, the fluid activity factor range corresponding to each of the plurality of fluid types is determined.

8. An electronic device, characterized in that, The electronic device includes a processor, the processor being configured to: From the frequency gather data volume corresponding to the target reservoir section in the exploration area, obtain the frequency gather corresponding to the target location to be detected for fluid. The frequency gather data volume includes frequency gathers corresponding to multiple seismic traces, and the frequency gathers include seismic wave data of multiple frequencies of the same seismic trace. From the seismic wave data of multiple frequencies included in the frequency gather of the target location, multiple amplitudes located on the reference isochrone are obtained. The multiple amplitudes correspond one-to-one with the multiple frequencies. The reference isochrone is determined based on the location of the target seismic reflection layer and the reference drift time. The target seismic reflection layer refers to the seismic reflection layer that is closest to the target reservoir section. Based on the multiple frequencies and multiple amplitudes, plot the target spectral characteristic curve; Obtain the target curve segment located within the sensitive frequency range from the target spectral characteristic curve, where the sensitive frequency range refers to the frequency range where oil and gas are sensitive to seismic wave absorption; The target curve segment is fitted according to a benchmark fitting method to obtain multiple fluid parameters corresponding to the target location. The benchmark fitting method is a candidate fitting method when a determination operation is detected. The determination operation is triggered when the same fluid parameter in all completed wells has the same pattern. The candidate fitting method is determined based on the location of the target seismic reflection layer and the frequency gathers corresponding to multiple benchmark well locations. The multiple benchmark well locations correspond to multiple different fluid types. The frequency gathers corresponding to the multiple benchmark well locations are obtained from the frequency gather data volume corresponding to the target reservoir segment. From the plurality of fluid parameters, select the fluid parameter with the parameter type of the reference activity factor type as the target fluid activity factor. The reference activity factor type refers to the type of fluid parameter required to distinguish multiple different types of fluids. If the target fluid activity factor is within the range of fluid activity factors corresponding to the target fluid type, then the fluid type at the target location is determined to be the target fluid type, and the target fluid type is one of multiple fluid types.

9. The electronic device as claimed in claim 8, characterized in that, The processor is also used for: Determine the location of the target seismic reflection layer and the frequency gather data volume corresponding to the target reservoir segment; Based on the location of the target seismic reflection layer and the frequency gather data volume corresponding to the target reservoir segment, the baseline drift duration, the sensitive frequency band, the baseline fitting method, the baseline activity factor type, and the fluid activity factor range corresponding to the multiple fluid types are determined.

10. The electronic device as claimed in claim 9, characterized in that, The processor is also used for: Using drilling, logging, and geological data from the exploration area, well-seismic composite records are calibrated for the three-dimensional seismic data of the exploration area to determine the location of the target reservoir section and the location of the target seismic reflection layer. Based on the location of the target reservoir segment, the reference frequency range, and the reference frequency step size, the three-dimensional seismic data located in the target reservoir segment in the exploration area are subjected to spectral decomposition to obtain single-frequency volumes of the multiple frequencies. The single-frequency volume includes seismic wave data of the multiple seismic traces at the same frequency. Seismic wave data from the same seismic trace in the multiple frequency single-frequency volumes are merged to obtain the frequency gather data volume corresponding to the target reservoir segment.

Images