CN114428322A - Method and device for predicting thickness of thin reservoir based on frequency attribute - Google Patents
Method and device for predicting thickness of thin reservoir based on frequency attribute Download PDFInfo
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- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
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Abstract
The application discloses a method and a device for predicting the thickness of a thin reservoir based on frequency attributes, wherein the method comprises the following steps: determining the position of a target layer, the time of seismic waves reaching the top of the target layer and the time of the seismic waves reaching the bottom of the target layer; determining a forward model of the thickness change of the thin reservoir according to the logging information, and determining the change condition of the seismic wave frequency of the target layer along with the thickness change of the thin reservoir; setting a time window and extracting the frequency attribute of a target layer; determining a forward model of the thickness change of the stratum of the target layer according to the logging information, and determining the rule that the frequency of the seismic waves of the target layer changes along with the thickness change of the stratum of the target layer; determining the stratum thickness of a target layer according to the three-dimensional seismic horizon interpretation and well logging information; correcting the frequency attribute of the target layer according to the rule that the frequency of the seismic wave of the target layer changes along with the thickness of the stratum of the target layer and the thickness of the stratum of the target layer; and predicting the thickness of the thin reservoir according to the corrected frequency attribute of the target layer. The method and the device can improve the accuracy of thin reservoir thickness prediction.
Description
Technical Field
The application relates to the technical field of geophysical exploration of petroleum, in particular to a method and a device for predicting the thickness of a thin reservoir based on frequency attributes.
Background
This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
At present, most of oil field exploration objects in China are thin reservoir layers with the thickness smaller than one-fourth seismic wave wavelength, and how to determine the thickness of the thin reservoir layers also becomes a problem of key research in seismic reservoir layer prediction at present. The method for predicting the thickness of the thin reservoir mainly comprises two types, one type is high-resolution inversion, such as model inversion, seismic statistics inversion, waveform characteristic indication inversion and the like, the method starts from a high-frequency model established among wells and combines the seismic inversion to obtain a high-resolution lithological section, but the method is adopted on the premise that a work area is provided with a sufficient number of exploratory wells, the exploratory wells are distributed uniformly, and therefore a proper model can be established, and the use of the method is greatly limited; the other type is to predict by using seismic attributes such as amplitude attribute, frequency attribute, phase attribute and the like, and the method usually starts from a forward model, finds out the rule of various seismic attributes changing along with the thickness of the reservoir, and then analyzes seismic data by using the rule, thereby predicting the thickness and distribution of the thin reservoir. However, in the actual stratum, not only the thickness of the thin reservoir varies, but also the thickness of the target stratum, the overburden stratum or the underburden where the thin reservoir is located varies, and the seismic response caused by the variation is obviously greater than that caused by the variation of the thickness of the thin reservoir, so that the accuracy of the thin reservoir thickness prediction is low.
Taking the frequency attribute as an example, since the thin reservoir cannot observe top and bottom reflection on the seismic profile, but can cause the change of the frequency value, it is feasible to predict the thickness of the thin reservoir by using the lateral change of the frequency value, which is also a widely applied technology at present. But the factors causing the frequency change include other factors besides the thin reservoir thickness, and the factors can interfere the prediction of the thin reservoir thickness, so that the prediction result of the thin reservoir thickness is inaccurate.
Disclosure of Invention
The embodiment of the application provides a method for predicting the thickness of a thin reservoir based on a frequency attribute, which is used for improving the accuracy of predicting the thickness of the thin reservoir based on the frequency attribute and comprises the following steps:
acquiring seismic data and logging data in a work area, performing synthetic record calibration, and determining the position of a target layer; performing three-dimensional seismic horizon interpretation, and determining the time of seismic waves reaching the top of a target layer and the time of seismic waves reaching the bottom of the target layer; determining a forward model of the thickness change of the thin reservoir according to the logging information, and determining the change condition of the seismic wave frequency of the target layer along with the thickness change of the thin reservoir; setting a time window according to the change condition of the seismic wave frequency of the target layer along with the thickness change of the thin reservoir layer, the time of the seismic wave reaching the top of the target layer and the time of the seismic wave reaching the bottom of the target layer, and extracting the frequency attribute of the target layer; determining a forward model of the thickness change of the stratum of the target layer according to the logging information, and determining the rule that the frequency of the seismic waves of the target layer changes along with the thickness change of the stratum of the target layer; determining the stratum thickness of a target layer according to the three-dimensional seismic horizon interpretation and well logging information; correcting the frequency attribute of the target layer according to the rule that the frequency of the seismic wave of the target layer changes along with the thickness of the stratum of the target layer and the thickness of the stratum of the target layer; and predicting the thickness of the thin reservoir according to the corrected frequency attribute of the target layer.
The embodiment of the present application further provides a device for predicting a thin reservoir thickness based on a frequency attribute, which is used for predicting the accuracy of the thin reservoir thickness based on the frequency attribute, and the device includes:
the acquisition module is used for acquiring seismic data and logging data in a work area, performing synthetic record calibration and determining the position of a target layer; the determining module is used for performing three-dimensional seismic horizon interpretation, and determining the time of seismic waves reaching the top of a target layer and the time of the seismic waves reaching the bottom of the target layer; the determining module is also used for determining a forward model of the thickness change of the thin reservoir according to the logging information acquired by the acquiring module and determining the change condition of the seismic wave frequency of the target layer along with the thickness change of the thin reservoir; the extraction module is used for setting a time window according to the change condition of the seismic wave frequency of the target layer, which is determined by the determination module, along with the thickness change of the thin reservoir layer, the time of the seismic wave reaching the top of the target layer and the time of the seismic wave reaching the bottom of the target layer, and extracting the frequency attribute of the target layer; the determining module is also used for determining a forward model of the thickness change of the stratum of the target layer according to the logging information acquired by the acquiring module and determining the rule that the seismic wave frequency of the target layer changes along with the thickness change of the stratum of the target layer; the determining module is further used for determining the stratum thickness of the target layer according to the three-dimensional seismic horizon interpretation and the logging data; the correction module is used for correcting the frequency attribute of the target layer extracted by the extraction module according to the rule that the frequency of the seismic wave of the target layer is changed along with the thickness of the stratum of the target layer and the thickness of the stratum of the target layer, which are determined by the determination module; and the prediction module is used for predicting the thickness of the thin reservoir according to the frequency attribute of the target layer corrected by the correction module.
In the embodiment of the application, the frequency attribute of the target layer, the stratum thickness of the target layer and the rule that the seismic wave frequency of the target layer changes along with the thickness of the stratum of the target layer are determined through seismic data and well logging data in a work area, and then the frequency attribute of the target layer is corrected by utilizing the rule that the stratum thickness of the target layer and the seismic wave frequency of the target layer change along with the thickness of the stratum of the target layer, so that the influence of the stratum thickness of the target layer on the frequency attribute of the target layer is eliminated, and the accuracy of the thickness of the thin reservoir predicted by the frequency attribute of the target layer is higher.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
FIG. 1 is a flow chart of a method for predicting thin reservoir thickness based on frequency attributes in an embodiment of the present application;
FIG. 2 is a schematic illustration of a synthetic record being best matched to a borehole seismic event in an embodiment of the present application;
FIG. 3 is a schematic diagram of a forward model of thin reservoir thickness variation provided by an embodiment of the present application;
FIG. 4 is a schematic illustration of a first seismic trace section provided by an embodiment of the present application;
FIG. 5 is a schematic diagram of a forward model of the thickness variation of a target stratum according to an embodiment of the present application;
FIG. 6 is a schematic illustration of a second seismic trace section provided by an embodiment of the present application;
FIG. 7 is a schematic diagram illustrating a fitted curve of the thickness of the formation of the target layer and the frequency of seismic waves according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of an apparatus for predicting a thin reservoir thickness based on a frequency attribute according to an embodiment of the present disclosure.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present application more apparent, the embodiments of the present application are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present application are provided herein to explain the present application and not to limit the present application.
The embodiment of the present application provides a method for predicting the thickness of a thin reservoir based on frequency attributes, as shown in fig. 1, the method includes steps 101 to 108:
Seismic data is typically a three-dimensional post-stack seismic data volume that is acquired at the surface and subsequently processed. In order to obtain seismic data, a seismic source capable of emitting seismic waves and a receiving device for reflected wave signals of the seismic waves can be arranged on the earth surface, when the seismic source is excited to generate the seismic waves, the seismic waves are transmitted to the deep part of an underground rock stratum and meet medium interfaces with different elasticity, and wave reflection can be generated; the reflected wave signal is received by a receiving device, and the characteristics of the reflected wave signal, such as time, frequency, amplitude and the like, are further analyzed to obtain the characteristic information of the underground rock stratum, and the characteristic information of the underground rock stratum can be used as seismic data.
The logging data comprises a sound wave time difference curve, a density curve, a gamma curve, a resistivity curve and the like, and is acquired from a deployed exploratory well in a work area.
In the embodiment of the application, the acoustic moveout curve and the density curve included in the seismic data and the logging data can be used for carrying out synthetic recording calibration so as to determine the position of the target layer. Specifically, firstly, determining a sound wave curve by using a sound wave time difference curve; then, multiplying the speed attribute on the sound wave curve corresponding to the same depth point by the density attribute on the density curve to obtain a wave impedance curve; then, extracting wavelets from the seismic data, and performing convolution operation on the wavelets and the wave impedance curve to obtain a synthetic record; and finally, optimally matching the well side earthquake and the synthetic record in the earthquake data according to the principle that the wave crest corresponds to the wave crest and the wave trough corresponds to the wave trough, and determining the time-depth relation and the position of the target layer.
The acoustic wave time difference curve is used for describing the reciprocal of the seismic wave velocity of different underground depth points, and the acoustic wave curve is used for describing the seismic wave velocity of different underground depth points, so that the acoustic wave curve can be obtained by taking the reciprocal of the numerical value on the acoustic wave time difference curve.
The density curve is used for describing the density of different depth points, the density on the density curve is multiplied by the speed of the same depth point on the sound wave curve to obtain the wave impedance value of the depth point, the depth point is taken as a vertical coordinate, the wave impedance value is taken as a horizontal coordinate, and the wave impedance values of the different depth points are mapped on a coordinate axis to obtain the wave impedance curve.
Wavelets are a component of the convolution model of seismic records, and generally refer to seismic impulses consisting of 2 to 3 or more phases, and extracting wavelets from seismic data is a well-established technical means, and for this process, it is not described herein again. In addition, convolution operation is also a mature technical means, and the operation process of convolution operation on wavelets and wave impedance curves is not repeated.
For example, referring to fig. 2, fig. 2 shows a more ideal matching result, the peak and the trough of the synthetic record and the earthquake beside the well are relatively matched, but due to the extremely complicated condition of the underground rock stratum, in many cases, the peak and the trough of the synthetic record and the earthquake beside the well cannot be completely corresponding, and at this time, as many peaks and troughs as possible can be respectively corresponding to achieve the best matching.
And 102, performing three-dimensional seismic horizon interpretation, and determining the time of seismic waves reaching the top of the target layer and the time of the seismic waves reaching the bottom of the target layer.
In the embodiment of the present application, the time of arrival of the seismic wave at the top of the destination layer is denoted as T1And the time of the seismic wave reaching the bottom of the destination layer is recorded as T2。
And 103, determining a forward model of the thickness change of the thin reservoir according to the logging data, and determining the change condition of the seismic wave frequency of the target layer along with the thickness change of the thin reservoir.
Because the logging information includes the characteristics of the stratum at the position of the deployed exploratory well, such as the thickness of various stratums, the thickness range of the thin reservoir in the work area can be determined according to the logging information: then according to the thickness range of the thin reservoir, determining a forward model of the thickness change of the thin reservoir, and determining the change condition of the seismic wave frequency of the target layer along with the thickness change of the thin reservoir, wherein the method comprises the following steps: determining the thickness range of a thin reservoir in a work area according to logging information, establishing a forward model of the thickness change of the thin reservoir, extracting wavelets from seismic data, and performing convolution operation on the wavelets and the forward model of the thickness change of the thin reservoir to generate a first seismic channel section; and determining the change condition of the seismic wave frequency of the target layer along with the change of the thickness of the thin reservoir according to the first seismic channel section.
In the forward model of the thickness variation of the thin reservoir, the thickness of the thin reservoir gradually varies, and the thicknesses of other rock strata do not vary.
Illustratively, according to the logging information, the whole target layer is determined to be high-impedance dense dolomite, and a medium-low-impedance pore dolomite reservoir layer develops at the top of the target layer. Based on the formation characteristics described above, a forward model of thin reservoir thickness variation can be constructed as shown in FIG. 3.
For example, the generated first seismic trace profile is shown in fig. 4, and it is obvious from the seismic profile that when the thickness of the thin reservoir is 0 m, the frequency of the seismic wave of the destination layer is higher, and as the thickness of the thin reservoir increases, the frequency of the seismic wave of the destination layer gradually decreases, so that the value of the frequency value of the seismic wave of the destination layer can reflect the change of the thickness of the thin reservoir.
And 104, setting a time window according to the change condition of the seismic wave frequency of the target layer along with the thickness change of the thin reservoir layer, the time of the seismic wave reaching the top of the target layer and the time of the seismic wave reaching the bottom of the target layer, and extracting the frequency attribute of the target layer.
In the embodiment of the present application, the destination layer frequency attribute is extracted within a set time window, which may be set to [ T [ ]1，T2Or may be set to [ T ]1-t，T1+ T ] or may be [ T ]2-t，T2+ T ], wherein T1Is the time, T, of arrival of the seismic waves at the top of the destination layer determined in step 1022Is the time at which the seismic waves determined in step 102 reach the bottom of the destination layer. In setting the time window, T can be selected and utilized with reference to the forward model of the thin reservoir thickness variation obtained in step 1031Or T2To set the time window, t may be set in conjunction with the actual formation characteristics. Illustratively, in the embodiment of the present application, the time window is set to [ T ]1，T2】。
And 105, determining a forward model of the thickness change of the stratum of the target layer according to the logging data, and determining the rule of the frequency of the seismic waves of the target layer along with the thickness change of the stratum of the target layer.
In the embodiment of the application, the stratum thickness range of a target layer in a work area can be determined according to logging information, and a forward model of the stratum thickness change of the target layer is established; then, extracting wavelets from the seismic data, and performing convolution operation on the wavelets and the forward modeling of the stratum thickness change of the target layer to generate a second seismic channel section; and determining the rule that the frequency of the seismic waves of the target layer changes along with the thickness of the stratum of the target layer according to the second seismic channel section.
In the forward model of the change in the thickness of the target stratum, the thickness of the target stratum gradually changes, and the thicknesses of other rock layers do not change.
Illustratively, according to the logging information, the thickness variation range of the target layer is determined to be between 80 meters and 100 meters, and based on the thickness variation range of the target layer, a forward model of the thickness variation of the target layer with the stratum thickness being between 80 meters and 100 meters and the thickness variation of other strata being constant is established, and the forward model of the thickness variation of the target layer is shown in fig. 5.
For example, the generated second seismic trace profile is shown in fig. 6, and it is obvious from this seismic trace profile that the seismic wave frequency of the destination layer gradually decreases as the thickness of the stratum layer of the destination layer gradually decreases, and it can be seen that the change of the thickness of the stratum layer of the destination layer causes the change of the seismic wave frequency of the destination layer.
In the embodiment of the application, determining the rule that the frequency of the seismic wave of the target stratum changes along with the thickness of the stratum of the target stratum according to the second seismic channel section comprises the following steps: acquiring stratum thicknesses of at least two target layers and corresponding seismic wave frequency values from the second seismic channel section; the stratum thicknesses of at least two target layers obtained from the second seismic channel section and the corresponding seismic wave frequency values are mapped to coordinate axes as basic points by taking the stratum thickness of the target layers as an abscissa and the seismic wave frequency values as an ordinate; and fitting by using the basic points, determining a fitting curve of the stratum thickness of the target layer and the seismic wave frequency and an expression of the fitting curve, and taking the expression of the fitting curve as a rule that the seismic wave frequency of the target layer changes along with the stratum thickness of the target layer.
Illustratively, the thickness of the stratum of the target layer is used as an abscissa, the frequency value of the seismic waves of the target layer is used as an ordinate, the obtained plurality of basic points are mapped onto coordinate axes to obtain 'actual data' shown in fig. 7, a 'fitting curve' shown in fig. 7 is determined according to the actual data, as can be seen from the figure, the difference between the fitting curve and the actual data is small, and the accuracy of the fitting curve is high. Obviously, in this example, the fitted curve resembles a parabola, and thus, F (H) ═ aH is the mathematical form of the parabola2+ bH + c represents the fitted curve, where H is the formation thickness of the formation of the layer of interest,f (H) is the frequency value of the seismic waves of the destination layer, and a, b and c are coefficients. After determining the mathematical form of the fitted curve, the coefficients a, b, and c in the above mathematical form may be calculated using actual data, illustratively, a is-0.026, b is 0.436, and c is 64.82, resulting in the expression F (H) is-0.026H2+0.436H+64.82。
It should be noted that the established forward model of the thickness variation of the thin reservoir and the forward model of the thickness variation of the stratum of the target layer need to conform to geological rules, otherwise, the forward models cannot be applied to practice.
And step 106, determining the stratum thickness of the target layer according to the three-dimensional seismic horizon interpretation and the logging information.
Specifically, three-dimensional seismic horizon interpretation can be carried out, and the time of seismic waves reaching the top surface and the time of seismic waves reaching the bottom surface of a target layer are picked up; determining the difference value of the time of the seismic waves reaching the bottom surface and the time of the top surface of the target layer as the time thickness of the target layer; determining the propagation speed of seismic waves in a target layer according to the logging information; according to the formula
And calculating the stratum thickness H of the target layer. Wherein V is used for representing the propagation velocity of the seismic waves in the target layer, and N is used for representing the time thickness of the target layer.
And step 107, correcting the frequency attribute of the target layer according to the rule that the frequency of the seismic wave of the target layer changes along with the thickness of the stratum of the target layer and the thickness of the stratum of the target layer.
In particular, it can be according to formula Fr(i,j)＝Ft(i,j)-F(H(i,j)) + C corrects the destination layer frequency property, where Fr(i,j)A correction result for the jth trace frequency attribute of the ith line representing a desired output; ft(i,j)Used for representing the jth track frequency attribute of the ith line; f (H)(i,j)) And C is a constant, and the values of i and j are positive integers.
And step 108, predicting the thickness of the thin reservoir according to the corrected frequency attribute of the target layer.
It should be noted that, predicting the thickness of the thin reservoir according to the frequency attribute of the target layer is a mature method, and details of the specific process are not described herein again.
In the embodiment of the application, the frequency attribute of the target layer, the stratum thickness of the target layer and the rule that the seismic wave frequency of the target layer changes along with the thickness of the stratum of the target layer are determined through seismic data and well logging data in a work area, and then the frequency attribute of the target layer is corrected by utilizing the rule that the stratum thickness of the target layer and the seismic wave frequency of the target layer change along with the thickness of the stratum of the target layer, so that the influence of the stratum thickness of the target layer on the frequency attribute of the target layer is eliminated, and the accuracy of the thickness of the thin reservoir predicted by the frequency attribute of the target layer is higher.
The embodiment of the present application provides an apparatus for predicting a thin reservoir thickness based on a frequency attribute, as shown in fig. 8, the apparatus 800 includes an obtaining module 801, a determining module 802, an extracting module 803, a correcting module 804, and a predicting module 805.
The obtaining module 801 is configured to obtain seismic data and logging data in a work area, perform synthetic record calibration, and determine a position of a target layer.
The determining module 802 is configured to perform three-dimensional seismic horizon interpretation, and determine the time when the seismic waves reach the top of the destination layer and the time when the seismic waves reach the bottom of the destination layer.
The determining module 802 is further configured to determine a forward model of the thickness variation of the thin reservoir according to the logging information acquired by the acquiring module 801, and determine a variation situation of the seismic wave frequency of the target layer along with the thickness variation of the thin reservoir.
The extracting module 803 is configured to set a time window according to the change condition of the target layer seismic wave frequency determined by the determining module 802, the time when the seismic wave reaches the top of the target layer, and the time when the seismic wave reaches the bottom of the target layer, and extract a target layer frequency attribute.
The determining module 802 is further configured to determine a forward model of the change of the thickness of the stratum of the target layer according to the logging information acquired by the acquiring module 801, and determine a rule that the frequency of the seismic wave of the target layer changes along with the thickness of the stratum of the target layer.
The determining module 802 is further configured to determine the thickness of the stratum of the target layer according to the three-dimensional seismic horizon interpretation and the logging data.
And the correcting module 804 is configured to correct the frequency attribute of the target layer extracted by the extracting module 803 according to the rule that the frequency of the target layer seismic wave determined by the determining module 802 changes with the thickness of the target layer and the thickness of the target layer.
And the prediction module 805 is used for predicting the thickness of the thin reservoir according to the target layer frequency attribute corrected by the correction module 804.
In an implementation manner of the embodiment of the present application, the correction module 804 is configured to:
according to formula Fr(i,j)＝Ft(i,j)-F(H(i,j)) + C corrects the destination layer frequency property, where Fr(i,j)A correction result for the jth trace frequency attribute of the ith line representing a desired output; ft(i,j)Used for representing the jth track frequency attribute of the ith line; f (H)(i,j)) And C is a constant, and the values of i and j are positive integers.
In one implementation of an embodiment of the present application, the well log data includes sonic moveout curves and density curves.
A determining module 802 for:
determining a sound wave curve by using the sound wave time difference curve;
multiplying the speed attribute on the acoustic curve corresponding to the same depth point with the density attribute on the density curve to obtain a wave impedance curve;
extracting wavelets from the seismic data, and performing convolution operation on the wavelets and the wave impedance curve to obtain a synthetic record;
and optimally matching the well side earthquake and the synthetic record in the earthquake data, and determining the time-depth relation and the position of the target layer.
In an implementation manner of the embodiment of the present application, the determining module 802 is configured to:
determining the thickness range of a thin reservoir in a work area according to logging information, and establishing a forward model of the thickness change of the thin reservoir, wherein in the forward model of the thickness change of the thin reservoir, the thickness of the thin reservoir gradually changes, and the thicknesses of other rock stratums do not change;
extracting wavelets from the seismic data, and performing convolution operation on the wavelets and a forward model of the thin reservoir thickness change to generate a first seismic channel section;
and determining the change condition of the seismic wave frequency of the target layer along with the change of the thickness of the thin reservoir according to the first seismic channel section.
In an implementation manner of the embodiment of the present application, the determining module 802 is configured to:
determining the stratum thickness range of a target layer in a work area according to logging information, and establishing a forward model of the stratum thickness change of the target layer, wherein in the forward model of the stratum thickness change of the target layer, the stratum thickness of the target layer gradually changes, and the thicknesses of other rock layers do not change;
extracting wavelets from the seismic data, and performing convolution operation on the wavelets and the forward modeling of the stratum thickness change of the target layer to generate a second seismic channel section;
and determining the rule that the frequency of the seismic waves of the target layer changes along with the thickness of the stratum of the target layer according to the second seismic channel section.
In an implementation manner of the embodiment of the present application, the determining module 802 is configured to:
acquiring stratum thicknesses of at least two target layers and corresponding seismic wave frequency values from the second seismic channel section;
the stratum thicknesses of at least two target layers obtained from the second seismic channel section and the corresponding seismic wave frequency values are mapped to coordinate axes as basic points by taking the stratum thickness of the target layers as an abscissa and the seismic wave frequency values as an ordinate;
and fitting by using the basic points, determining a fitting curve of the stratum thickness of the target layer and the seismic wave frequency and an expression of the fitting curve, and taking the expression of the fitting curve as a rule that the seismic wave frequency of the target layer changes along with the stratum thickness of the target layer.
In an implementation manner of the embodiment of the present application, the determining module 802 is configured to:
performing three-dimensional seismic horizon interpretation, and picking up the time of seismic waves reaching the top surface and the time of seismic waves reaching the bottom surface of a target layer;
determining the difference value of the time of the seismic waves reaching the bottom surface and the time of the top surface of the target layer as the time thickness of the target layer;
determining the propagation speed of seismic waves in a target layer according to the logging information;
according to the formula
And calculating the stratum thickness H of the destination layer, wherein V is used for representing the propagation speed of the seismic waves in the destination layer, and N is used for representing the time thickness of the destination layer.
In the embodiment of the application, the frequency attribute of the target layer, the stratum thickness of the target layer and the rule that the seismic wave frequency of the target layer changes along with the thickness of the stratum of the target layer are determined through seismic data and well logging data in a work area, and then the frequency attribute of the target layer is corrected by utilizing the rule that the stratum thickness of the target layer and the seismic wave frequency of the target layer change along with the thickness of the stratum of the target layer, so that the influence of the stratum thickness of the target layer on the frequency attribute of the target layer is eliminated, and the accuracy of the thickness of the thin reservoir predicted by the frequency attribute of the target layer is higher.
The embodiment of the present application further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method described in step 101 to step 108 when executing the computer program.
An embodiment of the present application further provides a computer-readable storage medium, where a computer program for executing the method described in step 101 to step 108 is stored in the computer-readable storage medium.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are further described in detail for the purpose of illustrating the invention, and it should be understood that the above-mentioned embodiments are only illustrative of the present invention and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method for predicting thin reservoir thickness based on frequency attributes, the method comprising:
acquiring seismic data and logging data in a work area, performing synthetic record calibration, and determining the position of a target layer;
performing three-dimensional seismic horizon interpretation, and determining the time of seismic waves reaching the top of a target layer and the time of seismic waves reaching the bottom of the target layer;
determining a forward model of the thickness change of the thin reservoir according to the logging information, and determining the change condition of the seismic wave frequency of the target layer along with the thickness change of the thin reservoir;
setting a time window according to the change condition of the seismic wave frequency of the target layer along with the thickness change of the thin reservoir layer, the time of the seismic wave reaching the top of the target layer and the time of the seismic wave reaching the bottom of the target layer, and extracting the frequency attribute of the target layer;
determining a forward model of the thickness change of the stratum of the target layer according to the logging information, and determining the rule that the frequency of the seismic waves of the target layer changes along with the thickness change of the stratum of the target layer;
determining the stratum thickness of a target layer according to the three-dimensional seismic horizon interpretation and well logging information;
correcting the frequency attribute of the target layer according to the rule that the frequency of the seismic wave of the target layer changes along with the thickness of the stratum of the target layer and the thickness of the stratum of the target layer;
and predicting the thickness of the thin reservoir according to the corrected frequency attribute of the target layer.
2. The method of claim 1, wherein the correcting the frequency attribute of the target layer according to the rule that the frequency of the seismic wave of the target layer changes along with the thickness of the stratum of the target layer and the thickness of the stratum of the target layer comprises:
according to formula Fr(i,j)＝Ft(i,j)-F(H(i,j)) + C corrects the destination layer frequency property, where Fr(i,j)A correction result for the jth trace frequency attribute of the ith line representing a desired output; ft(i,j)For representingThe ith line and the jth track frequency attribute; f (H)(i,j)) And C is a constant, and the values of i and j are positive integers.
3. The method of claim 1, wherein the well log data comprises sonic moveout curves and density curves;
the performing synthetic record calibration and determining the position of the target layer includes:
determining a sound wave curve by using the sound wave time difference curve;
multiplying the speed attribute on the acoustic curve corresponding to the same depth point with the density attribute on the density curve to obtain a wave impedance curve;
extracting wavelets from the seismic data, and performing convolution operation on the wavelets and the wave impedance curve to obtain a synthetic record;
and optimally matching the well side earthquake and the synthetic record in the earthquake data, and determining the time-depth relation and the position of the target layer.
4. The method of claim 1, wherein the determining a forward model of the change of the thin reservoir thickness according to the well log data and the change of the seismic wave frequency of the target stratum along with the change of the thin reservoir thickness comprise:
determining the thickness range of a thin reservoir in a work area according to logging information, and establishing a forward model of the thickness change of the thin reservoir, wherein in the forward model of the thickness change of the thin reservoir, the thickness of the thin reservoir gradually changes, and the thicknesses of other rock stratums do not change;
extracting wavelets from the seismic data, and performing convolution operation on the wavelets and a forward model of the thin reservoir thickness change to generate a first seismic channel section;
and determining the change condition of the seismic wave frequency of the target layer along with the change of the thickness of the thin reservoir according to the first seismic channel section.
5. The method of claim 1, wherein determining a forward model of the change in the thickness of the formation of the target layer from the well log data, determining the regularity of the change in the frequency of the seismic waves of the target layer with the thickness of the formation of the target layer, comprises:
determining the stratum thickness range of a target layer in a work area according to logging information, and establishing a forward model of the stratum thickness change of the target layer, wherein in the forward model of the stratum thickness change of the target layer, the stratum thickness of the target layer gradually changes, and the thicknesses of other rock stratums are unchanged;
extracting wavelets from the seismic data, and performing convolution operation on the wavelets and the forward modeling of the stratum thickness change of the target layer to generate a second seismic channel section;
and determining the rule that the frequency of the seismic waves of the target layer changes along with the thickness of the stratum of the target layer according to the second seismic channel section.
6. The method of claim 5, wherein determining the frequency of the seismic waves of the target interval as a function of the thickness of the formation of the target interval from the second seismic trace section comprises:
acquiring stratum thicknesses of at least two target layers and corresponding seismic wave frequency values from the second seismic channel section;
the stratum thicknesses of at least two target layers obtained from the second seismic channel section and the corresponding seismic wave frequency values are mapped to coordinate axes as basic points by taking the stratum thickness of the target layers as an abscissa and the seismic wave frequency values as an ordinate;
and fitting by using the basic points, determining a fitting curve of the stratum thickness of the target layer and the seismic wave frequency and an expression of the fitting curve, and taking the expression of the fitting curve as a rule that the seismic wave frequency of the target layer changes along with the stratum thickness of the target layer.
7. The method of claim 1, wherein determining the formation thickness of the target interval from the three-dimensional seismic horizon interpretation and log data comprises:
performing three-dimensional seismic horizon interpretation, and picking up the time of seismic waves reaching the top surface and the time of seismic waves reaching the bottom surface of a target layer;
determining the difference value of the time of the seismic waves reaching the bottom surface and the time of the top surface of the target layer as the time thickness of the target layer;
determining the propagation speed of seismic waves in a target layer according to the logging information;
according to the formula
And calculating the stratum thickness H of the destination layer, wherein V is used for representing the propagation speed of the seismic waves in the destination layer, and N is used for representing the time thickness of the destination layer.
8. An apparatus for predicting thin reservoir thickness based on frequency attributes, the apparatus comprising:
the acquisition module is used for acquiring seismic data and logging data in a work area, performing synthetic record calibration and determining the position of a target layer;
the determining module is used for performing three-dimensional seismic horizon interpretation, and determining the time of seismic waves reaching the top of a target layer and the time of the seismic waves reaching the bottom of the target layer;
the determining module is also used for determining a forward model of the thickness change of the thin reservoir according to the logging information acquired by the acquiring module and determining the change condition of the seismic wave frequency of the target layer along with the thickness change of the thin reservoir;
the extraction module is used for setting a time window according to the change condition of the seismic wave frequency of the target layer, which is determined by the determination module, along with the thickness change of the thin reservoir layer, the time of the seismic wave reaching the top of the target layer and the time of the seismic wave reaching the bottom of the target layer, and extracting the frequency attribute of the target layer;
the determining module is also used for determining a forward model of the thickness change of the stratum of the target layer according to the logging information acquired by the acquiring module and determining the rule that the seismic wave frequency of the target layer changes along with the thickness change of the stratum of the target layer;
the determining module is further used for determining the stratum thickness of the target layer according to the three-dimensional seismic horizon interpretation and the logging data;
the correction module is used for correcting the frequency attribute of the target layer extracted by the extraction module according to the rule that the frequency of the seismic wave of the target layer is changed along with the thickness of the stratum of the target layer and the thickness of the stratum of the target layer, which are determined by the determination module;
and the prediction module is used for predicting the thickness of the thin reservoir according to the frequency attribute of the target layer corrected by the correction module.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 7.
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