Method and system for depicting internal configuration of carbonate fractured-vuggy reservoir

Abstract

The invention provides a carbonate rock fracture-vug reservoir internal configuration depiction method and system, and the method comprises the specific steps: obtaining seismic data, separating a fracture-vug reservoir from an undisturbed stratum through a median filtering algorithm, and achieving the outline depiction of the fracture-vug reservoir; obtaining seismic data, obtaining a fault enhanced image body by using a fault identification technology, and realizing depiction of a fracture-cavity reservoir separation barrier; seismic data are obtained, continuous characteristics of stratums in the fractured-vuggy reservoir bodies are obtained through the phase continuous scanning technology, and depiction of dense stratums and fractured stratums is achieved; acquiring seismic data, and depicting an internal corrosion zone of the fracture-cavity reservoir body by using instantaneous attenuation attributes of seismic waves; and the fracture-cavity reservoir body, the separation barrier, the compact stratum, the broken stratum and the corrosion zone are overlapped, and fine description of the internal configuration of the fracture-cavity reservoir body is achieved. According to the method, various factors such as a compact stratum, a fractured stratum and a corrosion zone are comprehensively considered, so that the internal configuration of the fracture-cavity reservoir body is described more accurately.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas exploration geophysics, and in particular to a method and system for characterizing the internal configuration of a carbonate fracture-vuggy reservoir. Background Art

[0002] Fault-controlled fracture-vuggy reservoirs are important oil and gas reservoirs in carbonate rocks. Because their formation is influenced by a combination of factors, including fault intensity, lithology and lithofacies, and surface and groundwater dissolution, fracture-vuggy reservoirs exhibit complex internal structures, including diverse stratigraphic features such as barriers, tight formations, fractured formations, and dissolution zones. Detailed characterization of the internal structure of fracture-vuggy reservoirs is crucial for revealing the distribution of reservoir space, predicting fluid migration patterns, and identifying effective development strategies.

[0003] Researchers have made considerable progress in studying the internal architecture of carbonate reservoirs. Common research methods include field geological observations, core section analysis, microscopic observation techniques such as scanning electron microscopy, and imaging logging. However, these techniques are based on single-point data and are unable to accurately characterize the internal architecture at the macroscale. The most commonly used macroscale methods are 3D seismic attributes and geological modeling. However, current techniques utilize 3D seismic attributes primarily to characterize the external contours of fracture-vuggy reservoirs, making it difficult to effectively characterize the internal architecture. While geological modeling can establish a 3D spatial distribution model of the internal architecture, it primarily relies on stochastic simulations, resulting in significant ambiguity and uncertainty, making it difficult to effectively guide well placement and development plans. Consequently, there is currently a lack of high-precision methods for characterizing the internal architecture of fracture-vuggy reservoirs. Summary of the Invention

[0004] In order to solve the problems existing in the prior art, the present invention provides a method and system for characterizing the internal configuration of carbonate fracture-vuggy reservoirs, which comprehensively considers multiple factors such as dense strata, fractured strata and dissolution zones, and provides comprehensive and accurate information on the internal configuration of fracture-vuggy reservoirs, thereby more accurately describing the internal configuration of fracture-vuggy reservoirs.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for characterizing the internal structure of a carbonate fracture-vuggy reservoir, comprising the following specific steps:

[0006] Seismic data is obtained and the median filter algorithm is used to separate the fracture-cavity reservoir from the original stratum to achieve the contour characterization of the fracture-cavity reservoir;

[0007] Acquire seismic data and use fault identification technology to obtain fault-enhanced images to characterize the barriers separating fracture-cavity reservoirs;

[0008] Acquire seismic data and use phase continuity scanning technology to obtain the continuous characteristics of the internal strata of fracture-cavity reservoirs, and achieve the characterization of dense and broken strata;

[0009] Obtain seismic data and use the instantaneous attenuation properties of seismic waves to characterize the internal dissolution zones of fracture-cavity reservoirs;

[0010] The fracture-cavity reservoirs, separation barriers, tight formations, fractured formations and dissolution zones are superimposed to achieve a detailed depiction of the internal configuration of the fracture-cavity reservoirs.

[0011] Furthermore, the median filter algorithm is used to filter and process the seismic data, separating the energy of the fracture-cavity reservoir from the energy of the surrounding strata, and filling the interior of the obtained fracture-cavity reservoir with a uniform value to achieve a fine depiction of the fracture-cavity reservoir's external contour.

[0012] Furthermore, the anisotropic diffusion filtering method is used to perform dip-guided filtering on the seismic data, and then the fault enhancement image volume is estimated using the maximum likelihood attribute.

[0013] Furthermore, the anisotropic diffusion filtering method is as follows:

[0014]

[0015] Where g is the seismic data, and t is the number of iterations. The six divergence formulas are to find the partial derivatives of the current seismic data in six directions, as shown in (3)-(8):

[0016]

[0017]

[0018]

[0019]

[0020]

[0021]

[0022] cE, cW, cN, cS, cD, and cU represent the thermal conductivity coefficients in six directions, as shown in formulas (9)-(14):

[0023]

[0024]

[0025]

[0026]

[0027]

[0028]

[0029] Where t is the number of iterations; k is the thermal conductivity of the material; and λ is the adjustment amplitude factor.

[0030] Furthermore, the maximum likelihood attribute is used to estimate the tomographic enhancement image volume, as follows:

[0031] First, set the azimuth scanning space and scanning interval of the tomographic plane;

[0032] Secondly, establish the local attribute smoothing function F along the fault plane smth (inData,ω), using the seismic dip-oriented coherence formula to perform fault plane orientation smoothing calculations and obtain the maximum fault likelihood attribute volume;

[0033] Finally, the strip-like data in the maximum fault likelihood attribute volume are thinned to obtain the fault enhancement image volume, which is the separation barrier between different fracture-cavity reservoirs.

[0034] Furthermore, the azimuth scanning space of the fault plane is specifically:

[0035] Φ={φ i |φ min ≤φ i ≤φ max , i=1, 2, 3, ..., n φ -1, n φ} (16)

[0036] Among them, φ min 、φ max 、n φ are the minimum azimuth, maximum azimuth, and average score, respectively. is the scanning interval.

[0037] Furthermore, the local attribute smoothing function F along the fault plane smth In (inData,ω), inData is the data of the target data point in the attribute volume to be smoothed, and ω∈W is the local occurrence of the fault plane where inData is located;

[0038] The relevant smoothing calculation formula of fault plane orientation is obtained by using the seismic dip angle orientation coherence formula as shown in (21):

[0039]

[0040] Specifically, the seismic dip steering coherence formulas are as follows (17)-(20):

[0041]

[0042] g ～ [i x ,i y ,i t ,j x ,j y ]=g[i x ,i y ,i t ,p x [i x ,i y ,i t ]j x ,p y [i x ,i y ,i t ]j y ] (18)

[0043]

[0044]

[0045] Among them, g is earthquake data, p x 、p y are the x- and y-direction components of the seismic reflection interface inclination attribute, M x , M y are the window radii of coherence in the x and y directions respectively. When the seismic reflection interface is isotropic, M x =M y ,j x 、j y are the window offsets in the x and y directions, respectively, and the local seismic reflection interface inclination attribute volume p is calculated using the structural tensor;

[0046] The formula for calculating the fault likelihood attribute body is as follows (22):

[0047] l(i x ,i y ,i t ,ω)=1-(s smth [i x ,i y ,i t ,ω]) 8 (twenty two)

[0048] To find the maximum fault likelihood attribute body, the formula is as follows (23)-(24):

[0049] l max (i x ,i y,i t )=max{l(i x ,i y ,i t ,ω)},ω∈W (23)

[0050] L max ={l max (i x ,i y ,i t )} (twenty four).

[0051] Furthermore, the instantaneous attenuation quality factor is calculated using the original seismic data without gain processing to characterize the internal dissolution zone of the fracture-cavity body, as follows:

[0052] Among them, Q i is the instantaneous attenuation quality factor, f is the instantaneous frequency, A is the amplitude envelope, and dA / dx is the derivative of the amplitude envelope.

[0053] The present invention also provides a system for characterizing the internal structure of a carbonate fracture-vuggy reservoir, comprising:

[0054] The contour characterization module is used to obtain seismic data and use the median filter algorithm to separate the fracture-cavity reservoir from the original stratum to achieve the contour characterization of the fracture-cavity reservoir;

[0055] Separation barrier characterization module, which is used to obtain seismic data and use fault identification technology to obtain fault enhancement images to achieve the characterization of separation barriers of fracture-cavity reservoirs;

[0056] The dense and fractured formation characterization module is used to obtain seismic data and use phase continuity scanning technology to obtain the continuous characteristics of the internal formations of fracture-cavity reservoirs to achieve the characterization of dense and fractured formations;

[0057] The dissolution zone characterization module is used to obtain seismic data and use the instantaneous attenuation properties of seismic waves to characterize the dissolution zones inside fracture-cavity reservoirs;

[0058] The superposition module is used to superimpose fracture-cavity reservoirs, separation barriers, tight formations, fractured formations, and dissolution zones to achieve a detailed depiction of the internal configuration of fracture-cavity reservoirs.

[0059] The present invention also provides a terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned method for characterizing the internal configuration of a carbonate fracture-vuggy reservoir or the functions of each module in the above-mentioned system are implemented.

[0060] Compared with the prior art, the present invention has at least the following beneficial effects:

[0061] The traditional method for characterizing the internal configuration of fracture-cavity reservoirs is based on establishing geological models through random simulation. The results have large multi-solutions and uncertainties, and cannot accurately characterize the detailed characteristics of fracture-cavity reservoirs. The present invention provides a method for characterizing the internal configuration of carbonate fracture-cavity reservoirs, which uses a median filtering algorithm to predict the external contours of fracture-cavity reservoirs. The median filtering algorithm can be used to smooth seismic data, reduce the impact of noise, and improve the quality and accuracy of data. Through median filtering, the external contours of fracture-cavity reservoirs can be better extracted; secondly, the separation barrier is characterized by fault identification technology, which not only enhances the fault signal in the seismic data to make it more prominent, but also performs statistical and probability analysis. The separation barrier is finely characterized by fault identification technology, and the characterization of different connected units of the fracture-cavity reservoir is achieved; then, the dense formation is characterized by phase continuity scanning technology. Phase continuity scanning technology is a seismic data processing method based on phase information, which can extract phase information in the formation, and can To reveal the tight strata inside the fracture-cavity reservoir, which are invalid reservoirs inside the fracture-cavity reservoir; again, the instantaneous attenuation attribute is used to characterize the space of the dissolution zone inside the fault reservoir. The instantaneous attenuation attribute is an attribute used to describe the attenuation degree of seismic signals, which can be used to judge the degree of formation fragmentation and the distribution of dissolution zones; finally, the fracture-cavity reservoir, separation barrier, tight strata, broken strata, and dissolution zones are superimposed to achieve the purpose of gradually characterizing the internal configuration of the fracture-cavity reservoir, improve the accuracy and completeness of the detailed characteristics of the internal configuration of the fracture-cavity reservoir, and be able to more comprehensively and accurately characterize the internal configuration of the fracture-cavity reservoir, increase the certainty of the prediction results, overcome the defects of multi-solution and uncertainty of geological modeling results, and improve the accuracy and certainty of the internal configuration of the fracture-cavity reservoir. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a conventional seismic section.

[0063] Figure 2 This is the seismic profile of the fracture-cavity reservoir after stripping.

[0064] Figure 3 This is a fracture-cavity reservoir profile.

[0065] Figure 4 It is a superimposed section separating barrier fracture-cavity reservoirs.

[0066] Figure 5 It is the phase profile obtained by phase continuity scanning technology.

[0067] Figure 6 a is the superposition diagram of the phase section and the fracture-cavity reservoir section, Figure 6 b is the superposition of the phase section and the fracture-cavity reservoir section (partial enlargement).

[0068] Figure 7a is the effect of superposition of instantaneous quality factor and fracture-cavity reservoir, separation barrier, tight formation and broken formation. Figure 7 b is the effect of superposition of instantaneous quality factor and fracture-cavity reservoir, separation barrier, tight formation and broken formation (partial magnification).

[0069] Figure 8 This is the flow chart of this technology. DETAILED DESCRIPTION

[0070] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0071] like Figure 8 As shown, the present invention provides a method for characterizing the internal structure of carbonate fracture-vuggy reservoirs, and the specific implementation steps are as follows:

[0072] Step 1: Use the median filter algorithm to separate the fracture-cavity reservoir from the original stratum and depict the outline of the fracture-cavity reservoir;

[0073] Step 2: Use fault identification technology to finely characterize the separation barriers of fracture-cavity reservoirs;

[0074] Step 3: Use phase continuity scanning technology to identify tight and broken formations inside the fracture-cavity reservoir;

[0075] Step 4: Use the instantaneous attenuation attribute to characterize the internal dissolution zone of the fracture-cavity reservoir;

[0076] Step 5: Superimpose the fracture-cavity reservoir, separation barrier, tight stratum, fractured stratum, and dissolution zone to precisely depict the internal structure of the fracture-cavity reservoir.

[0077] In order to further illustrate the purpose and advantages of the present invention, a detailed description is given in conjunction with the accompanying drawings and technical flow charts.

[0078] Step 1: Use the median filter algorithm to separate the fracture-cavity reservoir from the original stratum and depict the outline of the fracture-cavity reservoir;

[0079] Fracture-cavity reservoirs are a special type of geological body developed in carbonate formations. They are usually characterized by strong amplitude in formations where mudstone and carbonate rocks are developed. On conventional seismic sections, for example, Figure 1 The signal of the fracture-vuggy reservoir in the T74 layer shown in the figure is submerged in the strong amplitude signal and cannot be identified, which greatly limits the detailed characterization of the fracture-vuggy reservoir.

[0080] The median filter algorithm is a commonly used seismic processing method used to suppress noise in seismic data or highlight abnormal signals in seismic data. It is based on the principle of median statistics. Based on the energy difference in seismic data, the algorithm separates the energy of fracture-cavity reservoirs from the energy of surrounding formations by filtering and processing seismic data. The specific implementation process is shown in formula (1):

[0081] f i,j,t =g i,j,t -Med(g i,j,t ,w i ,w j ) (1)

[0082] Where i, j, and t are the indices of the three-dimensional data line, channel, and time direction, respectively. i,j,t is the separated crack and hole data, g i,j,t is the earthquake data, Med() is the median filter method, w i ,w j are the window lengths in the line and track directions, respectively. In an isotropic environment, w i =w j .

[0083] like Figure 1 The figure shows a conventional seismic profile. Below T74, the overall energy is weak, and the fault reservoir can be identified (as shown by the arrow in the figure). However, at the T74 layer, due to the strong amplitude, the fracture-cavity reservoir cannot be identified. Figure 2 On the seismic profile of the fracture-cavity reservoir after the stripping, the distribution range of the fault reservoir can be clearly identified, especially the fault reservoir at T74 which is submerged by the strong amplitude can also be clearly shown (as shown in the circle in the figure). Figure 2 The seismic profile of the fracture-cavity reservoir is further processed to fill the interior of the fracture-cavity reservoir with a uniform value, thus achieving a fine depiction of the fracture-cavity reservoir's outline ( Figure 3 ).

[0084] Step 2: Use fault identification technology to finely characterize the separation barriers of fracture-cavity reservoirs;

[0085] The carbonate fracture-cavity reservoir separation barrier refers to a dense isolation layer or isolation zone formed by fracture-cavity bodies (such as cracks, caves, etc.) in carbonate reservoirs. It has a certain reservoir separation function and can limit the vertical or horizontal migration of fluids, thereby affecting the effectiveness and development effect of the reservoir. In the process of fracture-cavity reservoir formation, fracture-cavity bodies are continuously dissolved vertically along the fault, and vertical separation barriers often develop between different fracture-cavity bodies. The vertically developed fracture-cavity bodies and separation barriers show great differences, so they will form fault-like features in seismic observations. Therefore, fault identification technology can be used to finely identify separation barriers. It can be divided into two steps:

[0086] 1. Anisotropic diffusion filtering is used to perform dip-guided filtering on seismic signals, which not only removes noise but also protects fault signals.

[0087] Anisotropic diffusion filtering is a commonly used image processing method that can perform dip-guided filtering on seismic signals, removing noise while protecting fault signals. This method is based on the gradient information between pixels in the image. By smoothing areas with smaller gradients and protecting areas with larger gradients, it achieves the purpose of denoising and protecting fault signals. The specific implementation is as shown in formula (2):

[0088]

[0089] Where g is the earthquake data and t is the number of iterations.

[0090] The six divergence formulas are to find the partial derivatives of the current seismic data in six directions, as shown in (3)-(8):

[0091]

[0092]

[0093]

[0094]

[0095]

[0096]

[0097] cE, cW, cN, cS, cD, and cU represent the thermal conductivity coefficients in six directions, as shown in formulas (9)-(14):

[0098]

[0099]

[0100]

[0101]

[0102]

[0103]

[0104] Where t is the number of iterations, which is set according to the situation; k is the thermal conductivity of the material. A larger value results in a smoother result and less likely to retain edges; λ is the adjustment amplitude factor, which controls the amount of change in each iteration. A larger value results in a smoother result.

[0105] 2. Obtain the tomographic enhancement image volume through maximum likelihood attributes.

[0106] Maximum likelihood attribution is a statistical method for estimating parameters. It selects the parameter value most likely to produce the observed result based on observed data. In earthquake fault prediction, maximum likelihood attribution can be used to estimate parameters such as the location, morphology, and properties of earthquake faults, thereby improving prediction accuracy.

[0107] The fault signal in 3D seismic data can be expressed as formula (15):

[0108] g=sgn(g)log(1+|g|) (15)

[0109] Where g is the seismic data, sgn() is the sign function, and log() is the logarithmic function.

[0110] Calculate the maximum fault likelihood attribute volume L max , the calculation process is as follows:

[0111] Set the azimuth scanning space of the fault plane, and set φ min 、φ max 、n φ are the minimum azimuth, maximum azimuth, and average score, respectively. is the scanning interval, and the azimuth scanning space is formula (16):

[0112] Φ={φ i |φ min ≤φ i ≤φ max , i=1, 2, 3, ..., n φ -1, n φ} (16)

[0113] Let F smth(inData, ω) is the local attribute smoothing function along the fault plane, where inData is the data of the target data point in the attribute volume to be smoothed, and ω∈W is the local occurrence of the fault plane where inData is located.

[0114] The known earthquake dip-orientation coherence formulas are as follows (17)-(20):

[0115]

[0116] g ～ [i x ,i y ,i t ,j x ,j y ]=g[i x ,i y ,i t ,p x [i x ,i y ,i t ]j x ,p y [i x ,i y ,i t ]j y ] (18)

[0117]

[0118]

[0119] Among them, g is earthquake data, p x 、p y are the x- and y-direction components of the seismic reflection interface inclination attribute, M x , M y are the window radii of coherence in the x and y directions respectively. When the seismic reflection interface is isotropic, M x =M y ,j x 、j y are the window offsets in the x and y directions respectively, and the local seismic reflection interface inclination attribute volume p is calculated using the structural tensor.

[0120] The relevant smoothing calculation formula for fault plane orientation is as follows (21):

[0121]

[0122] Calculate the fault likelihood attribute body, formula is as follows (22):

[0123] l(i x ,i y ,it ,ω)=1-(s smth [i x ,i y ,i t ,ω]) 8 (twenty two)

[0124] To find the maximum fault likelihood attribute body, the formula is as follows (23)-(24):

[0125] l max (i x ,i y ,i t )=max{l(i x ,i y ,i t ,ω)},ω∈W (23)

[0126] L max ={l max (i x ,i y ,i t )} (twenty four)

[0127] To L max The strip-like data in the image are thinned to obtain the fault-enhanced image volume, which is the separation barrier between different fracture-cavity reservoirs.

[0128] Based on the above, the maximum fault likelihood attribute is used to achieve fine identification of separation barriers, such as Figure 4 In order to superimpose the separation barrier onto the fracture-cavity reservoir cross section, the arrows in the figure indicate the separation barrier. It can be seen that the separation barrier is roughly distributed around the fracture-cavity reservoir.

[0129] Step 3: Use phase continuity scanning technology to identify tight and broken formations inside the fracture-cavity reservoir.

[0130] Fracture-cavity reservoirs typically contain dense and fractured strata. Dense strata typically have low porosity and permeability, limiting the flow of fluids within the reservoir. Fractured strata refer to fractures, cracks, or fracture zones formed by crustal movement or other geological processes. These strata typically have high permeability and large porosity, providing good storage space and channels, which are conducive to the storage and migration of fluids within the reservoir. Phase continuity scanning technology can be used to identify the continuity characteristics of strata to characterize the degree of density or fracture of the strata. Phase continuity scanning technology is a method used for seismic data processing, primarily used to analyze and interpret the continuity and fracture characteristics of underground strata structures. It identifies continuity and fracture surfaces in underground strata by detecting changes in the phase of seismic waves, providing important information for geological interpretation. Phase continuity scanning technology can be applied to three-dimensional seismic data. The basic idea is to calculate the phase difference between adjacent seismic traces based on the phase information recorded in the seismic data, and further analyze the distribution of these phase differences to infer the continuity characteristics of the underground strata. Strata with good continuity are dense strata, while strata with poor continuity are broken strata.

[0131] Assume there is a continuous wave (CW) signal with a frequency of f, which can be expressed as formula (25):

[0132]

[0133] Among them, S(t) is the signal curve, A is the amplitude of the signal, t is the time, f is the frequency of the signal, is the phase of the signal.

[0134] In phase continuity scanning technology, we want to change the phase of the signal In order to facilitate analysis, we can use the phase Expressed as the sum of a linear phase and a nonlinear phase:

[0135]

[0136] Where φl(t) is the linear phase and φnl(t) is the nonlinear phase.

[0137] In practical applications, we usually use a linearly changing phase to achieve continuous scanning. Assuming that the linear phase changes according to the speed v, the linear phase can be expressed as:

[0138]

[0139] in, is the initial phase.

[0140] Substituting the linear phase into the signal expression, we get:

[0141]

[0142] After simplification, we get:

[0143]

[0144] It can be seen that by changing the linear phase By changing the slope v of the signal, we can change the signal frequency, thereby achieving a scanning or modulation effect. Figure 5 To obtain the phase section, the phase section is superimposed with the fracture-cavity reservoir section, as shown in Figure 6 As shown in (a) and (b), it can be seen that tight strata and fracture zones are alternately developed inside the reservoir.

[0145] Step 4: Use the instantaneous attenuation attribute to characterize the internal dissolution zone of the fracture-cavity reservoir.

[0146] "Dissolution zone" refers to the cavity or channel formed in the carbonate rock formation due to water flow and dissolution. Since carbonate rock has a high solubility in water, water dissolves in the rock and forms a dissolution zone. These dissolution zones provide additional storage space and play a role in increasing the reservoir reserves and improving the fluid channel. When the fluid enters the fracture-cavity reservoir, it will dissolve the original formation and form a "dissolution zone", but the degree of dissolution in the dense formation and the fracture zone is often quite different. Therefore, complex and changing dissolution zones will develop inside the fracture-cavity reservoir. When the seismic wave passes through the "dissolution zone" formation inside the cave, it will cause frequency and energy attenuation, and the high-frequency part of the seismic wave will attenuate particularly sharply. Therefore, the original seismic data without gain processing can be used to calculate the instantaneous attenuation quality factor to characterize the "dissolution zone" inside the fracture-cavity body. The specific calculation formula is as follows (30):

[0147]

[0148] Among them, Q i Q is the instantaneous attenuation quality factor, f is the instantaneous frequency, A is the amplitude envelope, and dA / dx is the derivative of the amplitude envelope. i The smaller the absolute value of the instantaneous quality factor, the stronger the dissolution effect.

[0149] Step 5: Superimpose the fracture-cavity reservoir, separation barrier, tight stratum, fractured stratum, and dissolution zone to precisely depict the internal structure of the fracture-cavity reservoir.

[0150] like Figure 7As shown in (a) and (b), the effect of superimposing the instantaneous quality factor with the fracture-cavity reservoir, separation barrier, tight formation, and broken formation can be clearly seen from the figure. The distribution characteristics of the fracture-cavity reservoir separation barrier, tight formation, and broken formation can be clearly seen, which means that the internal structure of the fracture-cavity reservoir is finely portrayed.

[0151] The present invention also provides a system for characterizing the internal structure of a carbonate fracture-vuggy reservoir, comprising:

[0152] The contour characterization module is used to obtain seismic data and use the median filter algorithm to separate the fracture-cavity reservoir from the original stratum to achieve the contour characterization of the fracture-cavity reservoir;

[0153] Separation barrier characterization module, which is used to obtain seismic data and use fault identification technology to obtain fault enhancement images to achieve the characterization of separation barriers of fracture-cavity reservoirs;

[0154] The dense and fractured formation characterization module is used to obtain seismic data and use phase continuity scanning technology to obtain the continuous characteristics of the internal formations of fracture-cavity reservoirs to achieve the characterization of dense and fractured formations;

[0155] The dissolution zone characterization module is used to obtain seismic data and use the instantaneous attenuation properties of seismic waves to characterize the dissolution zones inside fracture-cavity reservoirs;

[0156] The superposition module is used to superimpose fracture-cavity reservoirs, separation barriers, tight formations, fractured formations, and dissolution zones to achieve a detailed depiction of the internal configuration of fracture-cavity reservoirs.

[0157] One embodiment of the present invention provides a terminal device comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the processor implements the steps of the aforementioned method for characterizing the internal configuration of a carbonate fracture-vuggy reservoir; alternatively, when the processor executes the computer program, the processor implements the functions of the various modules of the aforementioned system for characterizing the internal configuration of a carbonate fracture-vuggy reservoir.

[0158] The computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to accomplish the present invention.

[0159] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0160] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0161] The memory may be used to store the computer programs and / or modules, and the processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory.

[0162] If the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0163] Based on this understanding, the present invention can implement all or part of the processes in the above-mentioned embodiment method by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of the above-mentioned method for characterizing the internal structure of carbonate fracture-vuggy reservoirs. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form.

[0164] The computer-readable medium may include any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electric carrier signal, a telecommunications signal, and a software distribution medium. It should be noted that the content of the computer-readable medium may be appropriately increased or decreased based on the requirements of legislation and patent practice within a jurisdiction. For example, in some jurisdictions, based on legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunications signals.

Claims

1. A method for characterizing the internal structure of a carbonate fracture-vuggy reservoir, characterized in that: The specific steps are as follows: Seismic data is obtained and the median filter algorithm is used to separate the fracture-cavity reservoir from the original stratum to achieve the contour characterization of the fracture-cavity reservoir; Acquire seismic data and use fault identification technology to obtain fault-enhanced images to characterize the barriers separating fracture-cavity reservoirs; Acquire seismic data and use phase continuity scanning technology to obtain the continuous characteristics of the internal strata of fracture-cavity reservoirs, and achieve the characterization of dense and broken strata; Obtain seismic data and use the instantaneous attenuation properties of seismic waves to characterize the internal dissolution zones of fracture-cavity reservoirs; The fracture-cavity reservoirs, separation barriers, tight formations, fractured formations and dissolution zones are superimposed to achieve a detailed depiction of the internal configuration of the fracture-cavity reservoirs.

2. The method for characterizing the internal structure of a carbonate fracture-vuggy reservoir according to claim 1, wherein: The median filter algorithm is used to filter and process the seismic data, separate the energy of the fracture-cavity reservoir from the energy of the surrounding strata, and fill the interior of the fracture-cavity reservoir with a uniform value to achieve a fine depiction of the fracture-cavity reservoir's outline.

3. The method for characterizing the internal structure of a carbonate fracture-vuggy reservoir according to claim 1, wherein: Anisotropic diffusion filtering is used to perform dip-guided filtering on seismic data, and then the fault enhancement image volume is estimated using maximum likelihood attributes.

4. The method for characterizing the internal structure of a carbonate fracture-vuggy reservoir according to claim 3, wherein: The anisotropic diffusion filtering method is as follows: Where g is the seismic data, and t is the number of iterations. The six divergence formulas are to find the partial derivatives of the current seismic data in six directions, as shown in (3)-(8): cE, cW, cN, cS, cD, and cU represent the thermal conductivity coefficients in six directions, as shown in formulas (9)-(14): Where t is the number of iterations; k is the thermal conductivity of the material; and λ is the adjustment amplitude factor.

5. The method for characterizing the internal structure of a carbonate fracture-vuggy reservoir according to claim 3, wherein: The maximum likelihood attribute is used to estimate the tomographic enhancement image volume, as follows: First, set the azimuth scanning space and scanning interval of the tomographic plane; Secondly, establish the local attribute smoothing function F along the fault plane smth (inData,ω), using the seismic dip-oriented coherence formula to perform fault plane orientation smoothing calculations and obtain the maximum fault likelihood attribute volume; Finally, the strip-like data in the maximum fault likelihood attribute volume are thinned to obtain the fault enhancement image volume, which is the separation barrier between different fracture-cavity reservoirs.

6. The method for characterizing the internal structure of a carbonate fracture-vuggy reservoir according to claim 5, characterized in that: The azimuth scanning space of the fault plane is specifically: Φ={φ i |f min ≤φ i ≤φ max ,i=1、2、3、...、n φ -1、n φ } (16) Among them, φ min 、φ max 、n φ are the minimum azimuth, maximum azimuth, and average score, respectively. is the scanning interval.

7. The method for characterizing the internal structure of a carbonate fracture-vuggy reservoir according to claim 5, characterized in that: Local attribute smoothing function F along the fault plane smth In (inData,ω), inData is the data of the target data point in the attribute volume to be smoothed, and ω∈W is the local occurrence of the fault plane where inData is located; The relevant smoothing calculation formula of fault plane orientation is obtained by using the seismic dip angle orientation coherence formula as shown in (21): Specifically, the seismic dip steering coherence formulas are as follows (17)-(20): g ～ [i x ,i y ,i t ,j x ,j y ]=g[i x ,i y ,i t ,p x [i x ,i y ,i t ]j x ,p y [i x ,i y ,i t ]j y ] (18) Among them, g is earthquake data, p x 、p y are the x- and y-direction components of the seismic reflection interface inclination attribute, M x , M y are the window radii of coherence in the x and y directions respectively. When the seismic reflection interface is isotropic, M x =M y ,j x 、j y are the window offsets in the x and y directions, respectively, and the local seismic reflection interface inclination attribute volume p is calculated using the structural tensor; The formula for calculating the fault likelihood attribute body is as follows (22): l(i x ,i y ,i t ,ω)=1-(s smth [i x ,i y ,i t ,ω]) 8 (22) To find the maximum fault likelihood attribute body, the formula is as follows (23)-(24): l max (i x ,i y ,i t )=max{l(i x ,i y ,i t ,ω)},ω∈W (23) L max ={l max (i x ,i y ,i t )} (24)。 8. The method for characterizing the internal structure of a carbonate fracture-vuggy reservoir according to claim 1, wherein: The instantaneous attenuation quality factor is calculated using the original seismic data without gain processing to characterize the internal dissolution zone of the fracture-cavity body, as follows: Among them, Q i is the instantaneous attenuation quality factor, f is the instantaneous frequency, A is the amplitude envelope, and dA / dx is the derivative of the amplitude envelope.

9. A system for characterizing the internal structure of carbonate fracture-vuggy reservoirs, characterized by: include: The contour characterization module is used to obtain seismic data and use the median filter algorithm to separate the fracture-cavity reservoir from the original stratum to achieve the contour characterization of the fracture-cavity reservoir; Separation barrier characterization module, which is used to obtain seismic data and use fault identification technology to obtain fault enhancement images to achieve the characterization of separation barriers of fracture-cavity reservoirs; The dense and fractured formation characterization module is used to obtain seismic data and use phase continuity scanning technology to obtain the continuous characteristics of the internal formations of fracture-cavity reservoirs to achieve the characterization of dense and fractured formations; The dissolution zone characterization module is used to obtain seismic data and use the instantaneous attenuation properties of seismic waves to characterize the dissolution zones inside fracture-cavity reservoirs; The superposition module is used to superimpose fracture-cavity reservoirs, separation barriers, tight formations, fractured formations, and dissolution zones to achieve a detailed depiction of the internal configuration of fracture-cavity reservoirs.

10. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the processor implements the steps of the method for characterizing the internal configuration of a carbonate fracture-vuggy reservoir according to any one of claims 1 to 8 or the functions of each module in the system according to claim 9.

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