Method and apparatus for modeling reservoir fracture permeability

Abstract

The application discloses a reservoir fracture permeability modeling method and device, and the method comprises the following steps: determining a quality factor data volume reflecting fracture distribution of a target reservoir according to seismic wave attenuation attributes of the target reservoir; converting the quality factor data volume reflecting fracture distribution of the target reservoir into a fracture intensity data volume of the target reservoir; converting the fracture intensity data volume of the target reservoir into a fracture permeability attribute volume of the target reservoir through distribution conversion; and constructing a fracture permeability model of the target reservoir according to the fracture permeability attribute volume of the target reservoir. The application extracts the quality factor which can best reflect the fracture distribution, avoids using uncertain seismic attribute parameters, converts the fracture intensity data volume consistent with the fracture permeability distribution of a single well, converts the fracture intensity data volume into the fracture permeability attribute volume through distribution conversion, constructs the fracture permeability model of the target reservoir based on the fracture permeability attribute volume, and improves the objectivity and reliability of the fracture permeability modeling.

Description

Technical Field

[0001] This invention relates to the field of oil and gas geological exploration technology, and in particular to a method and apparatus for modeling reservoir fracture permeability. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] Modeling fracture permeability in fracture-cavity carbonate reservoirs is a crucial yet challenging task. Numerous studies have explored permeability by numerically solving the Navie-Stokes equations (Chorin & Alexandre Joel, 1968; Cetin Kiris & Dochan Kwak, 2001; Sedaghatjoo Z et al., 2018). This process typically involves simplifications and assumptions (Ghadimi P & Dashtimanesh A, 2011; Liu C et al., 2019). For different reservoirs, these simplifications require an understanding of the reservoir's spatial structure. For porous reservoirs, CT scan data can be used to establish the pore structure distribution, which can then be used for nonlinear fluid simulation (Peng S. et.al, 2016; Liu C et.al, 2019). For fractured carbonate reservoirs, the DFN model is widely used (Le Goc Ret.al, 2017; Lei Q et.al, 2017; Liu R et.al, 2018; Pan D et.al, 2019; Giuffrida Aet.al, 2020; Baptiste Lepillier et.al, 2020).

[0004] However, the use of the DFN model carries significant uncertainty because fracture geometry parameters (fracture length, aperture, strike, dip, etc.) are extremely difficult to determine. The most common method is to obtain precise fracture distribution data through laser scanning and microscopic scanning of outcrops, using this data as a reference for the fracture model in subsurface reservoir fracture simulation (Guerriero V et al., 2011, 2013). The DFN model has been used for over 30 years and is a widely accepted method for fracture modeling. However, a careful analysis of the inputs required by the DFN model—fracture geometry parameters—reveals that the uncertainty of this model is almost immeasurable. Aperture is the most important parameter, closely related to fracture porosity and permeability. However, this parameter is generally replaced by the average aperture; that is, in the fracture description, the aperture of each fracture or type of fracture is characterized by only one average aperture value. In core samples, the aperture of fractures in fracture-porosity carbonate rocks often varies greatly, with large ranges reaching the centimeter level. Ignoring aperture variations in modeling will inevitably lead to excessive model bias, making effective production prediction impossible.

[0005] Machine learning algorithms have been widely used by scholars in recent years to calculate reservoir permeability models. Anifowose F. et al. (2019) summarized six machine learning algorithms, established the dependency between well logging and seismic data, and constructed a permeability model through supervised learning, but did not specify which seismic attribute to use to simulate permeability. Rostami A. et al. (2019) compared various neural network algorithms, SVM algorithms, and GP algorithms, concluding that the neural network expert system was the optimal algorithm, while the GP algorithm was the most efficient. They used publicly available data banks, but did not analyze the completeness and reliability of the samples in supervised learning. Ursula Iturrarán-Viveros and Jorge O. Parra (2014) also used a neural network supervised learning algorithm to model the permeability of carbonate reservoirs. A key aspect of these studies was determining the true or most reliable permeability value. For porous carbonate reservoirs, this parameter is relatively easy to obtain, through laboratory measurements or even conventional well logging interpretation. However, for fracture-dissolution-cavity carbonate reservoirs, this seemingly uncontroversial data becomes completely unevaluable, thus losing the theoretical basis for machine learning and preventing algorithms such as support vector machines and neural networks from exerting their ability to find patterns in massive amounts of data. Summary of the Invention

[0006] This invention provides a method for modeling reservoir fracture permeability to improve the objectivity and reliability of fracture permeability modeling. The method includes:

[0007] The quality factor data volume reflecting the fracture distribution of the target reservoir is determined based on the seismic wave attenuation properties of the target reservoir.

[0008] The quality factor data volume reflecting the fracture distribution of the target reservoir is converted into the fracture intensity data volume of the target reservoir;

[0009] The fracture intensity data volume of the target reservoir is converted into the fracture permeability attribute volume of the target reservoir through distribution transformation;

[0010] Construct a fracture permeability model of the target reservoir based on the fracture permeability attribute body of the target reservoir.

[0011] This invention also provides a reservoir fracture permeability modeling device to improve the objectivity and reliability of fracture permeability modeling. The reservoir fracture permeability modeling device includes:

[0012] The quality factor determination module is used to determine the quality factor data volume reflecting the fracture distribution of the target reservoir based on the seismic wave attenuation properties of the target reservoir.

[0013] The fracture intensity conversion module is used to convert the quality data volume factor reflecting the fracture distribution of the target reservoir into the fracture intensity data volume of the target reservoir.

[0014] The fracture permeability conversion module is used to convert the fracture intensity data volume of the target reservoir into the fracture permeability attribute volume of the target reservoir through distribution conversion.

[0015] The fracture permeability model construction module is used to construct a fracture permeability model of the target reservoir based on the fracture permeability attribute body of the target reservoir.

[0016] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described reservoir fracture permeability modeling method.

[0017] This invention also provides a computer-readable storage medium storing a computer program that performs the above-described reservoir fracture permeability modeling method.

[0018] In this embodiment of the invention, a quality factor data volume reflecting the fracture distribution of the target reservoir is determined based on the seismic wave attenuation properties of the target reservoir; this quality factor data volume is then converted into a fracture intensity data volume of the target reservoir; the fracture intensity data volume is further converted into a fracture permeability attribute volume of the target reservoir through distribution transformation; and a fracture permeability model of the target reservoir is constructed based on the fracture permeability attribute volume. This embodiment of the invention improves the objectivity and reliability of fracture permeability modeling by extracting the quality factor that best reflects the fracture distribution, avoiding the use of uncertain seismic attribute parameters, determining a fracture intensity data volume consistent with the fracture permeability distribution through transformation, converting the fracture intensity data volume into a fracture permeability attribute volume through distribution transformation, and finally constructing a fracture permeability model of the target reservoir based on the fracture permeability attribute volume. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0020] Figure 1 A flowchart illustrating the implementation of the reservoir fracture permeability modeling method provided in this embodiment of the invention;

[0021] Figure 2 This is another implementation flowchart of the reservoir fracture permeability modeling method provided in the embodiments of the present invention;

[0022] Figure 3 The flowchart illustrates the implementation of step 203 in the reservoir fracture permeability modeling method provided in this embodiment of the invention.

[0023] Figure 3-1 This is a schematic diagram of crack intensity distribution in a well-side earthquake provided in an embodiment of the present invention;

[0024] Figure 4 The flowchart illustrates the implementation of step 104 in the reservoir fracture permeability modeling method provided in this embodiment of the invention.

[0025] Figure 5 A flowchart illustrating another implementation of the reservoir fracture permeability modeling method provided in this embodiment of the invention;

[0026] Figure 5-1 A schematic diagram of the logarithmic distribution of fracture permeability in a reservoir well provided for an embodiment of the present invention;

[0027] Figure 6A functional block diagram of the reservoir fracture permeability modeling device provided in an embodiment of the present invention;

[0028] Figure 7 Another functional module diagram of the reservoir fracture permeability modeling device provided in the embodiments of the present invention;

[0029] Figure 8 This is a structural block diagram of the fracture intensity conversion module 602 in the reservoir fracture permeability modeling device provided in an embodiment of the present invention;

[0030] Figure 9 This is a structural block diagram of the fracture permeability model construction module 604 in the reservoir fracture permeability modeling device provided in an embodiment of the present invention;

[0031] Figure 10 Another functional module diagram of the reservoir fracture permeability modeling device provided in the embodiments of the present invention;

[0032] Figure 11 This is a schematic diagram illustrating the intersection of reservoir matrix porosity and permeability in the study area, provided as an embodiment of the present invention.

[0033] Figure 12 A schematic diagram of the quality factor slice in the middle of the reservoir in the study area, after layer normalization, provided for an embodiment of the present invention.

[0034] Figure 13 A schematic diagram of the fracture permeability model of the reservoir (based on corner grid) in the study area provided for an embodiment of the present invention. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0036] Figure 1 The implementation flow of the reservoir fracture permeability modeling method provided in the embodiments of the present invention is illustrated. For ease of description, only the parts related to the embodiments of the present invention are shown, and are detailed below:

[0037] like Figure 1 As shown, the reservoir fracture permeability modeling method includes:

[0038] Step 101: Determine the quality factor data volume reflecting the fracture distribution of the target reservoir based on the seismic wave attenuation properties of the target reservoir.

[0039] Step 102: Convert the quality factor data volume reflecting the fracture distribution of the target reservoir into the fracture intensity data volume of the target reservoir.

[0040] Step 103: Convert the fracture intensity data volume of the target reservoir into the fracture permeability attribute volume of the target reservoir through distribution transformation;

[0041] Step 104: Construct a fracture permeability model of the target reservoir based on the fracture permeability attribute body of the target reservoir.

[0042] There are many types of seismic attributes, each with different geological significance. Using seismic attributes indiscriminately can yield chaotic results. Using instantaneous seismic attributes is optimal, provided they accurately reflect reservoir permeability. Seismic waves experience energy attenuation during propagation through strata, especially when encountering bedding planes, where attenuation accelerates. Geologically, strata with similar attributes exhibit similar seismic wave attenuation patterns; a fracture essentially represents a bedding plane. Therefore, the quality factor, theoretically, has the ability to reflect fracture distribution.

[0043] Research over the years has consistently highlighted the importance of quality factor parameters. Seismic wave attenuation is another crucial parameter besides porosity and permeability. It is closely related to rock porosity, permeability, and hydrocarbon saturation, all of which are important factors influencing reservoir seismic properties. Evaluating seismic wave attenuation is as important as evaluating instantaneous seismic wave velocity, providing a new means of observing reservoir facies and properties. Many scholars have studied seismic wave attenuation techniques, recognizing the close relationship between seismic wave attenuation and reservoir properties, and its ability to be estimated at different frequencies. Therefore, using seismic wave attenuation techniques to study reservoir properties affected by fractures yields better results.

[0044] In summary, this invention uses seismic wave attenuation technology (quality factor) to quantitatively analyze the fracture distribution in reservoirs.

[0045] Assume the quality factor Q is constant and independent of the frequency f. Then, the relationship between the quality factor Q, frequency f, and initial amplitude spectrum A0(f) is as follows:

[0046] |A1(f)|=|A0(f)|e -πft / Q Formula (1)

[0047] Where A0(f) represents the initial amplitude spectrum, A1(f) represents the final amplitude spectrum, and t represents the two-way travel time from the initial position to the final position.

[0048] By changing formula (1), we can obtain the following formula:

[0049]

[0050]

[0051] Where t0 represents the starting position time and t1 represents the ending position time.

[0052] Calculations of seismic attributes in multiple regions demonstrate that this method is highly stable. In stratigraphic systems with strong continuity, this estimation generally works without issue; however, when stratigraphic continuity is poor and A0(f) is very small, it can lead to significant estimation errors.

[0053] Therefore, based on the above discussion, the quality factor data volume reflecting the fracture distribution of the target reservoir (the reservoir under study) is determined according to the seismic wave attenuation properties. That is, after calculating the three-dimensional seismic wave attenuation properties, the distribution of quality factor parameters (quality factor data volume) is obtained.

[0054] In geostatistical modeling, the distributions of two datasets can be transformed. Furthermore, the distribution of any dataset can be transformed into another distribution, even if the two distributions are completely different. However, if the two distributions differ significantly (e.g., their forms are entirely different—one exponential, the other normal), then the two sets of data are not comparable. It is necessary to process the distribution characteristics of the quality factor of well-side seismic data to ensure that its distribution follows a similar pattern to that of drilling permeability.

[0055] The distribution of quality factor data cannot be directly converted. It's necessary to remove the seismic attributes that don't represent fractures and convert the seismic attribute distribution into a seismic fracture intensity distribution. In other words, the quality factor data reflecting the fracture distribution of the target reservoir is converted into the fracture intensity data of the target reservoir.

[0056] Furthermore, through distribution transformation (i.e. quantile transformation), the fracture intensity data volume of the target reservoir is converted into the fracture permeability attribute volume of the target reservoir, so as to construct the fracture permeability model of the target reservoir based on the fracture permeability attribute volume of the target reservoir.

[0057] In this embodiment of the invention, a quality factor data volume reflecting the fracture distribution of the target reservoir is determined based on the seismic wave attenuation properties of the target reservoir; this quality factor data volume is then converted into a fracture intensity data volume of the target reservoir; the fracture intensity data volume is further converted into a fracture permeability attribute volume of the target reservoir through distribution transformation; and a fracture permeability model of the target reservoir is constructed based on the fracture permeability attribute volume. This embodiment of the invention improves the objectivity and reliability of fracture permeability modeling by extracting the quality factor that best reflects the fracture distribution, avoiding the use of uncertain seismic attribute parameters, determining a fracture intensity data volume consistent with the fracture permeability distribution through transformation, converting the fracture intensity data volume into a fracture permeability attribute volume through distribution transformation, and finally constructing a fracture permeability model of the target reservoir based on the fracture permeability attribute volume.

[0058] Figure 2 Another implementation flow of the reservoir fracture permeability modeling method provided in the embodiments of the present invention is shown. For ease of description, only the parts related to the embodiments of the present invention are shown, and are detailed below:

[0059] In one embodiment of the present invention, in order to further improve the accuracy of fracture permeability modeling, such as Figure 2 As shown, based on the above method steps, the reservoir fracture permeability modeling method further includes:

[0060] Step 201: Determine the reservoir with a porosity less than the preset porosity as the target reservoir.

[0061] Core analysis was used to compare the surrounding rocks with larger fractures, and well sections with surrounding rock porosity below a preset porosity were extracted separately (target reservoirs). Here, it is assumed that when the porosity of carbonate reservoirs is below the preset porosity, the contribution to permeability comes from fractures, and the contribution of bedrock to permeability is negligible. This preset porosity can be adjusted according to different reservoirs. For example, the preset porosity can be 5% or 3%, etc.

[0062] In this embodiment of the invention, reservoirs with porosity less than a preset porosity are identified as target reservoirs, which can further improve the accuracy of fracture permeability modeling.

[0063] In one embodiment of the present invention, in order to further improve the accuracy of fracture permeability modeling, such as Figure 2 As shown, based on the above method steps, the reservoir fracture permeability modeling method further includes:

[0064] Step 202: Normalize the quality factor data volume reflecting the fracture distribution of the target reservoir to determine the normalized quality factor data volume.

[0065] Accordingly, step 102 converts the quality factor data volume reflecting the fracture distribution of the target reservoir into the fracture intensity data volume of the target reservoir, including:

[0066] Step 203: Convert the normalized quality factor data volume reflecting the fracture distribution of the target reservoir into the fracture intensity data volume of the target reservoir.

[0067] After determining the quality factor data volume reflecting the fracture distribution of the target reservoir, it is necessary to normalize the quality factor data volume to further improve the accuracy of fracture permeability modeling, thus determining the normalized quality factor data volume. Correspondingly, the normalized quality factor data volume reflecting the fracture distribution of the target reservoir is converted into the fracture intensity data volume of the target reservoir.

[0068] In this embodiment of the invention, the quality factor data volume reflecting the fracture distribution of the target reservoir is normalized to determine the normalized quality factor data volume. The normalized quality factor data volume is then converted into the fracture intensity data volume of the target reservoir, which can further improve the accuracy of fracture permeability modeling.

[0069] Figure 3 The implementation flow of step 203 in the reservoir fracture permeability modeling method provided in the embodiment of the present invention is shown. For ease of description, only the parts related to the embodiment of the present invention are shown, and are detailed below:

[0070] In one embodiment of the present invention, in order to further improve the accuracy of fracture permeability modeling, such as Figure 3 As shown, step 203 involves converting the normalized quality factor data volume reflecting the fracture distribution of the target reservoir into a fracture intensity data volume for the target reservoir, including:

[0071] Step 301: Remove seismic properties of the matrix that do not reflect fractures from the normalized quality factor data volume to obtain the fracture intensity data volume of the target reservoir.

[0072] The distribution of normalized quality factor data cannot be transformed. It is necessary to remove the seismic attributes that do not represent fractures and convert the seismic attribute distribution into a seismic fracture intensity distribution. Specifically, based on the core sample, extract the seismic attributes (normalized attributes) around well sections with clearly undeveloped fractures. Based on the distribution of these attributes, remove the matrix attribute values, i.e., subtract the matrix permeability, to obtain a quality factor characteristic that reflects the reservoir fracture distribution, similar to drilling permeability. Figure 3-1 This diagram illustrates the crack intensity distribution of a well-side earthquake according to an embodiment of the present invention. Figure 3-1 As can be seen, the normalized distribution of crack strength exhibits an exponential distribution.

[0073] In this embodiment of the invention, by removing seismic properties of the matrix that do not reflect the fractures from the normalized quality factor data volume, the fracture intensity data volume of the target reservoir can be obtained, which can further improve the accuracy of fracture permeability modeling.

[0074] Figure 4 The implementation flow of step 104 in the reservoir fracture permeability modeling method provided in the embodiment of the present invention is shown. For ease of description, only the parts related to the embodiment of the present invention are shown, and are detailed below:

[0075] In one embodiment of the present invention, in order to further improve the accuracy of fracture permeability modeling, such as Figure 4 As shown, step 104 involves constructing a fracture permeability model of the target reservoir based on the fracture permeability attribute body of the target reservoir, including:

[0076] Step 401: Based on the fracture permeability attribute volume of the target reservoir, extract multiple fracture permeability data existing in each corner grid.

[0077] Step 402: Based on the extracted crack permeability data of each corner grid, use Monte Carlo simulation to determine the crack permeability distribution of each corner grid.

[0078] Step 403: Based on the fracture permeability distribution of each corner grid, the fracture permeability data of each corner grid is determined by random path simulation to obtain the fracture permeability model of the target reservoir.

[0079] Typically, the corner grid size of the model is larger than the seismic sampling interval (3D). Therefore, in the process of fracture permeability modeling, it is also necessary to perform Monte Carlo simulation on the permeability values ​​corresponding to multiple seismic samples to obtain the permeability distribution of each corner grid, and then use random simulation to sample to obtain a true permeability model.

[0080] For each corner grid, based on the fracture permeability attribute volume of the target reservoir, all multiple fracture permeability data existing in that grid are extracted. Then, based on the extracted multiple fracture permeability data of each corner grid, the Monte Carlo method is used to simulate and obtain the fracture permeability distribution of each corner grid. Then, the random path simulation method is used to extract a sample from the multiple fracture permeability data to determine a fracture permeability data as the fracture permeability data of that corner grid, thereby obtaining the fracture permeability model of the target reservoir.

[0081] In this embodiment of the invention, multiple crack permeability data existing in each corner grid are extracted; the crack permeability distribution of each corner grid is determined by Monte Carlo simulation; and the crack permeability data of each corner grid is determined by random path simulation, which can further improve the accuracy of crack permeability modeling.

[0082] Figure 5 This paper illustrates another implementation flow of the reservoir fracture permeability modeling method provided in the embodiments of the present invention. For ease of description, only the parts related to the embodiments of the present invention are shown, and are detailed below:

[0083] In one embodiment of the present invention, in order to improve the accuracy of seismic interpretation of fracture permeability, such as Figure 5 As shown, based on the above method steps, the reservoir fracture permeability modeling method further includes:

[0084] Step 501: Use nuclear magnetic resonance logging to determine the fracture permeability distribution in a single well within the target reservoir.

[0085] After normalization, seismic attribute data (quality factor data volume) only represents the intensity of fracture distribution, not true permeability. It is necessary to establish a conversion relationship between reservoir fracture permeability and normalized quality factor data volume. This step requires combining various drilling and production data. First, laboratory measurements (i.e., core analysis permeability) do not include the contribution of fractures (due to the presence of fractures, especially large open fractures, it is impossible to drill suitable rock samples for laboratory measurements). Therefore, core analysis data is not used in fracture permeability interpretation. Conventional logging interpretation of fracture permeability has significant errors, and the Archie formula calculation results are based on porous formations, thus it is not suitable as a direct reference for fracture permeability. Nuclear magnetic resonance (NMR) logging is a relatively better choice, using permeability interpreted from NMR logging to determine the distribution of fracture permeability in a single well within the target reservoir.

[0086] In this embodiment of the invention, nuclear magnetic resonance logging is used to determine the distribution of fracture permeability in a single well within a target reservoir, which can improve the accuracy of interpreting the fracture permeability in a single well.

[0087] In one embodiment of the present invention, in order to further improve the accuracy of single-well fracture permeability interpretation, such as... Figure 5 As shown, based on the above method steps, the reservoir fracture permeability modeling method further includes:

[0088] Step 502: Using the fracture permeability obtained from well test interpretation, the fracture permeability in the single-well fracture permeability distribution of the target reservoir determined by nuclear magnetic resonance logging is corrected to determine the corrected single-well fracture permeability distribution of the target reservoir.

[0089] Nuclear magnetic resonance (NMR) logging is a relatively good option, especially NMR logging interpretation results that have been corrected by well test interpretation. That is, by using the permeability interpretation from well tests, the fracture permeability in the single-well fracture permeability distribution of the target reservoir determined by NMR logging is corrected, thereby obtaining the corrected single-well fracture permeability distribution of the target reservoir. Figure 5-1 This diagram illustrates the logarithmic distribution of fracture permeability in a single well of a reservoir, as provided in an embodiment of the present invention. From... Figure 5-1 It can be seen that the distribution of fracture permeability is completely different from that of matrix permeability. Its logarithmic distribution does not show the characteristics of a normal distribution. However, this characteristic is consistent with the actual geological conditions of fracture distribution and also with the research results in the literature (outcrop scanning measurement conclusions), that is, the larger the scale of the fracture, the fewer the number of fractures.

[0090] In this embodiment of the invention, the fracture permeability obtained from well test interpretation is used to correct the fracture permeability in the single-well fracture permeability distribution of the target reservoir determined by nuclear magnetic resonance logging, thereby determining the corrected single-well fracture permeability distribution of the target reservoir, which can further improve the accuracy of single-well fracture permeability interpretation.

[0091] In one embodiment of the present invention, in order to verify the accuracy of the fracture permeability model, such as Figure 5 As shown, based on the above method steps, the reservoir fracture permeability modeling method further includes:

[0092] Step 503: Validate the constructed fracture permeability model of the target reservoir using the single-well fracture permeability distribution corrected for the target reservoir.

[0093] Combination Figure 3-1 The distribution of crack intensity in the earthquake near the well is shown. Figure 5-1 The logarithmic distribution of fracture permeability shown reveals that the normalized distribution of fracture intensity also exhibits an exponential distribution, similar to the distribution of single-well fracture permeability, indicating an intrinsic correlation between the two. Therefore, the fracture intensity data volume of the target reservoir can be converted into the fracture permeability attribute volume of the target reservoir through distribution transformation.

[0094] Therefore, the fracture permeability in the single-well fracture permeability distribution (based on nuclear magnetic resonance logging interpretation) after correction of the target reservoir can be used to verify the fracture permeability model of the target reservoir (based on the quality factor of seismic wave attenuation properties) to evaluate the accuracy of the constructed fracture permeability model of the target reservoir.

[0095] In this embodiment of the invention, the fracture permeability model of the target reservoir is verified by using the single-well fracture permeability distribution after the target reservoir is corrected, which can verify the accuracy of the fracture permeability model.

[0096] This invention also provides a reservoir fracture permeability modeling apparatus, as described in the following embodiments. Since the principles underlying these apparatuses are similar to those of the reservoir fracture permeability modeling method, the implementation of these apparatuses can be found in the implementation of the method; repeated details will not be elaborated further.

[0097] Figure 6 The functional modules of the reservoir fracture permeability modeling device provided in the embodiments of the present invention are shown. For ease of explanation, only the parts related to the embodiments of the present invention are shown, and are described in detail below:

[0098] refer to Figure 6 The reservoir fracture permeability modeling device comprises various modules used for performing... Figure 1 For details of each step in the corresponding embodiment, please refer to [link / reference]. Figure 1 as well as Figure 1 The relevant descriptions in the corresponding embodiments will not be repeated here. In this embodiment of the invention, the reservoir fracture permeability modeling device includes a quality factor determination module 601, a fracture intensity conversion module 602, a fracture permeability conversion module 603, and a fracture permeability model construction module 604.

[0099] The quality factor determination module 601 is used to determine the quality factor data volume reflecting the fracture distribution of the target reservoir based on the seismic wave attenuation properties of the target reservoir.

[0100] The fracture intensity conversion module 602 is used to convert the quality data volume factor reflecting the fracture distribution of the target reservoir into the fracture intensity data volume of the target reservoir.

[0101] Fracture permeability conversion module 603 is used to convert the fracture intensity data volume of the target reservoir into the fracture permeability attribute volume of the target reservoir through distribution conversion;

[0102] The fracture permeability model construction module 604 is used to construct a fracture permeability model of the target reservoir based on the fracture permeability attribute body of the target reservoir.

[0103] In this embodiment of the invention, the quality factor determination module 601 determines a quality factor data volume reflecting the fracture distribution of the target reservoir based on the seismic wave attenuation properties of the target reservoir; the fracture intensity conversion module 602 converts the quality factor data volume reflecting the fracture distribution of the target reservoir into a fracture intensity data volume of the target reservoir; the fracture permeability conversion module 603 converts the fracture intensity data volume of the target reservoir into a fracture permeability attribute volume of the target reservoir through distribution conversion; and the fracture permeability model construction module 604 constructs a fracture permeability model of the target reservoir based on the fracture permeability attribute volume of the target reservoir. In this embodiment, the quality factor determination module 601 extracts the quality factors that best reflect the fracture distribution, avoiding the use of uncertain seismic attribute parameters. The fracture intensity conversion module 602 determines a fracture intensity data volume consistent with the fracture permeability distribution through conversion. Then, the fracture permeability conversion module 603 converts the fracture intensity data volume into a fracture permeability attribute volume through distribution conversion. Finally, the fracture permeability model construction module 604 constructs a fracture permeability model of the target reservoir based on the fracture permeability attribute volume, thereby improving the objectivity and reliability of fracture permeability modeling.

[0104] Figure 7 Another functional module of the reservoir fracture permeability modeling device provided in an embodiment of the present invention is shown. For ease of explanation, only the part related to the embodiment of the present invention is shown, and is described in detail below:

[0105] In one embodiment of the present invention, in order to further improve the accuracy of fracture permeability modeling, reference is made to... Figure 7 The reservoir fracture permeability modeling device comprises various modules used for performing... Figure 2 For details of each step in the corresponding embodiment, please refer to [link / reference]. Figure 2 as well as Figure 2 The relevant descriptions in the corresponding embodiments will not be repeated here. In the embodiments of the present invention, in the above... Figure 6Based on the functional modules shown, the reservoir fracture permeability modeling device also includes a target reservoir determination module 701.

[0106] The target reservoir determination module 701 is used to determine reservoirs with porosity less than a preset porosity as target reservoirs.

[0107] In this embodiment of the invention, the target reservoir determination module 701 determines reservoirs with porosity less than a preset porosity as target reservoirs, which can further improve the accuracy of fracture permeability modeling.

[0108] In one embodiment of the present invention, in order to further improve the accuracy of fracture permeability modeling, reference is made to... Figure 7 Based on the above functional modules, the reservoir fracture permeability modeling device also includes a quality factor normalization module 702.

[0109] The quality factor normalization module 702 is used to normalize the quality factor data volume reflecting the fracture distribution of the target reservoir and determine the normalized quality factor data volume.

[0110] Correspondingly, the fracture intensity conversion module 602 is specifically used to convert the normalized quality factor data volume reflecting the fracture distribution of the target reservoir into the fracture intensity data volume of the target reservoir.

[0111] In this embodiment of the invention, the quality factor normalization module 702 normalizes the quality factor data volume reflecting the fracture distribution of the target reservoir to determine the normalized quality factor data volume, and the fracture intensity conversion module 602 converts the normalized quality factor data volume into the fracture intensity data volume of the target reservoir, which can further improve the accuracy of fracture permeability modeling.

[0112] Figure 8 The diagram illustrates the structure of the fracture intensity conversion module 602 in the reservoir fracture permeability modeling device provided in an embodiment of the present invention. For ease of explanation, only the parts relevant to the embodiment of the present invention are shown, and are described in detail below:

[0113] In one embodiment of the present invention, in order to further improve the accuracy of fracture permeability modeling, reference is made to... Figure 8 The crack strength conversion module 602 includes various units for performing... Figure 3 For details of each step in the corresponding embodiment, please refer to [link / reference]. Figure 3 as well as Figure 3 The relevant descriptions in the corresponding embodiments will not be repeated here. In this embodiment of the invention, the crack strength conversion module 602 includes a matrix removal unit 801.

[0114] The matrix removal unit 801 is used to remove seismic properties of the matrix that do not reflect fractures from the normalized quality factor data volume, thereby obtaining the fracture intensity data volume of the target reservoir.

[0115] In this embodiment of the invention, the matrix removal unit 801 removes seismic properties of the matrix that do not reflect fractures from the normalized quality factor data volume, thereby obtaining the fracture intensity data volume of the target reservoir, which can further improve the accuracy of fracture permeability modeling.

[0116] Figure 9 The diagram illustrates the structure of the fracture permeability model construction module 604 in the reservoir fracture permeability modeling apparatus provided in an embodiment of the present invention. For ease of explanation, only the parts relevant to the embodiment of the present invention are shown, and are described in detail below:

[0117] In one embodiment of the present invention, in order to further improve the accuracy of fracture permeability modeling, reference is made to... Figure 9 The various units included in the fracture permeability model construction module 604 are used to perform... Figure 4 For details of each step in the corresponding embodiment, please refer to [link / reference]. Figure 4 as well as Figure 4 The relevant descriptions in the corresponding embodiments will not be repeated here. In this embodiment of the invention, the fracture permeability model construction module 604 includes a fracture permeability extraction unit 901, a Monte Carlo simulation unit 902, and a random path simulation unit 903.

[0118] The fracture permeability extraction unit 901 is used to extract multiple fracture permeability data existing in each corner grid based on the fracture permeability attribute volume of the target reservoir.

[0119] Monte Carlo simulation unit 902 is used to determine the fracture permeability distribution of each corner grid using Monte Carlo simulation based on multiple fracture permeability data extracted from each corner grid.

[0120] The random path simulation unit 903 is used to determine the fracture permeability data of each corner grid by using random path simulation based on the fracture permeability number distribution of each corner grid, so as to obtain the fracture permeability model of the target reservoir.

[0121] In this embodiment of the invention, the fracture permeability extraction unit 901 extracts multiple fracture permeability data existing in each corner grid; the Monte Carlo simulation unit 902 uses Monte Carlo simulation to determine the fracture permeability distribution of each corner grid; and the random path simulation unit 903 uses random path simulation to determine the fracture permeability model of the target reservoir, which can further improve the accuracy of fracture permeability modeling.

[0122] Figure 10This illustration shows another functional module of the reservoir fracture permeability modeling apparatus provided in an embodiment of the present invention. For ease of explanation, only the part related to the embodiment of the present invention is shown, and is described in detail below:

[0123] In one embodiment of the present invention, in order to improve the accuracy of seismic interpretation of fracture permeability, reference is made to... Figure 10 The reservoir fracture permeability modeling device comprises various modules used for performing... Figure 5 For details of each step in the corresponding embodiment, please refer to [link / reference]. Figure 5 as well as Figure 5 The relevant descriptions in the corresponding embodiments will not be repeated here. In this embodiment of the invention, based on the above functional modules, the reservoir fracture permeability modeling device further includes a single-well fracture permeability distribution determination module 1001.

[0124] The Single Well Fracture Permeability Determination Module 1001 is used to determine the single well fracture permeability distribution in a target reservoir using nuclear magnetic resonance logging.

[0125] In this embodiment of the invention, the single-well fracture permeability determination module 1001 uses nuclear magnetic resonance logging to determine the single-well fracture permeability distribution in the target reservoir.

[0126] In one embodiment of the present invention, in order to further improve the accuracy of single-well fracture permeability interpretation, reference is made to... Figure 10 Based on the above functional modules, the reservoir fracture permeability modeling device also includes a correction module 1002.

[0127] The correction module 1002 is used to correct the fracture permeability in the single-well fracture permeability distribution of the target reservoir determined by nuclear magnetic resonance logging using the fracture permeability obtained from well test interpretation, and to determine the corrected single-well fracture permeability distribution of the target reservoir.

[0128] In this embodiment of the invention, the correction module 1002 uses the fracture permeability obtained from well test interpretation to correct the fracture permeability in the single-well fracture permeability distribution of the target reservoir determined by nuclear magnetic resonance logging, thereby determining the corrected single-well fracture permeability distribution of the target reservoir, which can further improve the accuracy of single-well fracture permeability interpretation.

[0129] In one embodiment of the present invention, in order to verify the accuracy of the fracture permeability model, reference is made to... Figure 10 Based on the above functional modules, the reservoir fracture permeability modeling device also includes a verification module 1003.

[0130] The verification module 1003 is used to verify the fracture permeability model of the target reservoir by using the single-well fracture permeability distribution after correction of the target reservoir.

[0131] In this embodiment of the invention, the verification module 1003 uses the single-well fracture permeability distribution after the target reservoir is corrected to verify the fracture permeability model of the constructed target reservoir, thereby verifying the accuracy of the fracture permeability model.

[0132] This invention is not limited to carbonate reservoirs; it also provides effective simulation results for shale and tight sandstone. The following section, using a fracture-dissolution-cavity type carbonate reservoir in a specific block as an example, illustrates the modeling process and principle of fracture permeability in fracture-dissolution-cavity type carbonate reservoirs:

[0133] A total of 18 wells were drilled in the study area, some of which encountered relatively large fractures. Core analysis compared the surrounding rocks with these larger fractures, and well sections with surrounding rock porosity below 5% were isolated. Here, it is assumed that when the porosity of carbonate reservoirs is below 5%, the contribution to permeability comes from fractures, and the contribution of bedrock to permeability is negligible. This threshold value can be adjusted according to different reservoir types. Figure 11 This diagram illustrates the intersection of reservoir matrix porosity and permeability in the study area. From... Figure 11 It can be seen that when the porosity is less than 5%, the permeability value is less than 0.01 mD.

[0134] In studying fracture permeability distribution, the permeability values ​​used were derived from NMR logging interpretation results. In production wells, these permeability values ​​were further corrected for well test interpretation. The distribution of quality factor parameters was obtained by calculating the attenuation properties of 3D seismic waves. Initially, this distribution approximates a normal distribution, differing significantly from the well permeability distribution. This is because fractures are not absolutely dominant in the study area; many reservoirs within the study area are of the dissolution-void type. Therefore, the logarithmic distribution of permeability approximates a normal distribution. Such a distribution cannot be transformed; it is necessary to remove the seismic attributes that do not represent fractures and convert the seismic attribute distribution into a seismic fracture intensity distribution.

[0135] Based on the core sample, the seismic properties (normalized properties) around the well section with no obvious fractures are extracted. According to the distribution of these properties, the property values ​​of these matrices are removed, that is, the matrix permeability is subtracted, to obtain a distribution characteristic similar to the fracture permeability of a single well. Figure 12 This illustration shows a slice of the reservoir in the study area provided by an embodiment of the present invention, with the quality factor normalized along the layer. Many studies suggest that total permeability is the sum of matrix permeability and fracture permeability. Figure 3-1 It clearly reflects the directionality and grouping characteristics of the crack distribution. Cool tones have lower normalized attribute values, and the areas where this color is distributed represent crack development zones.

[0136] Using distribution transformation, the fracture intensity data volume obtained after filtering the normalized seismic quality factor attributes is transformed into a fracture permeability attribute volume. Thus, a post-stack seismic attribute volume becomes a fracture permeability attribute volume. Typically, the data density of the fracture permeability attribute volume is greater than that of the corner grid model. Therefore, for each corner grid, all fracture permeability data existing within that grid are extracted, and Monte Carlo simulation is performed to obtain the permeability data distribution for each corner grid. Then, a random path simulation method is used to extract samples to obtain a model based on the corner grid. Figure 13 This illustration shows a schematic diagram of a fracture permeability model for a reservoir (based on a corner grid) in the study area provided by an embodiment of the present invention.

[0137] from Figure 13 The fracture permeability model shown clearly indicates that fracture permeability is mainly distributed around larger fractures and in higher structural areas. This result is consistent with the geological patterns of fracture distribution obtained from core samples and seismic interpretations. This demonstrates that the proposed modeling method has high reliability and operability, avoids the influence of parameters that cannot be evaluated, and fully utilizes drilling, seismic, and well test data.

[0138] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described reservoir fracture permeability modeling method.

[0139] This invention also provides a computer-readable storage medium storing a computer program that performs the above-described reservoir fracture permeability modeling method.

[0140] Constructing fracture permeability models for target reservoirs is a crucial task in the petroleum geology industry, yet definitive solutions remain elusive. This invention first utilizes seismic wave attenuation technology to detect heterogeneity caused by fractures disrupting the matrix structure. The quantitative index for this is the quality factor, which, after normalization, effectively characterizes the distribution of fracture zones. Secondly, a distribution transformation method is employed to establish the relationship between single-well permeability data and well-side seismic attributes. Then, a Monte Carlo method is used to transform the single-well permeability distribution across the entire region, completing the permeability modeling. Fracture permeability models built using the DFN (Digital-Fractional-Nutrition) model require prior acquisition of reservoir-fracture geometry parameters and struggle to determine the relationship between fracture aperture and permeability, as well as to evaluate uncertainties. Compared to the DFN modeling method, this invention offers greater operability, primarily addressing the challenge of constructing fracture permeability models for target reservoirs when outcrop data is lacking and traditional modeling procedures are not feasible. The constructed model, in addition to satisfying well data constraints, conforms to the framework of tectonic and sedimentological theories in interpreting geological phenomena. Meanwhile, this invention does not artificially define the geometric parameters of cracks during the process of determining the spatial distribution of cracks, which significantly reduces the interference of human factors. All uncertainties in the transformation are controllable and there is no arbitrariness. The calculation results are more objective and have high credibility.

[0141] This invention, based on drilling and seismic data, extracts the seismic attributes that best reflect fracture distribution through comprehensive analysis of seismic properties. These attributes are then normalized to obtain a corresponding normalized attribute distribution of permeability that closely approximates the actual reservoir geological patterns. The distribution of fracture permeability in a single well is determined using nuclear magnetic resonance logging (with necessary corrections if well test data is available) and core data. After comparing the two distributions and confirming their reasonableness, a distribution transformation method from geostatistics is used to convert the seismic attribute parameters into permeability parameters. Finally, this permeability volume data is transformed into a corner grid using Monte Carlo simulation (typically, the corner grid scale is larger than the scale of the grid formed by the seismic trace spacing and sampling interval), completing the fracture permeability modeling.

[0142] This fracture permeability modeling method fully utilizes drilling, seismic, and production data. Starting from the perspective of data distribution and based on the macroscopic laws of reservoir geology, it possesses significant practical value. The method in this invention avoids the difficulty in evaluating modeling results caused by uncertain parameters in complex computational simulations, making this invention highly operable. Studies on fracture distribution in multiple oilfields have yielded excellent results.

[0143] In summary, in this embodiment of the invention, a quality factor data volume reflecting the fracture distribution of the target reservoir is determined based on the seismic wave attenuation properties of the target reservoir; this quality factor data volume is then converted into a fracture intensity data volume of the target reservoir; the fracture intensity data volume is further converted into a fracture permeability attribute volume of the target reservoir through distribution transformation; and a fracture permeability model of the target reservoir is constructed based on the fracture permeability attribute volume. This embodiment of the invention improves the objectivity and reliability of fracture permeability modeling by extracting the quality factor that best reflects the fracture distribution, avoiding the use of uncertain seismic attribute parameters, determining a fracture intensity data volume consistent with the fracture permeability distribution through transformation, converting the fracture intensity data volume into a fracture permeability attribute volume through distribution transformation, and finally constructing a fracture permeability model of the target reservoir based on the fracture permeability attribute volume.

[0144] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can 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, etc.) containing computer-usable program code.

[0145] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can 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, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0146] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0147] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0148] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for modeling reservoir fracture permeability, characterized in that, include: The quality factor data volume reflecting the fracture distribution of the target reservoir is determined based on the seismic wave attenuation properties of the target reservoir. The quality factor data volume reflecting the fracture distribution of the target reservoir is converted into the fracture intensity data volume of the target reservoir; The fracture intensity data volume of the target reservoir is converted into the fracture permeability attribute volume of the target reservoir through distribution transformation; Construct a fracture permeability model of the target reservoir based on the fracture permeability attribute volume of the target reservoir; It also includes: normalizing the quality factor data volume reflecting the fracture distribution of the target reservoir to determine the normalized quality factor data volume; Converting the quality factor data volume reflecting the fracture distribution of the target reservoir into the fracture intensity data volume of the target reservoir includes: converting the normalized quality factor data volume reflecting the fracture distribution of the target reservoir into the fracture intensity data volume of the target reservoir. The normalized quality factor data volume reflecting the fracture distribution of the target reservoir is converted into the fracture intensity data volume of the target reservoir, including: based on the core, removing the seismic properties of the matrix that do not reflect the fracture in the normalized quality factor data volume to obtain the fracture intensity data volume of the target reservoir. The fracture permeability model of the target reservoir is constructed based on the fracture permeability attribute volume of the target reservoir, including: extracting multiple fracture permeability data points existing in each corner grid based on the fracture permeability attribute volume of the target reservoir; determining the fracture permeability distribution of each corner grid using Monte Carlo simulation based on the extracted multiple fracture permeability data points of each corner grid; and determining the fracture permeability data of each corner grid using random path simulation based on the fracture permeability distribution of each corner grid, thereby obtaining the fracture permeability model of the target reservoir.

2. The reservoir fracture permeability modeling method as described in claim 1, characterized in that, Also includes: Reservoirs with porosity less than a preset porosity are identified as target reservoirs.

3. The reservoir fracture permeability modeling method as described in claim 1, characterized in that, Also includes: Nuclear magnetic resonance logging was used to determine the fracture permeability distribution in a single well within a target reservoir.

4. The reservoir fracture permeability modeling method as described in claim 3, characterized in that, Also includes: Using the fracture permeability obtained from well test interpretation, the fracture permeability in the single-well fracture permeability distribution of the target reservoir determined by nuclear magnetic resonance logging is corrected to determine the corrected single-well fracture permeability distribution of the target reservoir.

5. The reservoir fracture permeability modeling method as described in claim 4, characterized in that, Also includes: The fracture permeability model of the target reservoir was validated by using the single-well fracture permeability distribution after correction of the target reservoir.

6. A reservoir fracture permeability modeling device, characterized in that, include: The quality factor determination module is used to determine the quality factor data volume reflecting the fracture distribution of the target reservoir based on the seismic wave attenuation properties of the target reservoir. The fracture intensity conversion module is used to convert the quality data volume factor reflecting the fracture distribution of the target reservoir into the fracture intensity data volume of the target reservoir. The fracture permeability conversion module is used to convert the fracture intensity data volume of the target reservoir into the fracture permeability attribute volume of the target reservoir through distribution conversion. The fracture permeability model construction module is used to construct a fracture permeability model of the target reservoir based on the fracture permeability attribute body of the target reservoir. It also includes: a quality factor normalization module, which is used to normalize the quality factor data volume reflecting the fracture distribution of the target reservoir and determine the normalized quality factor data volume; The fracture intensity conversion module is specifically used to convert the normalized quality factor data volume reflecting the fracture distribution of the target reservoir into the fracture intensity data volume of the target reservoir. The fracture strength conversion module includes a matrix removal unit, which is used to remove seismic properties of the matrix that do not reflect fractures from the normalized quality factor data volume based on the core sample, and obtain the fracture strength data volume of the target reservoir. The fracture permeability model construction module includes: a fracture permeability extraction unit, used to extract multiple fracture permeability data existing in each corner grid based on the fracture permeability attribute volume of the target reservoir; a Monte Carlo simulation unit, used to determine the fracture permeability distribution of each corner grid using Monte Carlo simulation based on the extracted multiple fracture permeability data of each corner grid; and a random path simulation unit, used to determine the fracture permeability data of each corner grid using random path simulation based on the fracture permeability distribution of each corner grid, thereby obtaining the fracture permeability model of the target reservoir.

7. The reservoir fracture permeability modeling device as described in claim 6, characterized in that, Also includes: The target reservoir determination module is used to identify reservoirs with porosity less than a preset porosity as target reservoirs.

8. The reservoir fracture permeability modeling device as described in claim 6, characterized in that, Also includes: The module for determining the permeability distribution of fractures in a single well is used to determine the permeability distribution of fractures in a target reservoir using nuclear magnetic resonance logging.

9. The reservoir fracture permeability modeling device as described in claim 8, characterized in that, Also includes: The correction module is used to correct the fracture permeability in the single-well fracture permeability distribution of the target reservoir determined by nuclear magnetic resonance logging, using the fracture permeability obtained from well test interpretation, and to determine the corrected single-well fracture permeability distribution of the target reservoir.

10. The reservoir fracture permeability modeling device as described in claim 9, characterized in that, Also includes: The verification module is used to verify the fracture permeability model of the target reservoir by using the single-well fracture permeability distribution after correction of the target reservoir.

11. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the reservoir fracture permeability modeling method according to any one of claims 1 to 5.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the reservoir fracture permeability modeling method according to any one of claims 1 to 5.

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