Coring fluid property evaluation method, device, equipment and storage medium

Abstract

The application discloses a kind of cuttings formation fluid property evaluation methods, including collecting cuttings sample under ultraviolet light irradiation under the cuttings fluorescence image and white light irradiation under the cuttings image;Fluorescence area in cuttings fluorescence image is identified, and fluorescence area area and fluorescence brightness are obtained;According to fluorescence area area and fluorescence brightness, determine the hydrocarbon abundance corresponding to cuttings sample;The geometric characteristics of each cuttings grain in cuttings image are identified to determine the porosity of cuttings sample;According to at least any two parameters in fluorescence area area, hydrocarbon abundance, porosity three parameters, determine the oiliness of formation corresponding to cuttings sample.In the present application, based on cuttings image and cuttings fluorescence image, the fluorescence area area of cuttings sample, hydrocarbon abundance and porosity are determined and the cuttings oiliness is determined, to ensure the accuracy of the evaluation obtained formation oiliness.The present application also provides a kind of cuttings formation fluid property evaluation device, equipment and computer readable storage medium, with the above beneficial effects.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration technology, and in particular to a method, apparatus, equipment, and computer storage medium for evaluating the properties of fluids in rock cutting formations. Background Technology

[0002] Exploring the oil and gas content in the formation is an essential step before oil wells can be used for oil and gas extraction. It has important guiding significance for oil and gas extraction, so the accuracy of formation oil and gas exploration results is of great importance to actual oil and gas extraction.

[0003] Currently, there are two main methods for exploring formation oil and gas: one is to analyze the radioactivity of formation cuttings and then analyze the oil content within the cuttings formation; the other is to utilize ultrasonic waves transmitted through the formation and obtain well logging data by detecting the reflected sound waves, then analyze the well logging data to determine the formation's oil content. However, in practical applications, it has been found that the accuracy of the formation oil content determined by these two exploration methods is not high. Summary of the Invention

[0004] The purpose of this invention is to provide a method, apparatus, equipment, and computer-readable storage medium for evaluating the fluid properties of rock cuttings formations, which greatly improves the accuracy of oil content analysis and evaluation of rock cuttings formations.

[0005] To address the aforementioned technical problems, this invention provides a method for evaluating the properties of fluids in rock cuttings formations, comprising:

[0006] Images of rock cuttings under ultraviolet light and under white light were collected.

[0007] Identify the fluorescent regions in the rock debris fluorescence image to obtain the area and brightness of the fluorescent regions;

[0008] The hydrocarbon abundance of the rock fragment sample is determined based on the area of ​​the fluorescent region and the fluorescence intensity.

[0009] Identify the geometric features of the imaging regions of each rock fragment in the rock fragment image, and determine the porosity of the rock fragment sample based on the geometric features;

[0010] The formation oil content of the rock cuttings sample is determined based on at least two of the following three parameters: the area of ​​the fluorescent region, the hydrocarbon abundance, and the porosity.

[0011] Optionally, identifying fluorescent regions in the rock debris fluorescence image and obtaining the area and intensity of the fluorescent regions includes:

[0012] Using image recognition technology, the fluorescent region corresponding to each rock fragment in the rock fragment fluorescence image is segmented and identified;

[0013] The maximum fluorescence brightness value of each of the fluorescent regions is averaged, and the average value is used as the fluorescence brightness.

[0014] The sum of the areas of all the fluorescent regions is the area of ​​the fluorescent region.

[0015] Optionally, determining the hydrocarbon abundance of the rock fragment sample based on the area of ​​the fluorescent region and the fluorescence intensity includes:

[0016] According to the hydrocarbon abundance formula Determine the hydrocarbon abundance; wherein, The hydrocarbon abundance; The area of ​​the fluorescent region; The fluorescence brightness; It is the first constant coefficient; It is the second constant coefficient.

[0017] Optionally, determining the porosity of the rock cutting sample based on the geometric features includes:

[0018] Based on the geometric features, the proportion of rock debris particles in the rock debris image whose geometric shape and circular shape approximation reach a preset approximation degree is determined as the roundness of the rock debris particles;

[0019] The porosity of the rock cutting sample is determined based on the pre-determined correspondence between the roundness of rock cutting particles and the porosity of rock cutting particles.

[0020] Optionally, the formation oil content of the cuttings sample is determined based on at least two of the following three parameters: the area of ​​the fluorescent region, the hydrocarbon abundance, and the porosity:

[0021] Based on historical fluorescence region area, historical hydrocarbon abundance, and historical porosity, an interpretation chart characterizing the relationship between at least two of the parameters (fluorescence region area, hydrocarbon abundance, and porosity) and formation oiliness is pre-determined.

[0022] Based on at least two of the three parameters—the area of ​​the fluorescent region corresponding to the rock cuttings sample, the hydrocarbon abundance, and the porosity—the formation oiliness corresponding to each layer of the rock cuttings sample is determined in the interpretation chart.

[0023] Optionally, after determining the formation oiliness, the method further includes:

[0024] Output information on the formation oil content of rock cuttings samples at different formation depths as the formation depth varies.

[0025] Optionally, images of rock cuttings under ultraviolet light and under white light are acquired, including:

[0026] The fluorescence image of the rock debris and the image of the rock debris were acquired using a microscope.

[0027] This application also provides a device for evaluating the fluid properties of rock cuttings formations, including:

[0028] The image acquisition module is used to acquire fluorescence images of rock cuttings under ultraviolet light and images of rock cuttings under white light.

[0029] The fluorescence recognition module is used to identify the fluorescent regions in the rock cutting fluorescence image and obtain the area and brightness of the fluorescent regions.

[0030] The first calculation module is used to determine the hydrocarbon abundance of the rock cutting sample based on the area of ​​the fluorescent region and the fluorescence brightness.

[0031] The second calculation module is used to identify the geometric features of the imaging area of ​​each rock cutting particle in the rock cutting image, and to determine the porosity of the rock cutting sample based on the geometric features.

[0032] The oil content analysis module is used to determine the formation oil content of the rock cuttings sample based on at least two of the following three parameters: the area of ​​the fluorescent region, the hydrocarbon abundance, and the porosity.

[0033] This application also provides a device for evaluating the fluid properties of rock cuttings formations, including:

[0034] Memory, used to store computer programs;

[0035] A processor for executing the computer program to implement the steps of the method for evaluating the fluid properties of cuttings formations as described in any of the preceding claims.

[0036] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the rock cuttings formation fluid property evaluation method as described in any of the preceding claims.

[0037] The present invention provides a method for evaluating the fluid properties of rock cuttings formations, comprising: acquiring rock cutting fluorescence images under ultraviolet light irradiation and rock cutting images under white light irradiation; identifying fluorescent regions in the rock cutting fluorescence images and obtaining the area and brightness of the fluorescent regions; determining the hydrocarbon abundance corresponding to the rock cutting sample based on the area and brightness of the fluorescent regions; identifying the geometric features of the imaging regions of each rock cutting particle in the rock cutting images and determining the porosity of the rock cutting sample based on the geometric features; and determining the formation oiliness corresponding to the rock cutting sample based on at least two of the three parameters: area of ​​the fluorescent regions, hydrocarbon abundance, and porosity.

[0038] In this application, rock cutting images and fluorescence images corresponding to rock cutting samples are directly acquired. Based on these images, the area of ​​the fluorescence region, hydrocarbon abundance, and porosity of the rock cutting samples are directly analyzed from an image recognition perspective to determine parameters characterizing the oil content of the rock cuttings. Compared to data on the radioactivity of rock cuttings, this application directly acquires and analyzes data on the inherent characteristics of the rock cutting samples themselves, resulting in less influence from noise factors. This ensures the accuracy of the parameters characterizing the oil content of the rock cuttings, and thus guarantees the accuracy of determining the formation oil content based on these parameters. This is beneficial for improving the accuracy of oil and gas exploration and reducing the cost of oil and gas extraction.

[0039] This application also provides a device, equipment, and computer-readable storage medium for evaluating the properties of fluids in rock cuttings formations, which have the aforementioned beneficial effects. Attached Figure Description

[0040] To more clearly illustrate the technical solutions of 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.

[0041] Figure 1 A schematic flowchart illustrating the method for evaluating the fluid properties of cuttings formations provided in this application embodiment;

[0042] Figure 2 A schematic diagram of the formation oiliness interpretation chart corresponding to hydrocarbon abundance and porosity provided in the embodiments of this application;

[0043] Figure 3 A schematic diagram of the formation oiliness interpretation chart corresponding to the fluorescent region area and porosity provided in the embodiments of this application;

[0044] Figure 4 A schematic diagram of the formation oiliness interpretation chart corresponding to the area of ​​the fluorescent region and the hydrocarbon abundance provided in the embodiments of this application;

[0045] Figure 5 This is a structural block diagram of the rock debris formation fluid property evaluation device provided in an embodiment of the present invention. Detailed Implementation

[0046] Currently, radiometric analysis of rock cuttings to determine their oil content primarily involves irradiating the rock cutting samples with X-rays or other light sources. The fluid properties within the rock cuttings are then assessed by detecting the excitation light generated by the excited elements, mainly indicating oil content. This helps determine whether the rock cutting formation belongs to different oil-bearing layers, such as oil-bearing, poor-oil-bearing, water-bearing, or dry layers. However, in practical applications, the spectral data obtained from collecting and detecting the excitation light often contains significant noise. Filtering out this noise also removes much useful information, leading to inaccurate results in assessing formation oil content based on this spectral data.

[0047] However, when using ultrasonic methods to analyze the oil content of rock cuttings, the results are inaccurate because the formation rock cuttings are too complex and there are many factors that affect the sound wave reflection.

[0048] Therefore, this application provides a technical solution for analyzing the accuracy of oil content in cuttings formations.

[0049] To enable those skilled in the art to better understand the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] like Figure 1 As shown, Figure 1 This is a flowchart illustrating the method for evaluating the properties of rock cuttings formation fluids provided in this application embodiment. The method may include:

[0051] S11: Collect images of rock cuttings under ultraviolet light and under white light.

[0052] During formation oil exploration, drill bits can be inserted into different formation depths to obtain drilling cuttings at varying depths; these cuttings are known as cuttings samples. Under ultraviolet light, these cuttings samples exhibit varying brightness and color of fluorescence based on their internal carbon content. Higher carbon content results in brighter fluorescence, indicating a higher oil (or natural gas) content in the cuttings. Therefore, the fluorescent areas displayed by cuttings samples under ultraviolet light, to some extent, reveal the oil content within the cuttings.

[0053] For each formation depth, multiple sampling points can be taken at different locations. The oil content analysis results of the rock cuttings samples obtained from these multiple samplings can be combined to obtain the oil content analysis result corresponding to that formation depth. Similarly, at the same sampling point, a corresponding rock cuttings sample can be obtained from multiple formations at different depths. By performing oil content analysis on rock cuttings samples from different locations and depths, the oil content information of the formations in the three-dimensional subsurface space can be obtained.

[0054] In addition, rock fragment samples are composed of a large number of fine particles. In order to obtain clearer rock fragment images and rock fragment fluorescence images, rock fragment images and rock fragment fluorescence images can be acquired separately through a microscope during actual image acquisition.

[0055] S12: Identify the fluorescent regions in the rock debris fluorescence image and obtain the area and brightness of the fluorescent regions.

[0056] Generally, the fluorescent regions in the fluorescence images of rock cuttings samples containing oil and gas will appear in colors such as bright yellow, yellow, yellowish-green, and dark green. When identifying fluorescent regions in rock cutting fluorescence images, the color of each pixel in the image can be determined based on its R, G, and B values. Then, based on the ranges of R, G, and B values ​​corresponding to bright yellow, yellow, yellowish-green, and dark green, respectively, the pixels in the fluorescent regions of the rock cutting fluorescence image can be segmented, thus achieving the segmentation of the fluorescent regions.

[0057] By segmenting the fluorescent regions in the rock debris fluorescence image and summing the pixel areas of each fluorescent region in the same rock debris fluorescence image, the area of ​​the fluorescent region can be determined.

[0058] As mentioned earlier, the higher the oil density in rock cuttings samples, the higher the fluorescence intensity, and the area of ​​the fluorescent region reflects the oil content of the rock cuttings to a certain extent. Therefore, the area of ​​the fluorescent region is also an important parameter reflecting the oil content of rock cuttings.

[0059] Of course, in practical applications, the percentage of the fluorescent region area in the rock cuttings fluorescence image to the total image area can also be used instead of the fluorescent region area as a parameter to characterize the oil content.

[0060] It should be noted that the oil and gas content inside rock fragment samples is not uniformly distributed. Therefore, in the fluorescence image of rock fragments, only part of the imaging area of ​​each rock fragment may be a fluorescent area, while the rest may appear as a darker area. In other words, for rock fragment samples, the fluorescent area is not the same as the imaging area of ​​the rock fragment particles. Furthermore, in the same rock fragment fluorescence image, there are obviously multiple fluorescent areas that are discretely distributed, and the fluorescence brightness of each pixel in each fluorescent area is different.

[0061] In one optional embodiment of this application, the maximum fluorescence brightness value corresponding to the pixel with the highest fluorescence brightness in each fluorescence region can be determined first, and then the maximum fluorescence brightness value corresponding to each fluorescence region in the rock debris fluorescence image can be averaged. The result of the average calculation can be used as the fluorescence brightness corresponding to the rock debris fluorescence image.

[0062] Understandably, in practical applications, the method for determining the fluorescence intensity corresponding to a rock cutting fluorescence image is not limited to this one. For example, the average fluorescence intensity of each pixel in the same fluorescent region can be used as the fluorescence intensity value of that region; then, based on the size of each fluorescent region's area relative to the total fluorescent region, the fluorescence intensity values ​​are weighted and summed to obtain the fluorescence intensity corresponding to the rock cutting fluorescence image.

[0063] Of course, in practical applications, other methods can also be used to determine the fluorescence brightness corresponding to the rock cutting fluorescence image, as long as they can characterize the overall fluorescence brightness of the rock cutting fluorescence image.

[0064] S13: Determine the hydrocarbon abundance of the rock cutting sample based on the area of ​​the fluorescent region and the fluorescence intensity.

[0065] In actual formation oil exploration, the hydrocarbon content in rock cuttings samples is an important indicator for determining crude oil content. In rock cuttings fluorescence images, the area of ​​the fluorescent region can be regarded as the hydrocarbon-bearing area, and different fluorescence intensities correspond to different hydrocarbon concentrations. Therefore, the hydrocarbon abundance can be determined based on the area and intensity of the fluorescent region in the rock cuttings fluorescence image. It can be understood that the hydrocarbon abundance in this embodiment is a parameter characterizing the amount of hydrocarbons.

[0066] In an optional embodiment of this application, the hydrocarbon abundance, the area of ​​the fluorescent region, and the fluorescence intensity satisfy the hydrocarbon abundance formula. ;in, Hydrocarbon abundance; The area of ​​the fluorescent region; Fluorescence brightness; It is the first constant coefficient; It is the second constant coefficient.

[0067] Therefore, when determining the hydrocarbon abundance in practice, it can be calculated based on the above hydrocarbon abundance formula.

[0068] It should be noted that for the first constant coefficient Second constant coefficient It can be determined based on statistical principles using a large amount of historical rock cuttings sample data. For example, first obtain the area and brightness of the fluorescent region corresponding to the historical rock cuttings sample, and then determine the constant coefficient in the relationship between the area and brightness of the fluorescent region and the abundance of hydrocarbons based on the actual mining of the stratum where the rock cuttings sample is located.

[0069] Secondly, in practical applications, hydrocarbon abundance is not limited to being determined by the aforementioned formula. For example, a neural network can be trained based on a large number of historical rock cutting samples labeled with hydrocarbon abundance, corresponding to rock cutting fluorescence images or the area and brightness of fluorescent regions within those images. This can ultimately determine a neural network model that establishes the correspondence between rock cutting fluorescence images (or the area and brightness of fluorescent regions within those images) and hydrocarbon abundance. Subsequently, when evaluating the oil content of rock cutting formations, this neural network model can be directly used to determine hydrocarbon abundance.

[0070] Of course, in practical applications, other methods can be used to obtain the hydrocarbon abundance of rock cuttings samples, which will not be listed in this application.

[0071] S14: Identify the geometric features of the imaging regions of each rock cutting particle in the rock cutting image, and determine the porosity of the rock cutting sample based on the geometric features.

[0072] Crude oil stored in formation rock cuttings is stored in the pores of the rock cuttings. Therefore, one of the necessary conditions for rock cutting samples to store a large amount of crude oil is that there are enough pores. Thus, the porosity of rock cutting samples is used as the basis for evaluating the oil content of rock cutting samples.

[0073] When determining the porosity of rock cuttings samples, the principle that the closer the rock cutting particles are to being spherical, the higher the porosity can be applied. First, determine the roundness of the rock cutting particles in the rock cutting image, and then determine the porosity based on the roundness. The matrix process can be as follows:

[0074] Geometric features of individual rock fragments in rock fragment images are identified using image recognition technology;

[0075] Based on geometric characteristics, the proportion of rock debris particles in the rock debris image whose geometric shape and circular shape approximation reach a preset approximation degree is determined as the roundness of the rock debris particles.

[0076] Based on the predetermined correspondence between the roundness of rock cutting particles and the porosity of rock cutting particles, the porosity of the rock cutting sample is determined.

[0077] Generally, based on conventional image recognition principles, the imaging region of each rock fragment can be identified and segmented based on the grayscale value of each pixel, thereby determining the geometric features of each rock fragment. Of course, to improve the accuracy of geometric feature recognition of rock fragments, in an optional embodiment of this application, the imaging region label of each rock fragment can be manually assigned based on a large number of historical rock fragment images. Then, computer learning can be performed to obtain a recognition model capable of identifying the geometric features of rock fragments in the rock fragment images. Subsequently, after acquiring rock fragment images corresponding to rock fragment samples, the imaging region of each rock fragment, i.e., the geometric features of each rock fragment in the rock fragment image, can be directly identified and determined using this recognition model.

[0078] Geometric texture recognition technology in image recognition can also be used to identify the geometric features of each rock fragment, which will not be listed in detail in this embodiment.

[0079] After segmenting and determining the imaging region of each rock fragment in the rock fragment image, that is, obtaining the geometric features of each rock fragment, the boundary lines of each rock fragment can be smoothed to minimize the jagged burrs on the boundary lines of the rock fragments. Then, based on the gradient of the boundary line change of each rock fragment, the similarity of each rock fragment to a near circle can be determined.

[0080] Alternatively, a circular coverage area can be found and its size adjusted. The final size of the circular coverage area is determined when the overlap between the circular coverage area and the rock fragments is the highest. This highest overlap can be achieved when the total area of ​​the circular coverage area is closest to the imaging area of ​​the rock fragments, and the area of ​​the rock fragments covered by the circular coverage area is the largest. For example, an overlap parameter M = a*A + b*B can be set, where a and b are two weighting coefficients, A is the ratio of the total area of ​​the circular coverage area to the imaging area of ​​the rock fragments, and B is the ratio of the imaging area of ​​the rock fragments covered by the circular coverage area to the imaging area of ​​the rock fragments. Of course, to avoid one of A or B having an excessively large weight while the other has an excessively small weight, leading to inaccurate overlap parameters, a range of values ​​for A and B can be set as a constraint to ensure that the two parameters A and B are in a balanced state when the maximum overlap parameter is determined.

[0081] After determining the circular overlay corresponding to the maximum overlap parameter, the similarity between the circular overlay and the corresponding rock fragment geometry can be determined. For example, this similarity can be set as N=1 / (c*C+d*D); where c and d are two weighting coefficients, C is the proportion of pixel regions in the circular overlay that do not overlap with the rock fragment, and D is the proportion of regions in the rock fragment imaging area not covered by the circular overlay. Obviously, the higher the final similarity, the closer the rock fragment is to a circle. Therefore, a similarity threshold can be set. When the similarity reaches this threshold, the rock fragment is considered to be approximately circular.

[0082] Based on determining the degree to which each rock cutting particle is nearly spherical, the proportion of nearly spherical rock cutting particles in the entire rock cutting image is then determined, which is the roundness of the rock cutting particles in the rock cutting image. The greater the roundness, the higher the porosity of the rock cutting sample. Generally, there is a positive proportional relationship between roundness and porosity of rock cutting samples. This specific proportional relationship can be determined in advance based on historical rock cutting images combined with the actual mining results of rock cuttings from the corresponding strata. This will not be elaborated on in detail in this application.

[0083] S15: Determine the formation oiliness of the rock cutting sample based on at least two of the following three parameters: fluorescence area, hydrocarbon abundance, and porosity.

[0084] As mentioned earlier, the oil content, or oiliness, of formation rock cuttings is reflected in factors such as the area of ​​the fluorescent region, hydrocarbon abundance, and porosity. However, relying solely on a single characteristic inevitably leads to inaccurate analytical results.

[0085] Therefore, in practical applications, formation oil content can be analyzed based on at least two of the above three characteristics.

[0086] In one optional embodiment of this application, it may further include:

[0087] Based on historical fluorescence region area, historical hydrocarbon abundance, and historical porosity, an interpretation chart characterizing the relationship between at least two of the parameters (fluorescence region area, hydrocarbon abundance, and porosity) and formation oiliness is pre-determined.

[0088] Based on at least two of the three parameters—fluorescent area, hydrocarbon abundance, and porosity—corresponding rock cutting samples, the formation oil content of each layer of rock cutting samples is determined in the interpretation chart.

[0089] refer to Figure 2 , Figure 3 as well as Figure 4 , Figure 2 A schematic diagram of the formation oiliness interpretation chart corresponding to hydrocarbon abundance and porosity provided in the embodiments of this application; Figure 3 A schematic diagram of the formation oiliness interpretation chart corresponding to the fluorescent region area and porosity provided in the embodiments of this application; Figure 4 This is a schematic diagram of the formation oiliness interpretation chart corresponding to the area of ​​the fluorescent region and the hydrocarbon abundance provided in the embodiments of this application.

[0090] It should be noted that, Figures 2 to 4 This can be achieved by pre-collecting fluorescence images and images of rock cuttings from historically sampled rock cuttings samples, obtaining corresponding historical fluorescence images and historical rock cutting images. Following a similar approach to the embodiments described above, the historical fluorescence region area, historical hydrocarbon abundance, and historical porosity corresponding to the historical rock cutting images are determined. The oil content of the rock cuttings, as determined by actual mining of the historical rock cutting samples, is used as a label. This allows for the creation of a two-dimensional coordinate map of discrete points with hydrocarbon abundance and porosity as the horizontal and vertical axes, based on the historical fluorescence region area, historical hydrocarbon abundance, and historical porosity. Based on the oil content labels, the oil content regions to which each discrete point belongs are divided, resulting in a schematic diagram of the formation oil content interpretation chart corresponding to hydrocarbon abundance and porosity. Of course, to ensure the accuracy of oil content region division, the oil content regions can be divided based on historical data discrete points (discrete points determined by historical fluorescence region area, historical hydrocarbon abundance, and historical porosity) with oil content labels using a clustering algorithm; alternatively, the division can be achieved based on neural network training. This application does not impose specific limitations on this approach.

[0091] Similarly, the same method can be used to obtain formation oiliness interpretation charts corresponding to the area of ​​fluorescent regions and porosity, as well as formation oiliness interpretation charts corresponding to the area of ​​fluorescent regions and hydrocarbon abundance.

[0092] In practical applications, the oily region to which the current cuttings sample belongs can be determined based on any one of the three interpretation charts mentioned above. Alternatively, one analysis result can be determined based on each of the three interpretation charts, and the final formation oiliness result can be determined by combining the analysis results of the three oily regions to which the cuttings sample belongs. For example, based on... Figure 2 and Figure 4 The formation identified in the study was a poor oil-bearing layer, while Figure 3 The formation was determined to be a dry oil layer, which clearly indicates that it is a poor oil layer with a tendency towards dryness.

[0093] In addition, three-dimensional spatial discrete points can be plotted based on historical fluorescence area, historical hydrocarbon abundance, and historical porosity, with coordinates in three different directions: fluorescence area, hydrocarbon abundance, and porosity. A three-dimensional interpretation map can then be obtained based on the oiliness label. Finally, when determining the formation oiliness of the rock cutting sample, its spatial position in the three-dimensional interpretation map can be determined directly based on the three parameters of fluorescence area, hydrocarbon abundance, and porosity of the rock cutting sample to determine the formation oiliness.

[0094] Furthermore, it is understood that the above-mentioned explanatory chart is merely a specific representation of the correspondence between the fluorescent area, hydrocarbon abundance, porosity, and oiliness of the rock cuttings. In practical applications, it is not necessary to use the explanatory chart to represent this correspondence. It can also be represented by lists, operational formulas, or even recognition models obtained through machine training and learning. These methods are not listed in detail in this embodiment.

[0095] As mentioned earlier, in practical applications, the oil content analysis of rock cuttings from the same location requires the extraction of rock cuttings samples corresponding to different formation depths. Therefore, in practical applications, once the oil content information of rock cuttings samples at different depths corresponding to the same sampling point is determined, the formation oil content information that varies with formation depth at that sampling point can be determined. This is beneficial for researchers to predict the oil content of deeper formations based on the formation oil content information that varies with formation depth, thereby obtaining more comprehensive information on formation fluid properties.

[0096] Currently, conventional techniques for analyzing the oil-bearing properties of formation cuttings based on data such as the radioactivity of well logging cuttings and the characteristics of acoustic wave propagation rely on the waveform data generated by the interference of the cuttings sample during the transmission of acoustic or optical waves. Information about the oil content in the cuttings is then indirectly obtained based on this waveform data. However, in actual exploration, it has been found that there are too many interference factors during the transmission of acoustic and optical waves, resulting in excessively noisy waveform data. Obviously, the accuracy of oil content assessment based on such waveform data is relatively low.

[0097] Therefore, this application directly collects fluorescence images and images of rock cuttings from rock cutting samples, which means analyzing the characteristics of the rock cutting samples themselves. This is less affected by environmental and other factors, and the results of the formation rock cutting oiliness analysis obtained from this analysis are more accurate, thus ensuring the accuracy of the assessment of formation fluid properties.

[0098] In summary, this application obtains fluorescence images and rock fragment images under ultraviolet and white light, respectively. Based on the analysis of these images, three different parameters reflecting the oil-bearing characteristics of the rock fragment samples are determined: fluorescence area, hydrocarbon abundance, and porosity. Finally, based on these three parameters, the formation oiliness of the rock fragment samples is determined, ensuring the accuracy of formation oiliness analysis and helping to save extraction costs in actual oil and gas extraction processes.

[0099] The following describes the rock cuttings formation fluid property evaluation device provided in the embodiments of the present invention. The rock cuttings formation fluid property evaluation device described below can be referred to in correspondence with the rock cuttings formation fluid property evaluation method described above.

[0100] Figure 5 This is a structural block diagram of the rock cuttings formation fluid property evaluation device provided in an embodiment of the present invention, with reference to... Figure 5 The device for evaluating the fluid properties of rock debris formations may include:

[0101] Image acquisition module 100 is used to acquire rock fragment fluorescence images under ultraviolet light irradiation and rock fragment images under white light irradiation.

[0102] The fluorescence recognition module 200 is used to identify the fluorescent regions in the rock cutting fluorescence image and obtain the area and brightness of the fluorescent regions.

[0103] The first calculation module 300 is used to determine the hydrocarbon abundance of the rock cutting sample based on the area of ​​the fluorescent region and the fluorescence brightness.

[0104] The second calculation module 400 is used to identify the geometric features of the imaging area of ​​each rock cutting particle in the rock cutting image, and to determine the porosity of the rock cutting sample based on the geometric features.

[0105] Oiliness analysis module 500 is used to determine the formation oiliness of the cuttings sample based on at least two of the following three parameters: the area of ​​the fluorescent region, the hydrocarbon abundance, and the porosity.

[0106] In an optional embodiment of this application, the fluorescence recognition module 200 is used to segment and identify the fluorescence region corresponding to each rock fragment in the rock fragment fluorescence image using image recognition technology; to perform an average calculation on the maximum fluorescence brightness value of each of the fluorescence regions, and to use the average calculation result as the fluorescence brightness; and to use the sum of the areas of each of the fluorescence regions as the area of ​​the fluorescence region.

[0107] In an optional embodiment of this application, the first calculation module 300 is used to calculate the hydrocarbon abundance formula. Determine the hydrocarbon abundance; wherein, The hydrocarbon abundance; The area of ​​the fluorescent region; The fluorescence brightness; It is the first constant coefficient; It is the second constant coefficient.

[0108] In an optional embodiment of this application, the second calculation module 400 is used to determine, based on the geometric features, the proportion of rock fragments in the rock fragment image whose geometric shape and circular shape approximation reaches a preset approximation degree as the roundness of the rock fragments; and to determine the porosity corresponding to the rock fragment sample based on a predetermined correspondence between the roundness of the rock fragments and the porosity of the rock fragments.

[0109] In an optional embodiment of this application, the oiliness analysis module 500 is used to pre-determine an interpretation chart characterizing the correspondence between at least two of the parameters of fluorescent region area, hydrocarbon abundance, and porosity and formation oiliness based on historical fluorescence region area, historical hydrocarbon abundance, and historical porosity; and to determine the formation oiliness corresponding to each layer of the rock cuttings sample on the interpretation chart based on at least two of the three parameters of fluorescent region area, hydrocarbon abundance, and porosity corresponding to the rock cuttings sample.

[0110] In an optional embodiment of this application, the oiliness analysis module 500 is used to output information on the formation oiliness of each layer of rock cuttings samples corresponding to different formation depths as the formation depth changes.

[0111] In one optional embodiment of this application, the image acquisition module 100 is used to acquire the fluorescence image of the rock cuttings and the rock cuttings image using a microscope.

[0112] The rock cuttings formation fluid property evaluation device of this embodiment is used to implement the aforementioned rock cuttings formation fluid property evaluation method. Therefore, the specific implementation of the rock cuttings formation fluid property evaluation device can be found in the embodiment section of the rock cuttings formation fluid property evaluation method above. The specific implementation can be referred to the description of the corresponding embodiment, and will not be repeated here.

[0113] This application also provides an embodiment of a cuttings formation fluid property evaluation device, which may include:

[0114] Memory, used to store computer programs;

[0115] A processor for executing the computer program to implement the steps of the method for evaluating the fluid properties of cuttings formations as described in any of the preceding claims.

[0116] The steps of the rock cuttings formation fluid property evaluation method executed by the processor in the rock cuttings formation fluid property evaluation device of this application may include:

[0117] Fluorescence images of rock cuttings under ultraviolet light irradiation and images of rock cuttings under white light irradiation were collected.

[0118] Identify the fluorescent regions in the rock debris fluorescence image to obtain the area and brightness of the fluorescent regions;

[0119] The hydrocarbon abundance of the rock fragment sample is determined based on the area of ​​the fluorescent region and the fluorescence intensity.

[0120] Identify the geometric features of the imaging regions of each rock fragment in the rock fragment image, and determine the porosity of the rock fragment sample based on the geometric features;

[0121] The formation oil content of the rock cuttings sample is determined based on at least two of the following three parameters: the area of ​​the fluorescent region, the hydrocarbon abundance, and the porosity.

[0122] The processor in this application determines the fluid properties of oil-bearing formations corresponding to rock cutting samples based on rock cutting fluorescence images and rock cutting image analysis. Compared with conventional techniques that analyze formation oil-bearing properties based on information such as radioactivity of rock cutting samples, this method helps improve the accuracy of analysis and prediction of oil content in formation rock cuttings, and provides more accurate data for oil and gas extraction.

[0123] This application also provides an embodiment of a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method for evaluating the fluid properties of cuttings formations as described in any of the preceding claims.

[0124] The computer-readable storage medium may include random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, register, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0125] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that the elements inherent in a process, method, article, or apparatus that includes a list of elements are included. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. Additionally, portions of the technical solutions provided in the embodiments of this application that are consistent with the implementation principles of corresponding technical solutions in the prior art have not been described in detail to avoid excessive elaboration.

[0126] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. It should be noted that those skilled in the art can make several improvements and modifications to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

Claims

1. A method for evaluating the properties of fluids in rock cuttings formations, characterized in that, include: Images of rock cuttings under ultraviolet light and under white light were collected. Identify the fluorescent regions in the rock debris fluorescence image to obtain the area and brightness of the fluorescent regions; The hydrocarbon abundance of the rock fragment sample is determined based on the area of ​​the fluorescent region and the fluorescence intensity. Identify the geometric features of the imaging regions of each rock fragment in the rock fragment image, and determine the porosity of the rock fragment sample based on the geometric features; The formation oil content of the rock cutting sample is determined based on a pre-determined identification model representing the correspondence between the three parameters: the area of ​​the fluorescent region, the hydrocarbon abundance, and the porosity, or based on a pre-determined interpretation chart representing the correspondence between the hydrocarbon abundance and the porosity; wherein the identification model is obtained based on machine training and learning. The hydrocarbon abundance of the rock fragment sample is determined based on the area of ​​the fluorescent region and the fluorescence intensity, including: According to the hydrocarbon abundance formula Determine the hydrocarbon abundance; wherein, The hydrocarbon abundance; The area of ​​the fluorescent region; The fluorescence brightness; It is the first constant coefficient; It is the second constant coefficient; Determining the porosity of the rock cuttings sample based on the geometric features includes: Based on the geometric features, the proportion of rock debris particles in the rock debris image whose geometric shape and circular shape approximation reach a preset approximation degree is determined as the roundness of the rock debris particles; The porosity of the rock cutting sample is determined based on the pre-determined correspondence between the roundness of rock cutting particles and the porosity of rock cutting particles.

2. The method for evaluating the fluid properties of rock cuttings formations as described in claim 1, characterized in that, Identifying fluorescent regions in the rock debris fluorescence image and obtaining the area and intensity of the fluorescent regions includes: Using image recognition technology, the fluorescent region corresponding to each rock fragment in the rock fragment fluorescence image is segmented and identified; The maximum fluorescence brightness value of each of the fluorescent regions is averaged, and the average value is used as the fluorescence brightness. The sum of the areas of all the fluorescent regions is the area of ​​the fluorescent region.

3. The method for evaluating the fluid properties of rock cuttings formations as described in claim 1, characterized in that, The identification model and the interpretation chart are pre-determined based on the area of ​​historical fluorescent regions, historical hydrocarbon abundance, and historical porosity.

4. The method for evaluating the fluid properties of rock cuttings formations as described in claim 1, characterized in that, After determining the oil content of the formation, the process also includes: Output information on the formation oil content of rock cuttings samples at different formation depths as the formation depth varies.

5. The method for evaluating the fluid properties of rock cuttings formations as described in claim 1, characterized in that, Images of rock cuttings under ultraviolet light and under white light were collected, including: The fluorescence image of the rock debris and the image of the rock debris were acquired using a microscope.

6. A device for evaluating the properties of fluids in rock cuttings formations, characterized in that, include: The image acquisition module is used to acquire fluorescence images of rock cuttings under ultraviolet light and images of rock cuttings under white light. The fluorescence recognition module is used to identify the fluorescent regions in the rock cutting fluorescence image and obtain the area and brightness of the fluorescent regions. The first calculation module is used to determine the hydrocarbon abundance of the rock cutting sample based on the area of ​​the fluorescent region and the fluorescence brightness. The second calculation module is used to identify the geometric features of the imaging area of ​​each rock cutting particle in the rock cutting image, and to determine the porosity of the rock cutting sample based on the geometric features. The oil content analysis module is used to determine the formation oil content of the cuttings sample based on a pre-determined identification model characterizing the correspondence between the three parameters: the area of ​​the fluorescent region, the hydrocarbon abundance, and the porosity, or based on a pre-determined interpretation chart characterizing the correspondence between the hydrocarbon abundance and the porosity; wherein the identification model is obtained based on machine training and learning. The first calculation module is used to calculate the hydrocarbon abundance formula. Determine the hydrocarbon abundance; wherein, The hydrocarbon abundance; The area of ​​the fluorescent region; The fluorescence brightness; It is the first constant coefficient; It is the second constant coefficient; The second calculation module is used to determine the proportion of rock debris particles in the rock debris image whose geometric shape and circular shape approximation reaches a preset approximation degree based on the geometric features, as the roundness of the rock debris particles; and to determine the porosity of the rock debris sample based on the pre-determined correspondence between the roundness of rock debris particles and the porosity of rock debris particles.

7. A device for evaluating the properties of fluids in rock cuttings formations, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the method for evaluating the fluid properties of rock cutting formations as described in any one of claims 1 to 5 when executing the computer program.

8. 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 steps of the method for evaluating the fluid properties of rock cuttings formations as described in any one of claims 1 to 5.

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