A method and device for determining a mixed source oil

Abstract

This specification provides a method and apparatus for determining mixed-source crude oil. The method involves acquiring a reference end-member sample and a crude oil sample to be tested from a target area; performing component analysis on both the reference end-member sample and the crude oil sample to determine the first component characteristic parameters corresponding to the reference end-member sample and the second component characteristic parameters corresponding to the crude oil sample; based on the first component characteristic parameters, selecting mutually exclusive feature pairs under geological conditions, and constructing a geologically mutually exclusive feature set based on these pairs; comparing the second component characteristic parameters with the geologically mutually exclusive feature set to determine whether mutually exclusive feature pairs exist in the crude oil sample to be tested, and determining whether the crude oil sample is mixed-source crude oil based on the determination result. This effectively solves the technical problem of misclassifying mixed-source crude oil as single-source crude oil due to the index averaging effect in existing technologies.

Description

Technical Field

[0001] This manual belongs to the field of oil and gas geological exploration technology, and in particular relates to a method and apparatus for determining mixed-source oil. Background Technology

[0002] Oil source correlation is a core technical means in petroleum geological exploration to identify the source of oil and gas and determine the main oil-generating strata. However, existing technologies mainly match based on the similarity of indicators, which can easily lead to misjudgment as transitional crude oil from a single source due to the average effect of indicators, making it difficult to achieve accurate qualitative identification of different genetic components.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This specification provides a method and apparatus for determining mixed-source oil, which solves the technical problem that existing technologies misclassify multi-source mixed-source oil as single-source transition phase crude oil due to the index averaging effect, making it difficult to accurately identify complex genetic components.

[0005] This specification provides a method for determining mixed-source oil, including: Acquire reference end-member samples and crude oil samples to be tested in the target area; The reference end-member sample and the crude oil sample to be tested are subjected to component detection to determine the first component characteristic parameter corresponding to the reference end-member sample and the second component characteristic parameter corresponding to the crude oil sample to be tested. Based on the first component characteristic parameters, mutually exclusive feature pairs under geological genesis conditions are selected, and a geological genesis mutually exclusive feature set is constructed based on the mutually exclusive feature pairs. The second component characteristic parameters are compared with the geologically exclusive feature set to determine whether the mutually exclusive feature pair exists in the crude oil sample to be tested, and whether the crude oil sample to be tested is a mixed source oil is determined based on the judgment result.

[0006] In one embodiment, the method further includes: If the crude oil sample to be tested is determined to be a mixed-source oil, a multi-feature origin chart is established using the feature pairs as coordinate axes. The mixing origin of the mixed source oil is determined based on the first component characteristic parameters, the second component characteristic parameters, and the multi-feature origin chart.

[0007] In one embodiment, determining the mixing origin of the mixed-source oil based on the first component characteristic parameters, the second component characteristic parameters, and the multi-feature genetic map includes: The first component characteristic parameters and the second component characteristic parameters are calibrated in the multi-feature origin chart to determine the end-member calibration point of the reference end-member sample and the test calibration point of the crude oil sample to be tested. Based on the distribution position of the calibration point to be tested relative to the end-member calibration point, the linear distribution trend of the calibration point to be tested is determined, and based on the linear distribution trend, the mixing line of the crude oil sample to be tested is determined. By utilizing the positional relationship of the calibration points to be tested on the mixing line, the reference end-member samples corresponding to both ends of the mixing line are identified as the genetic components of the mixed source oil; The contribution ratio of each of the genetic components is determined based on the ratio of the geometric distance between the calibration point to be tested and the endmember calibration point on the mixing line. The genetic components and contribution ratios of the genetic components of the mixed-source oil are determined as the mixed origin of the mixed-source oil.

[0008] In one embodiment, the mutually exclusive feature pairs include: redox environment feature pairs, biological origin feature pairs, and isotope fractionation feature pairs; The redox environment characteristic pair is a combination of indicators, namely the plutophyte ratio (Pr / Ph) characterizing the oxidative environment and the gammacerane index characterizing the reductive salinization environment, used to establish a logical criterion for determining the incompatibility of sedimentary environments. The biogenic characteristics are compared to the olane index, which characterizes input from terrestrial higher plants, and the C, which characterizes algal origin. 30 4-Methylsterane and C 29 A combination of indicators for regular sterane ratios is used to identify causal conflicts caused by diversity in student input. The isotopic fractionation characteristic is an index of the isotopic fractionation difference between saturated hydrocarbon carbon isotopes and aromatic hydrocarbon carbon isotopes, used for in-depth verification through deviations from the genetic evolution benchmark.

[0009] In one embodiment, comparing the second component characteristic parameters with the geologically exclusive feature set to determine whether the mutually exclusive feature pair exists in the crude oil sample to be tested, and determining whether the crude oil sample to be tested is a mixed-source oil based on the determination result, includes: Extract the target parameter values ​​corresponding to each feature pair from the second component feature parameters; The target parameter values ​​are compared with the preset mutual exclusion threshold range of the geological genesis mutual exclusion feature set to determine the logical state value of the crude oil sample to be tested on each feature pair. The logical state values ​​corresponding to each of the aforementioned feature pairs are detected. If at least one set of the aforementioned logical state values ​​that characterize mutually exclusive geological genesis attributes are detected in the crude oil sample to be tested, it is determined that the crude oil sample to be tested contains the aforementioned mutually exclusive feature pairs. Based on the detection results of the mutually exclusive feature pairs, the crude oil sample to be tested is determined to be a mixed-source oil.

[0010] In one embodiment, when the crude oil sample to be tested is determined to be a non-mixed-source oil, the method further includes: Calculate the causal correlation evaluation parameters between the characteristic parameters of the second component and the characteristic parameters of the first component; Based on the genetic correlation evaluation parameters, a target reference end-member sample with genetic consistency with the component characteristics of the crude oil sample to be tested is determined. The origin of the target reference end-member sample is determined as the single origin of the crude oil sample to be tested.

[0011] In one embodiment, the step of performing component detection on the reference end-member sample and the crude oil sample to be tested, respectively, to determine the first component characteristic parameter corresponding to the reference end-member sample and the second component characteristic parameter corresponding to the crude oil sample to be tested, includes: Gas chromatography-mass spectrometry and stable carbon isotope detection were performed on the reference end-member sample and the crude oil sample to be tested, respectively, to obtain the corresponding biomarker fingerprint data and isotope composition data. Extract the peak area of ​​each biomarker in the biomarker fingerprint data and calculate the corresponding biomarker ratio index; and determine the stable carbon isotope values ​​in the isotopic composition data; Based on the bio-standard ratio index and the stable carbon isotope value, the first component characteristic parameters and the second component characteristic parameters are constructed.

[0012] In one embodiment, the method further includes: The genetic components and their contribution ratios are matched with the geological strata information in the target area to determine the genetic contribution weights of different strata source rocks to the crude oil sample to be tested. By comparing the genetic contribution weights of different hydrocarbon source rocks to the crude oil sample under test, the layers that meet the preset threshold are identified as the main hydrocarbon source layers that play a dominant role in hydrocarbon accumulation. Based on the spatial distribution characteristics of the main hydrocarbon source strata, favorable oil and gas exploration areas within the target region are determined.

[0013] This specification provides a device for determining mixed-source oil, comprising: The sample acquisition module is used to acquire reference end-member samples and crude oil samples to be tested in the target area; The parameter determination module is used to perform component detection on the reference end-member sample and the crude oil sample to be tested, respectively, and determine the first component characteristic parameter corresponding to the reference end-member sample and the second component characteristic parameter corresponding to the crude oil sample to be tested. The feature set determination module is used to select mutually exclusive feature pairs under geological genesis conditions based on the feature parameters of the first component, and to construct a geological genesis mutually exclusive feature set based on the mutually exclusive feature pairs. The mixed-source oil determination module is used to compare the second component characteristic parameters with the geologically exclusive feature set, determine whether the mutually exclusive feature pairs exist in the crude oil sample to be tested, and determine whether the crude oil sample to be tested is a mixed-source oil based on the determination result.

[0014] This specification also provides a computer-readable storage medium having computer instructions stored thereon, which, when executed, implement a method for determining mixed-source oil.

[0015] Based on the method for determining mixed-source oil provided in this specification, a reference end-member sample and a crude oil sample to be tested from a target area are obtained; the components of the reference end-member sample and the crude oil sample to be tested are analyzed to determine the first component characteristic parameter corresponding to the reference end-member sample and the second component characteristic parameter corresponding to the crude oil sample to be tested; based on the first component characteristic parameter, mutually exclusive feature pairs under geological genesis are selected, and a geologically mutually exclusive feature set is constructed based on the mutually exclusive feature pairs; the second component characteristic parameter is compared with the geologically mutually exclusive feature set to determine whether the mutually exclusive feature pairs exist in the crude oil sample to be tested, and whether the crude oil sample to be tested is a mixed-source oil is determined based on the determination result. In this way, by using reference end-member samples to screen out mutually exclusive feature pairs under geological conditions and constructing a geologically mutually exclusive feature set, the second component feature parameters of the crude oil sample to be tested are compared with this feature set. By detecting whether the mutually exclusive feature pairs exist in the crude oil sample to be tested, it is possible to accurately determine whether the crude oil sample to be tested is a mixed-origin oil. This method uses the mutual exclusion logic at the genetic level to overcome the misleading effect of single parameter values, effectively solving the technical problem in the prior art where parameters appear as medium values ​​due to mixing, and thus misjudging it as a single-origin environment. This significantly improves the accuracy of identifying mixed-origin oils with complex genesis. Attached Figure Description

[0016] To more clearly illustrate the embodiments of this specification, the accompanying drawings used in the embodiments will be briefly introduced below. The drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating a method for determining mixed-source oil according to an embodiment of this specification; Figure 2 This is a schematic diagram of the electronic device structure provided in one embodiment of this specification; Figure 3 This is a schematic diagram of the structural composition of a mixed-source oil determination device provided in one embodiment of this specification; Figure 4 This is a schematic diagram of the overall process of a method for determining mixed-source oil, provided in one embodiment of this specification; Figure 5 This is a schematic diagram illustrating the intersection of geochemical parameters of crude oil and source rock in the Qikou Depression, provided as an embodiment of this specification. Detailed Implementation

[0018] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0019] See Figure 1 As shown in the embodiments of this specification, a method for determining mixed-source oil is provided, wherein the method is specifically applied to the server side. In specific implementation, the method may include the following: S101: Obtain the reference end-member sample and the crude oil sample to be tested in the target area; S102: Perform component detection on the reference end-member sample and the crude oil sample to be tested respectively, and determine the first component characteristic parameter corresponding to the reference end-member sample and the second component characteristic parameter corresponding to the crude oil sample to be tested. S103: Based on the first component characteristic parameters, select mutually exclusive feature pairs under geological genesis conditions, and construct a geological genesis mutually exclusive feature set based on the mutually exclusive feature pairs. S104: Compare the second component characteristic parameters with the geologically exclusive feature set to determine whether the mutually exclusive feature pair exists in the crude oil sample to be tested, and determine whether the crude oil sample to be tested is a mixed source oil based on the determination result.

[0020] The aforementioned reference end-member sample can refer to a pristine sample representing a specific, single, and undisturbed genetic source within the target area. It is typically selected from source rock extracts from a specific stratum or crude oil proven to originate from a single source rock formation. In petroleum geological analysis, it is considered the "endpoint" for constructing a hybrid model. Its geochemical characteristics are at the extremes or in a pure state of the genetic spectrum, serving as the physical benchmark for determining whether the sample to be tested has a hybrid origin.

[0021] The aforementioned crude oil sample to be tested can refer to a target crude oil object collected from the target area reservoir whose genetic background is not yet clear and which needs to be qualitatively identified or quantitatively analyzed. This sample is the core input of the evaluation system of this invention. It may contain physical mixed signals from multiple source layers and serves as a physical carrier for identifying "median artifacts" and restoring the true genetic origin.

[0022] The aforementioned component detection refers to the process of extracting and quantitatively determining chemical components such as saturated hydrocarbons, aromatic hydrocarbons, biomarker compounds (such as steranes and terpenes), and stable carbon isotopes in a sample using modern analytical instruments such as gas chromatography (GC), gas chromatography-mass spectrometry (GC-MS), or isotope ratio mass spectrometry (IRMS). This process transforms geological samples into a digital set of geochemical indicators, providing data support for subsequent logical judgments.

[0023] The aforementioned first component characteristic parameters can refer to a set of quantitative geochemical index data extracted from the reference end-member sample after component analysis, which can reflect its specific sedimentary environment, parent material source, or degree of evolution. These parameters characterize the "feature fingerprint" of a single genetic end-member and are the original logical input for constructing a set of mutually exclusive geological genesis features and defining the map coordinate space.

[0024] The aforementioned second component characteristic parameter refers to a set of quantitative geochemical index data extracted from the crude oil sample after component analysis, reflecting its current chemical composition state. By comparing this parameter with mutually exclusive feature sets or genetic maps, it is possible to detect whether incompatible characteristic signals exist in the sample, thereby enabling the derivation from data to genetic conclusions.

[0025] The aforementioned set of mutually exclusive geological genesis features can refer to a set of criteria consisting of two or more geochemical indicators that cannot coexist under a single geological sedimentary environment or genetic condition and are logically mutually exclusive. This set utilizes the "fingerprint paradox" principle to transform geological logic into comparable threshold intervals, used to identify whether there are contradictory features coexisting in the sample under test due to physical mixing.

[0026] The aforementioned mixed-source oil refers to a complex crude oil system formed by the physical mixing of hydrocarbons from two or more source rocks with different genetic backgrounds (such as different strata, different sedimentary facies zones, or different evolutionary stages) during migration or accumulation. The conventional parameters of such crude oils often exhibit an "averaged" characteristic, which is the focus of this invention for differentiation and disassembly through logical paradox identification.

[0027] In some embodiments, the step of selecting mutually exclusive feature pairs under geological genetic conditions based on the first component characteristic parameters, and constructing a geologically mutually exclusive feature set based on the mutually exclusive feature pairs, may specifically include: Extract characteristic indicators representing different geological environment attributes from each of the aforementioned reference end-member samples; Based on the detection values ​​of each of the reference end-member samples, determine the mutual exclusion threshold range corresponding to each of the feature indicators; Identify at least two of the aforementioned feature indices that are logically conflicting and incompatible under a single geological genetic background to obtain the mutually exclusive feature pair; The geological genesis mutually exclusive feature set is constructed by combining each of the feature pairs and their corresponding mutually exclusive threshold intervals.

[0028] By extracting characteristic indicators representing extreme geological environments and defining their mutually exclusive threshold ranges, a logical identification criterion based on causal paradox was established. This criterion can effectively capture contradictory characteristic signals that appear simultaneously in crude oil due to physical mixing from different sources. It fundamentally eliminates the risk of misjudgment when faced with the index averaging effect of traditional similarity matching methods, and greatly improves the scientificity and accuracy of qualitative identification of complex mixed-source oils.

[0029] In some embodiments, the method may further include the following: S1: If the crude oil sample to be tested is determined to be mixed source oil, a multi-feature origin chart is established using the feature pairs as coordinate axes. S2: Determine the mixing origin of the mixed source oil based on the first component characteristic parameters, the second component characteristic parameters, and the multi-feature origin chart.

[0030] Specifically, after determining that the crude oil sample to be tested is a mixed-source oil, the quantitative evaluation stage begins. First, a multi-feature genetic map is established using the previously screened mutually exclusive feature pairs as coordinate axes. In this embodiment, the ratio of pterane to phytane is selected as the abscissa, and the gammacerane index is selected as the ordinate, constructing a two-dimensional planar coordinate system that can reflect the extreme polarity of the depositional environment.

[0031] Subsequently, the component characteristic parameters of each reference end-member sample and the component characteristic parameters of the crude oil sample to be tested are converted into corresponding coordinate points. In the chart, the first reference end-member point, representing a strongly oxidizing freshwater environment, is marked in the lower right of the coordinate system, and the second reference end-member point, representing a strongly reducing brine environment, is marked in the upper left of the coordinate system. At this point, the detection value of the crude oil sample to be tested is projected onto this chart to form a calibration point.

[0032] Next, the genetic components were determined by analyzing the spatial relationships. Observation revealed that the calibration point to be tested accurately fell on the straight line segment connecting the first and second reference end-member points. Based on this geometric topological envelope relationship, it was determined from a genetic logic perspective that the crude oil sample to be tested was formed by the mixing of the formations represented by the two reference end-members, thus clarifying the genetic composition of the mixed-source oil.

[0033] Finally, the contribution ratio of each component is determined using geometric distance ratios. The physical distances from the test calibration point to the two reference end-member points are measured on the chart. According to the principle of linear mixing, the degree to which the test point deviates from one end point is proportional to the contribution of the other end point. By calculating the relative positional proportion of the test point on the mixing line, the mass percentages of the first and second reference end-member components in the mixed oil are obtained, ultimately outputting a complete evaluation conclusion on the mixing genesis.

[0034] By establishing a multi-feature genetic map based on mutually exclusive features, complex chemical composition data is transformed into an intuitive geometric spatial distribution. By utilizing the linear evolution trajectory and geometric distance ratio of the test points in the map, accurate qualitative identification of genetic components of mixed-source oil and quantitative decomposition of contribution ratios are achieved. This effectively solves the technical problem that traditional methods cannot quantitatively evaluate the contribution share of multiple sources, and provides a reliable digital basis for the accurate locking of the main hydrocarbon source strata and the evaluation of exploration zones.

[0035] In some embodiments, the method for determining the mixing origin of the mixed-source oil based on the first component characteristic parameters, the second component characteristic parameters, and the multi-feature genetic map may further include the following: S1: The first component characteristic parameters and the second component characteristic parameters are calibrated in the multi-feature origin chart to determine the end-member calibration point of the reference end-member sample and the test calibration point of the crude oil sample to be tested. S2: Based on the distribution position of the calibration point to be tested relative to the end-member calibration point, determine the linear distribution trend of the calibration point to be tested, and based on the linear distribution trend, determine the mixing line of the crude oil sample to be tested; S3: Using the positional relationship of the calibration point to be tested on the mixing line, the reference end-member samples corresponding to both ends of the mixing line are determined as the genetic components of the mixed source oil; S4: Determine the contribution ratio of each of the genetic components based on the ratio of the geometric distance between the calibration point to be tested and the endmember calibration point on the mixing line; S5: The genetic components and contribution ratios of the genetic components of the mixed-source oil are determined as the mixed origin of the mixed-source oil.

[0036] Specifically, in determining the mixed-source genesis of oil, the first step is coordinate calibration. Technicians select the lower strata representing a strongly reducing environment within the target area as the first reference end-member, and the upper strata representing a weakly oxidizing environment as the second reference end-member. The ptarane to phytane ratio and gamma-cerane index of these end-member samples are extracted and converted into planar coordinate values. The first and second end-member points are then marked on a pre-designed multi-characteristic genetic chart. Simultaneously, the same conversion is performed on the crude oil sample to be tested, and the calibration points are marked on the chart.

[0037] Next, the determination of the mixing line was initiated. By examining the spatial distribution relationship between the calibration point to be measured and each end-member point, a strong geometric correlation was found between the calibration point to be measured and the first and second end-member points, exhibiting a clear linear distribution trend. Based on this, a mixing trajectory line connecting two end-member points and passing through the calibration point to be measured was established on the chart. This line segment defines the evolutionary path of physical mixing of crude oil from different environments in the geological genetic space.

[0038] Next, the genetic components were qualitatively determined. By observing the positional relationship of the calibration points to be tested on the mixing line, it was confirmed that they were within the constraints of the line segment formed by the first and second endmember points. Based on this geometric membership, it was determined that the genetic components of the crude oil sample to be tested consisted of two sets of sources with completely opposite characteristics: the lower strata source rocks and the upper strata source rocks, thus locking in the "lineage" of the mixed-source oil.

[0039] Furthermore, a quantitative calculation of the contribution ratio is performed. The geometric distances from the calibration point to be measured to the first and second end-member points are precisely measured on the chart. Using the lever principle, the contribution of the other end-member point is calculated in reverse based on the ratio of the distance of the measured point from one end-member point to the total length of the mixing line. For example, when the measured point is closer to the first end-member point, it indicates that it inherits more characteristics of the stratum. The calculation shows that the contribution ratio of the lower strata source rocks is 75%, and the contribution ratio of the upper strata source rocks is 25%.

[0040] Finally, the two sets of stratigraphic names and their corresponding 75% and 25% contribution values ​​were logically summarized to ultimately determine the mixed origin of the crude oil sample. This conclusion clarifies the origin of the crude oil and the contribution of each layer, providing a digital basis for subsequent evaluation of the main hydrocarbon-generating layers.

[0041] By transforming complex geochemical parameters into geometric displacements on a genetic map and utilizing the topological constraints between points, lines, and surfaces, the source of mixed-source oil can be accurately identified and its contribution share quantitatively decomposed. This not only overcomes the subjectivity of relying on experience-based judgment in traditional qualitative analysis, but also solves the technical pain point of not being able to accurately quantify the contribution of multiple sources through geometric distance ratios, significantly improving the credibility and engineering practical value of oil source comparison conclusions.

[0042] In some embodiments, the mutually exclusive feature pairs include: redox environment feature pairs, biological origin feature pairs, and isotope fractionation feature pairs; The redox environment characteristic pair is a combination of indicators, namely the plutophyte ratio (Pr / Ph) characterizing the oxidative environment and the gammacerane index characterizing the reductive salinization environment, used to establish a logical criterion for determining the incompatibility of sedimentary environments. The biosource characteristics are a combination of an orlane index characterizing input from terrestrial higher plants and an index characterizing the ratio of C30 4-methyl sterane to C29 regular sterane from algae, used to identify causal conflicts caused by biosource diversity. The isotopic fractionation characteristic is an index of the isotopic fractionation difference between saturated hydrocarbon carbon isotopes and aromatic hydrocarbon carbon isotopes, used for in-depth verification through deviations from the genetic evolution benchmark.

[0043] In some embodiments, the method of comparing the second component characteristic parameters with the geologically exclusive feature set to determine whether the mutually exclusive feature pairs exist in the crude oil sample to be tested, and determining whether the crude oil sample to be tested is a mixed-source oil based on the determination result, may further include the following: S1: Extract the target parameter values ​​corresponding to each feature pair from the feature parameters of the second component; S2: Compare each of the target parameter values ​​with the preset mutual exclusion threshold range of the geological genesis mutual exclusion feature set to determine the logical state value of the crude oil sample to be tested on each of the feature pairs; S3: Detect the logical state value corresponding to each of the feature pairs. If at least one set of the logical state values ​​that characterize mutually exclusive geological genesis attributes are detected in the crude oil sample to be tested, it is determined that the crude oil sample to be tested contains the mutually exclusive feature pairs. S4: Based on the detection results of the mutually exclusive feature pairs, the crude oil sample to be tested is determined to be a mixed-source oil.

[0044] Specifically, when identifying the mixed-source properties of the crude oil sample to be tested, the first step is to extract the target parameter values. Technicians send the crude oil sample collected from the target well to the laboratory for component analysis. From the obtained second component characteristic parameters, they accurately extract the key indicator values ​​corresponding to the preset characteristic pairs. In this embodiment, the focus is on extracting the ptarane to phytane ratio, which characterizes the redox degree of the sedimentary environment, and the gammacerane index, which characterizes the salinity of the sedimentary water.

[0045] Next, the logical state value is determined. The extracted index values ​​are compared one by one with preset threshold ranges in the set of mutually exclusive geological features. For example, in this embodiment, the measured value of the pterane to phytane ratio of the crude oil sample is 5.0, falling into the strong oxidation mutually exclusive threshold range greater than 3.0; simultaneously, the measured value of the gamma-cerane index of the sample is 0.5, also falling into the strong reduction high-salinity mutually exclusive threshold range greater than 0.4. Based on this, a logical state value representing the simultaneous existence of extreme features is assigned to this feature pair.

[0046] Next, the detection of mutually exclusive feature pairs was performed. By retrieving the aforementioned logical state values, it was found that the crude oil sample exhibited significant strong oxidizing properties in the pterane to phytane ratio, while showing significant strong reducing supersalt properties in the gammacerane index. Since strong oxidizing and strong reducing environments are logically fundamentally conflicting and incompatible under a single geological origin, the appearance of this "paradoxical" signal directly triggered the judgment criterion: the detection of a set of mutually exclusive logical state values ​​representing geological origin attributes determined the presence of mutually exclusive feature pairs in the sample.

[0047] Finally, a conclusion was drawn based on the test results. Based on the aforementioned causal paradox, the possibility that the crude oil was generated from a single weakly oxidizing to weakly reducing transition environment was ruled out. It was determined that the moderate geochemical values ​​exhibited in the sample were actually a "median artifact" formed by the physical mixing of strongly oxidizing and strongly reducing end-member crude oils. Therefore, the crude oil sample was ultimately identified as a mixed-source oil and proceeded to the next step of quantitative component separation.

[0048] By introducing a feature pair detection mechanism based on geological logic paradox, it is possible to directly identify contradictory causal signals in the crude oil to be tested that should not coexist. This effectively exposes the illusion of index averaging caused by physical mixing, fundamentally solving the technical problem that existing technologies can easily misjudge multi-source mixed-source oil as single-source transition phase crude oil by simply matching similarity. This greatly improves the accuracy and objectivity of identifying crude oil with complex origins.

[0049] In some embodiments, when the crude oil sample to be tested is determined to be a non-mixed source oil, the method may further include the following: S1: Calculate the causal correlation evaluation parameters between the characteristic parameters of the second component and the characteristic parameters of the first component; S2: Based on the genetic correlation evaluation parameters, determine the target reference end-member sample that has genetic consistency with the component characteristics of the crude oil sample to be tested; S3: The origin of the target reference end-member sample is determined as the single origin of the crude oil sample to be tested.

[0050] Specifically, when the crude oil sample to be tested is determined to be non-mixed-source oil, a single-source attribution process will be executed. First, the calculation of genetic correlation evaluation parameters will begin. Technicians will use the second-component characteristic parameters of the crude oil sample to be tested to compare them one by one with the first-component characteristic parameters of each reference end-member sample stored in the database. By calculating the vector similarity or Euclidean distance between the two samples in terms of the distribution of key biomarker compounds, stable carbon isotope composition, and environmentally sensitive parameters, genetic correlation evaluation parameters that quantify the closeness of their phylogenetic relationship will be obtained.

[0051] Subsequently, based on the calculated correlation values, the target reference end-member sample was determined. By sorting all comparison results in descending order, the specific end-member with the highest correlation value and all key genetic indicators within the same error range was retrieved. In this embodiment, if the correlation coefficient between the crude oil sample to be tested and the reference end-member sample representing the source rock of the Shahejie Formation (Member 3) is closest to 100%, and their positions on the chart almost overlap, then this end-member is selected as the target reference end-member sample with genetic consistency.

[0052] Finally, the source attribution is determined. The system automatically extracts the preset geological attribute tags from the target reference end-member sample, directly identifying the genetic source of that end-member, such as specific stratigraphic names, sedimentary facies types, and maturity stages, as the single genetic source of the crude oil sample to be tested. In this embodiment, the final output conclusion is: the crude oil to be tested is a typical crude oil controlled by a single source, and its genetic source is the third member of the Shahejie Formation. This process achieves a logical closed loop from determining non-mixed-source origins to identifying the specific contributing stratigraphic layer.

[0053] By introducing a genetic correlation evaluation mechanism under the premise of determining non-mixed-source crude oil, an automatic identification and attribution path for single-source crude oil was constructed. This not only improves the completeness of the method for determining mixed-source crude oil and ensures that clear geological conclusions can be obtained for various crude oil samples, but also eliminates the interference of single-parameter randomness by using multi-index joint evaluation methods, which greatly improves the accuracy and efficiency of identifying the source of single-gene crude oil.

[0054] In some embodiments, the method of performing component detection on the reference end-member sample and the crude oil sample to be tested, respectively, to determine the first component characteristic parameter corresponding to the reference end-member sample and the second component characteristic parameter corresponding to the crude oil sample to be tested, may further include the following in specific implementations: S1: Gas chromatography-mass spectrometry and stable carbon isotope detection are performed on the reference end-member sample and the crude oil sample to be tested, respectively, to obtain the corresponding biomarker fingerprint data and isotope composition data. S2: Extract the peak area of ​​each biomarker in the biomarker fingerprint data and calculate the corresponding biomarker ratio index; and determine the stable carbon isotope values ​​in the isotope composition data; S3: Based on the bio-standard ratio index and the stable carbon isotope value, construct the first component characteristic parameters and the second component characteristic parameters.

[0055] Specifically, in the implementation phase of obtaining component characteristic parameters, the reference end-member sample and the crude oil sample to be tested from the area to be tested are first subjected to laboratory testing. After sample pretreatment, technicians inject the samples into a gas chromatography-mass spectrometry (GC-MS) instrument. Using the temperature program set in the instrument, hydrocarbon components in the samples are separated and identified, thereby obtaining biomarker fingerprint data reflecting the source of organic matter and sedimentary environment. Simultaneously, the samples are injected into an isotope ratio mass spectrometer for detection; through high-temperature combustion conversion and mass spectrometry analysis, the isotopic composition distribution data of carbon in the samples are obtained.

[0056] Subsequently, the data quantification stage begins. From the fingerprint data obtained by gas chromatography-mass spectrometry (GC-MS), the integration function of the chromatography workstation is used to automatically extract the peak area values ​​of various key biomarkers. These compounds include, but are not limited to, n-alkanes, isoprene-like alkanes, steranes, and terpenes. Based on this, a series of biomarker ratio indices are obtained by calculating the ratios between the peak areas of specific compounds, such as the pterane to phytane ratio reflecting the redox environment, and the gammacerane index reflecting water salinity. Simultaneously, stable carbon isotope values ​​of the whole oil and its different fractions are accurately obtained from the isotopic composition data.

[0057] Finally, the parameter set construction operation is performed. The multiple bio-standard ratio indices and stable carbon isotope values ​​obtained from the above calculations are structurally compiled. For the reference end-member sample, its corresponding indices are integrated to form the first component characteristic parameters; for the crude oil sample to be tested, its corresponding indices are integrated to form the second component characteristic parameters. These parameter sets cover multi-dimensional information from molecular fingerprints to isotopic characteristics, providing standardized digital input for subsequent establishment of mutually exclusive geological genesis logic and construction of genetic maps.

[0058] By integrating gas chromatography-mass spectrometry and stable carbon isotope detection, multi-dimensional geochemical characteristics were extracted from both molecular composition and isotope distribution, ensuring the objectivity and comprehensiveness of the original data. By converting peak area into ratio indicators, systematic errors caused by sample quantity differences and fluctuations in the detection environment were effectively eliminated, significantly improving the reliability of key characteristic parameters in the subsequent genetic identification process. This laid a solid experimental data foundation for the accurate disassembly of complex mixed-source oils.

[0059] In some embodiments, the method may further include the following: S1: Match the genetic components and their contribution ratios with the geological strata information in the target area to determine the genetic contribution weights of different source rocks to the crude oil sample to be tested. S2: Compare the genetic contribution weights of different hydrocarbon source rocks to the crude oil sample to be tested, and determine the layers that meet the preset threshold as the main hydrocarbon source layers that play a dominant role in hydrocarbon accumulation. S3: Based on the spatial distribution characteristics of the main hydrocarbon source strata, determine the favorable oil and gas exploration areas within the target region.

[0060] Specifically, after the quantitative analysis of the genetic components and proportions of the mixed-source oil is completed, the application of the results begins. The first step is to determine the genetic contribution weights. Technicians physically map the names of the genetic components identified in the previous steps, such as the third and fourth sections of the Shahejie Formation, to the actual geological sequences within the target area. By directly assigning the calculated contribution ratios of 70% and 30% to the corresponding geological strata, the genetic contribution weight of the third section of the Shahejie Formation to the tested crude oil sample is determined to be 0.7, and the genetic contribution weight of the fourth section of the Shahejie Formation is determined to be 0.3.

[0061] Next, the process moves to determining the primary hydrocarbon source layer. A preset dominant contribution threshold is retrieved, for example, set at 50%. Comparison reveals that the genetic contribution weight of the third member of the Shahejie Formation is significantly higher than this preset threshold, and significantly better than that of the fourth member. Based on this, the third member of the Shahejie Formation is determined to be the dominant hydrocarbon source layer for hydrocarbon accumulation in the target well location and surrounding area. This process eliminates interference from layers with smaller contributions, focusing exploration efforts on the core contributing source.

[0062] Finally, the delineation of favorable oil and gas exploration areas was carried out. Technicians retrieved spatial distribution data of the main source rock formation, namely the third member of the Shahejie Formation, within the target area, including the distribution of hydrocarbon generation centers, effective stratigraphic thickness, and thermal evolution distribution maps. By spatially overlaying the hydrocarbon generation centers of the main source rock formation with known fault migration pathways and structural traps, reservoir spaces within the oil supply range of the main source rock were identified. Ultimately, favorable oil and gas exploration areas were determined within the target area in locations close to the hydrocarbon generation centers of the third member of the Shahejie Formation and with favorable migration conditions.

[0063] By matching the contribution ratio at the chemical level with the geological strata at the physical level, a logical bridge was established from molecular fingerprint inversion to resource evaluation weights, enabling the quantitative determination of the main hydrocarbon source strata. This not only overcomes the problem of not distinguishing between primary and secondary sources in traditional qualitative descriptions, but also directly guides the selection of exploration target areas by combining spatial distribution characteristics, greatly improving the scientificity and accuracy of exploration decisions and effectively reducing drilling risks in complex multi-source systems.

[0064] As can be seen from the above, the embodiment of this specification provides a method for determining mixed-source oil, which involves acquiring a reference end-member sample and a crude oil sample to be tested from a target area; performing component detection on the reference end-member sample and the crude oil sample to be tested respectively to determine a first component characteristic parameter corresponding to the reference end-member sample and a second component characteristic parameter corresponding to the crude oil sample to be tested; based on the first component characteristic parameter, selecting feature pairs that are mutually exclusive under geological genesis, and constructing a geologically mutually exclusive feature set based on the mutually exclusive feature pairs; comparing the second component characteristic parameter with the geologically mutually exclusive feature set to determine whether the mutually exclusive feature pairs exist in the crude oil sample to be tested, and determining whether the crude oil sample to be tested is a mixed-source oil based on the determination result. In this way, by using reference end-member samples to screen out mutually exclusive feature pairs under geological conditions and constructing a geologically mutually exclusive feature set, the second component feature parameters of the crude oil sample to be tested are compared with this feature set. By detecting whether the mutually exclusive feature pairs exist in the crude oil sample to be tested, it is possible to accurately determine whether the crude oil sample to be tested is a mixed-origin oil. This method uses the mutual exclusion logic at the genetic level to overcome the misleading effect of single parameter values, effectively solving the technical problem in the prior art where parameters appear as medium values ​​due to mixing, and thus misjudging it as a single-origin environment. This significantly improves the accuracy of identifying mixed-origin oils with complex genesis.

[0065] See Figure 2 As shown in the embodiments of this specification, a specific electronic device is also provided, wherein the electronic device includes a network communication port 201, a processor 202 and a memory 203, and the above structures are connected by internal cables so that the various structures can perform specific data interaction.

[0066] Specifically, the network communication port 201 can be used to acquire reference terminal samples and crude oil samples to be tested in the target area.

[0067] The processor 202 can specifically be used to perform component detection on the reference end-member sample and the crude oil sample to be tested, respectively, to determine the first component characteristic parameter corresponding to the reference end-member sample and the second component characteristic parameter corresponding to the crude oil sample to be tested; based on the first component characteristic parameter, to screen out feature pairs that are mutually exclusive under geological conditions, and to construct a geologically mutually exclusive feature set based on the mutually exclusive feature pairs; to compare the second component characteristic parameter with the geologically mutually exclusive feature set, to determine whether the mutually exclusive feature pairs exist in the crude oil sample to be tested, and to determine whether the crude oil sample to be tested is a mixed-source oil based on the determination result.

[0068] The memory 203 can be used to store the corresponding instruction program.

[0069] Based on the above method, the relevant structural performance of electronic equipment can be effectively utilized to improve the data processing speed of electronic equipment and efficiently realize a method for determining mixed-source oil.

[0070] In this embodiment, the network communication port 201 can be a virtual port bound to different communication protocols, thereby enabling the sending or receiving of different data. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. Furthermore, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM or CDMA; it can also be a Wi-Fi chip; or it can be a Bluetooth chip.

[0071] In this embodiment, the processor 202 can be implemented in any suitable manner. For example, the processor can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, etc. This specification is not limiting.

[0072] In this embodiment, the memory 203 may include a hierarchy. In a digital system, anything that can store binary data can be a memory. In an integrated circuit, a circuit with storage function but no physical form is also called a memory, such as RAM, FIFO, etc. In a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0073] This specification also provides a computer-readable storage medium based on the above-described method for determining mixed-source oil, which acquires a reference end-member sample and a crude oil sample to be tested from a target area; performs component detection on the reference end-member sample and the crude oil sample to be tested, respectively, to determine a first component characteristic parameter corresponding to the reference end-member sample and a second component characteristic parameter corresponding to the crude oil sample to be tested; based on the first component characteristic parameter, selects feature pairs that are mutually exclusive under geological conditions, and constructs a geologically mutually exclusive feature set based on the mutually exclusive feature pairs; compares the second component characteristic parameter with the geologically mutually exclusive feature set to determine whether the mutually exclusive feature pairs exist in the crude oil sample to be tested, and determines whether the crude oil sample to be tested is mixed-source oil based on the determination result.

[0074] In this embodiment, the storage medium includes, but is not limited to, Random Access Memory (RAM), Read-Only Memory (ROM), Cache, Hard Disk Drive (HDD), or Memory Card. The memory can be used to store computer program instructions. The network communication unit can be an interface configured according to standards specified in the communication protocol for network connection communication.

[0075] In this embodiment, the specific functions and effects implemented by the program instructions stored in the computer-readable storage medium can be explained in comparison with other embodiments, and will not be repeated here.

[0076] See Figure 3 At the software level, embodiments of this specification also provide a mixed-source oil determination device, which may specifically include the following structural modules: The sample acquisition module 301 is used to acquire the reference end-member sample and the crude oil sample to be tested in the target area. The parameter determination module 302 is used to perform component detection on the reference end-member sample and the crude oil sample to be tested, respectively, and determine the first component characteristic parameter corresponding to the reference end-member sample and the second component characteristic parameter corresponding to the crude oil sample to be tested. The feature set determination module 303 is used to filter out mutually exclusive feature pairs under geological genesis conditions based on the first component feature parameters, and to construct a geological genesis mutually exclusive feature set based on the mutually exclusive feature pairs. The mixed-source oil determination module 304 is used to compare the second component characteristic parameters with the geologically exclusive feature set, determine whether the mutually exclusive feature pair exists in the crude oil sample to be tested, and determine whether the crude oil sample to be tested is a mixed-source oil based on the determination result.

[0077] In some embodiments, the above-described apparatus further includes: when the crude oil sample to be tested is determined to be a mixed-source oil, establishing a multi-feature origin chart with the feature pairs as coordinate axes; and a mixed origin determination module, used to determine the mixed origin of the mixed-source oil based on the first component feature parameters, the second component feature parameters, and the multi-feature origin chart.

[0078] In some embodiments, the above-described mixture origin determination module, in specific implementation, performs coordinate calibration of the first component characteristic parameters and the second component characteristic parameters in the multi-feature origin chart to determine the end-member calibration point of the reference end-member sample and the test calibration point of the crude oil sample to be tested; determines the linear distribution trend of the test calibration point relative to the end-member calibration point based on the distribution position of the test calibration point relative to the end-member calibration point, and determines the mixing line of the crude oil sample to be tested based on the linear distribution trend; uses the positional relationship of the test calibration point on the mixing line to determine the reference end-member samples corresponding to both ends of the mixing line as the genetic components of the mixed source oil; determines the contribution ratio of each genetic component based on the geometric distance ratio of the test calibration point on the mixing line relative to the end-member calibration point; and determines the mixture origin of the mixed source oil by the genetic components and the contribution ratio of the genetic components.

[0079] In some embodiments, the above-described device further includes: the mutually exclusive feature pairs include: redox environment feature pairs, biological origin feature pairs, and isotope fractionation feature pairs; wherein, the redox environment feature pairs are a combination of indicators characterizing the oxidative environment (Pr / Ph ratio) and the gammacerane index characterizing the reductive salinization environment, used to establish logical criteria for determining sedimentary environment incompatibility; the biological origin feature pairs are a combination of indicators characterizing the orlene index characterizing the input from terrestrial higher plants and the ratio of C30 4-methylsterane to C29 regular sterane characterizing algal origin, used to identify causal conflicts caused by biogenic input diversity; the isotope fractionation feature pairs are isotope fractionation difference indicators between saturated hydrocarbon carbon isotopes and aromatic hydrocarbon carbon isotopes, used for depth verification through deviations from the genetic evolution benchmark.

[0080] In some embodiments, the above-mentioned mixed-source oil determination module 304 specifically extracts the target parameter values ​​corresponding to each of the feature pairs from the second component feature parameters; compares each of the target parameter values ​​with a preset mutual exclusion threshold interval in the set of mutually exclusive geological genesis features to determine the logical state value of the crude oil sample to be tested on each of the feature pairs; detects the logical state value corresponding to each of the feature pairs; if at least one set of logical state values ​​characterizing mutually exclusive geological genesis attributes is detected in the crude oil sample to be tested, it is determined that the crude oil sample to be tested contains the mutually exclusive feature pairs; and determines that the crude oil sample to be tested is a mixed-source oil based on the detection results of the mutually exclusive feature pairs.

[0081] In some embodiments, the above-described apparatus further includes: when the crude oil sample to be tested is determined to be a non-mixed-source oil, calculating the causal correlation evaluation parameter between the second component characteristic parameter and the first component characteristic parameter; determining a target reference end-member sample that has causal consistency with the component characteristics of the crude oil sample to be tested based on the causal correlation evaluation parameter; and determining the causal source of the target reference end-member sample as the single causal source of the crude oil sample to be tested.

[0082] In some embodiments, the parameter determination module 302, in specific implementation, performs gas chromatography-mass spectrometry detection and stable carbon isotope detection on the reference end-member sample and the crude oil sample to be tested, respectively, to obtain corresponding biomarker fingerprint data and isotope composition data; extracts the peak area of ​​each biomarker in the biomarker fingerprint data and calculates the corresponding biomarker ratio index; determines the stable carbon isotope value in the isotope composition data; and constructs the first component characteristic parameter and the second component characteristic parameter based on the biomarker ratio index and the stable carbon isotope value.

[0083] In some embodiments, the above-described apparatus further includes: matching the genetic components and their contribution ratios with geological strata information within the target area to determine the genetic contribution weights of different strata source rocks to the crude oil sample to be tested; comparing the genetic contribution weights of different strata source rocks to the crude oil sample to be tested, and determining the strata that meet a preset threshold as the main source strata that play a dominant role in hydrocarbon accumulation; and determining favorable oil and gas exploration areas within the target area based on the spatial distribution characteristics of the main source strata.

[0084] It should be noted that the units, devices, or modules described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. For ease of description, the above devices are described by dividing them into various modules according to their functions. Of course, in implementing this specification, the functions of each module can be implemented in the same software and / or hardware, or modules that implement the same function can be implemented by a combination of sub-modules or sub-units, etc. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. For example, units or components can be combined or integrated into another system, or some features can be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection between the devices or units shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0085] As can be seen from the above, based on the mixed-source oil determination device provided in the embodiments of this specification, a reference end-member sample and a crude oil sample to be tested from a target area are acquired; the reference end-member sample and the crude oil sample to be tested are respectively subjected to component detection to determine the first component characteristic parameter corresponding to the reference end-member sample and the second component characteristic parameter corresponding to the crude oil sample to be tested; based on the first component characteristic parameter, mutually exclusive feature pairs under geological genesis are selected, and a geological genesis mutually exclusive feature set is constructed based on the mutually exclusive feature pairs; the second component characteristic parameter is compared with the geological genesis mutually exclusive feature set to determine whether the mutually exclusive feature pairs exist in the crude oil sample to be tested, and whether the crude oil sample to be tested is a mixed-source oil is determined based on the determination result.

[0086] In a specific scenario example, the method and apparatus for determining mixed-source oil provided in this specification can be applied to solve the technical problem that existing technologies misclassify multi-source mixed-source oil as single-source transition phase crude oil due to the index averaging effect, making it difficult to accurately identify complex genetic components. The specific implementation process may include the following:

[0087] S1: Sample collection and geochemical data acquisition.

[0088] Crude oil samples to be analyzed and potential source rock (end-member) samples in the study area were collected and subjected to gas chromatography-mass spectrometry (GC-MS) and stable carbon isotope analysis to obtain biomarker parameters and isotope data.

[0089] S2: Construct a “mutually exclusive fingerprint database of geological genesis”.

[0090] Based on the principles of sedimentology and organic geochemistry, mutually exclusive index pairs in terms of geological origin are selected, and the "paradoxical characteristic" is defined. The mutually exclusive index pairs include at least one or more of the following: Redox repulsion pair: Pr / Ph ratio and gammacerane index (G / C3OH). (High Pr / Ph indicates oxidation, high gammacerane indicates reductive salinization; their coexistence is a paradox).

[0091] Biologically exclusive pairs: Orylane (terrestrial higher plants) and C304-methylsterane / C29 regular sterane (freshwater / saltwater algae).

[0092] Isotope fractionation mutual exclusion pairs: abnormal fractionation difference between saturated hydrocarbon carbon isotopes and aromatic hydrocarbon carbon isotopes.

[0093] S3: Diagnosis of the "paradoxical characteristics" of mixed-source oil (qualitative identification).

[0094] Geochemical data of the crude oil sample to be analyzed are projected into the mutually exclusive fingerprint database. If a sample simultaneously possesses two extreme features in a mutually exclusive pair (e.g., it has both feature value A indicating oxidation and feature value B indicating reduction), or if the data points significantly deviate from a single source rock evolution sequence and fall into the "forbidden zone," then the crude oil is determined to be a mixed-source oil.

[0095] S4: Construct a multidimensional fingerprint hybrid model.

[0096] Select mutually exclusive indices that constitute the paradoxical feature as coordinate axes (e.g., the X-axis is the gammacerane index, and the Y-axis is Pr / Ph) to construct a two-dimensional or three-dimensional scatter plot.

[0097] Project known or predicted single endmembers (such as the Ed3 freshwater oxidation endmember and the Es1x salinization reduction endmember).

[0098] S5: Place the mixed source oil sample to be tested at the designated point.

[0099] Verify linearity: If the test sample points show a clear linear arrangement and are located within the mixing zone connecting the endmembers, then the mixing cause is confirmed.

[0100] Based on the above embodiments, the "average misjudgment" defect of conventional indicators is effectively overcome, significantly improving the accuracy of identification. Existing technologies, when faced with crude oil mixtures with diametrically opposed properties (such as strong oxidizing and strong reducing), often misinterpret them as a single "weakly oxidizing-weakly reducing" transitional sedimentary environment because the resulting geochemical parameters are of moderate value. This specification introduces "paradoxical characteristics" (i.e., coexistence of mutually exclusive indicators) as the core identification criterion, directly seeing through the "median illusion" to understand the "true nature of the mixture," fundamentally avoiding the misjudgment of "physical mixing" as "chemical evolution transition," and greatly improving the accuracy of identifying crude oils with complex origins.

[0101] This approach overcomes the limitations of purely mathematical statistical methods, enhancing the scientific rigor and reliability of geological interpretation. Traditional multivariate statistical methods (such as cluster analysis) classify data solely based on numerical distance, lacking constraints on the rationality of geological processes and easily eliminating seemingly anomalous mixed samples. This specification is built upon the solid geological logic of "mutual exclusivity of sedimentary environments" (i.e., a body of water cannot be both fresh and saline at the same geological moment). By visually demonstrating the linear distribution trend of data points along the line connecting endmembers such as Ed3 (freshwater) and Es1x (saline water) using graphical representations, it provides strong physicochemical evidence for the identification of mixed-source oil, making the identification conclusions more convincing than simple mathematical fitting.

[0102] It can identify "hidden mixed" reservoirs that are difficult to detect using conventional methods. For mixed-source oils with significantly different mixing ratios or indistinct end-member characteristics, conventional spider diagrams often overlap in shape, making them difficult to distinguish. This specification utilizes highly specific "conflict fingerprints" (such as anomalous combinations of gammacerane and Pr / Ph) to keenly capture logical conflicts between indicators even in cases of atypical mixing characteristics, thereby discovering masked secondary end-member contributions and effectively broadening the applicability of source-source correlation.

[0103] The method is simple and easy to implement, and has extremely high value for widespread application. The basic data required in this manual (such as chromatographic-mass spectrometry data) are all routine testing items in oil and gas exploration, without the need to introduce expensive additional testing equipment or complex experimental procedures. Technicians only need to use existing geochemical data to construct specific paradox maps to achieve rapid identification. This greatly reduces the technical threshold and application cost, facilitating large-scale promotion and standardized application in the production front lines of major oilfields.

[0104] This manual provides clear direction for detailed exploration in complex basins. By accurately identifying mixed-source oils and their end-member types (e.g., explicitly indicating a mixture of Ed3 and Es1x), it is possible to directly deduce the migration paths and charging history of underground hydrocarbons (e.g., indicating the existence of cross-strata fault transport systems). This has significant practical guiding significance for guiding explorers in finding potential hydrocarbon-generating sites and predicting favorable hydrocarbon accumulation zones.

[0105] In some embodiments, see Figure 4 As shown, the process begins with sample collection and data acquisition. Then, gas chromatography-mass spectrometry (GC-MS) and isotope ratio mass spectrometry (IRMS) are used to perform geochemical analysis on the sample to obtain raw detection data. Based on this, key fingerprint parameters are automatically extracted, including but not limited to the pterane to phytane ratio, gammacerane index, and sterane compound distribution characteristics. Next, the core logic judgment stage is initiated, which checks whether there are coexisting mutually exclusive indicators representing a genetic paradox in the sample. If no such paradoxical characteristics are found, the process switches to the conventional oil source comparison path, performing a reasonable explanation based on a single source.

[0106] If the assessment results reveal paradoxical characteristics, the crude oil to be tested is identified as a mixed-source oil, and a multi-dimensional mixing model chart is further constructed, spatializing the data using a two-dimensional planar diagram or a triangular diagram. Subsequently, by verifying the distribution trend of data points in the chart, it is confirmed whether it conforms to the linear or zonal evolution trajectory characteristic of physical mixing. Finally, by integrating spatial distribution and geological background, a qualitative conclusion regarding the origin of the crude oil is output, thus completing the entire identification process from preliminary screening to in-depth analysis.

[0107] In some embodiments, a basin with a specific depression is selected as the study area, and the origin of Type III and Type IV crude oils with significant genetic controversy within the area is identified.

[0108] S1: Data acquisition and parameter selection.

[0109] First, gas chromatography-mass spectrometry (GC-MS) analysis was performed on typical crude oil samples and potential source rock (Ed3 section, Es1x section, Es3 section) samples collected from the area.

[0110] The pristine-to-plant ratio (Pr / Ph) was selected as a sensitive indicator of the redox environment; the gammacerane index (G / C30H) was selected as a sensitive indicator of water salinity and stratification; and C27 / C29 regular steranes and C30-4-methylsterane / C29 steranes were selected as distinguishing indicators of parent material source (algae vs. higher plants).

[0111] S2: Identification based on the "oxidation-salinization" environmental paradox, see [reference]. Figure 5 (a) in the middle.

[0112] like Figure 5 As shown in (a), a two-dimensional cross plot of "Environment: Redox and Salinity" was constructed. The horizontal axis represents the gammacerane index, and the vertical axis represents the pteranocyanate ratio (Pr / Ph).

[0113] S2-1: Defining End-Member Characteristics. By analyzing known source rock samples, two end-member regions with diametrically opposed properties were identified on the plate: Ed3 endmember (diamond-shaped dot in the upper left corner of the figure): characterized by "high Pr / Ph (>1.8) and low gammacerane", indicating a strongly oxidized freshwater shallow lacustrine swamp facies sedimentary environment.

[0114] Es1x endmember (diamond-shaped dot in the lower right corner of the figure): exhibits characteristics of "low Pr / Ph (<1.3), high gammacerane", indicating a strongly reducing saline / semi-saline deep lacustrine sedimentary environment.

[0115] S2-2: Diagnosing the "Paradoxical Feature" The Type III crude oil sample to be tested (red dot in the image) was plotted on this plate. Observation revealed that this type of crude oil did not fall into any single end-member region, but instead exhibited a significant geochemical paradox: This type of crude oil also showed high levels of gammacerane (inherited from the salinization gene of Es1x) and high Pr / Ph values ​​(inherited from the oxidation gene of Ed3).

[0116] Geologically, a single body of water cannot simultaneously maintain both a strong oxidizing and a strong reducing environment. Therefore, this phenomenon of "coexistence of contradictions" directly rules out the possibility of a single transitional phase as the cause.

[0117] S2-3: Observation of Linear Distribution Verification Figure 5 The spatial distribution trend of data points in (a) is shown. The data points of Class III crude oil show a clear linear arrangement and fall precisely on the straight line (mixing line) connecting the Ed3 endmember and the Es1x endmember.

[0118] Qualitative conclusion: This strict linear relationship confirms that Group III crude oil is a product of the physical mixing of Ed3 segment freshwater oxidized oil and Es1x segment saline water reduced oil. The closer the red dot is to the lower right corner of the graph, the greater the contribution of the Es1x endmember; conversely, the greater the contribution of Ed3.

[0119] S3: Auxiliary identification based on the "source input" paradox, see [link / reference] Figure 5 (b) in the middle.

[0120] To further verify the above conclusions, a "source input: parent material source" chart was constructed using biomarkers, such as... Figure 5 As shown in (b) of the diagram.

[0121] S3-1: Construct a multi-endmember identification model. Select parameters that are sensitive to the source of the parent material and construct a triangular region (or polygonal region) enclosed by three endmembers: Es1z, Es1x, and Es3.

[0122] Es1z endmembers: rich in dinoflagellates / mixed input features.

[0123] Es1x endmembers: rich in algal characteristics, with a significant C27 sterane advantage.

[0124] Es3 end-members: Higher plants have relatively more input.

[0125] S3-2: Mixed feature confirmation involves placing the crude oil to be tested (yellow and green dots in the figure) at the sampling point.

[0126] See Figure 5 In (b), some crude oil samples (such as Group II crude oil, yellow dots) fall inside the dashed triangle formed by the endmembers or on the edge line.

[0127] This indicates that these crude oils did not originate from a single source rock stratum, but rather were formed by the mixing of oils generated from different source rock strata during migration. Their biomarker characteristics possess dual attributes of algal bloom (Es1x feature) and mixed / dinoflagellate input (Es1z / Es3 feature).

[0128] S4: Judgment Summary.

[0129] comprehensive Figure 5 (a) and Figure 5 The analysis results in (b) show that by capturing the paradoxical phenomenon of "coexistence of oxidation index and salinization index" at the geological and geochemical level, this invention successfully identified Class III crude oil as a typical mixed-source oil. Figure 5 The clear linear mixing zone in (a) not only refutes the single-gene hypothesis, but also intuitively reveals the geological fact that this type of mixed-source oil is formed by the mixing of two sets of end-member oil and gas, Ed3 (freshwater / oxidation) and Es1x (saltwater / reduction), in the underground reservoir.

[0130] While this specification provides the steps of operation for the methods described in the embodiments or flowcharts, more or fewer steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible order of execution among many steps and does not represent the only possible order. In actual device or client product execution, the methods shown in the embodiments or drawings may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitations, the presence of other identical or equivalent elements in a process, method, product, or apparatus that includes said elements is not excluded. The terms "first," "second," etc., are used to denote names and do not indicate any particular order.

[0131] Those skilled in the art will also know that, besides implementing the controller using purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller function as logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0132] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this specification can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions of this specification can essentially be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, mobile terminal, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments of this specification.

[0133] Although this specification has been described by way of examples, those skilled in the art will recognize that many variations and modifications are possible without departing from the spirit of this specification, and it is intended that the appended claims cover such variations and modifications without departing from the spirit of this specification.

Claims

1. A method for determining mixed-source oil, characterized in that, include: Acquire reference end-member samples and crude oil samples to be tested in the target area; The reference end-member sample and the crude oil sample to be tested are subjected to component detection to determine the first component characteristic parameter corresponding to the reference end-member sample and the second component characteristic parameter corresponding to the crude oil sample to be tested. Based on the first component characteristic parameters, mutually exclusive feature pairs under geological genesis conditions are selected, and a geological genesis mutually exclusive feature set is constructed based on the mutually exclusive feature pairs. The second component characteristic parameters are compared with the geologically exclusive feature set to determine whether the mutually exclusive feature pair exists in the crude oil sample to be tested, and whether the crude oil sample to be tested is a mixed source oil is determined based on the judgment result.

2. The method according to claim 1, characterized in that, The method further includes: If the crude oil sample to be tested is determined to be a mixed-source oil, a multi-feature origin chart is established using the feature pairs as coordinate axes. The mixing origin of the mixed source oil is determined based on the first component characteristic parameters, the second component characteristic parameters, and the multi-feature origin chart.

3. The method according to claim 2, characterized in that, Determining the mixing origin of the mixed-source oil based on the first component characteristic parameters, the second component characteristic parameters, and the multi-feature genetic map includes: The first component characteristic parameters and the second component characteristic parameters are calibrated in the multi-feature origin chart to determine the end-member calibration point of the reference end-member sample and the test calibration point of the crude oil sample to be tested. Based on the distribution position of the calibration point to be tested relative to the end-member calibration point, the linear distribution trend of the calibration point to be tested is determined, and based on the linear distribution trend, the mixing line of the crude oil sample to be tested is determined. By utilizing the positional relationship of the calibration points to be tested on the mixing line, the reference end-member samples corresponding to both ends of the mixing line are identified as the genetic components of the mixed source oil; The contribution ratio of each of the genetic components is determined based on the ratio of the geometric distance between the calibration point to be tested and the endmember calibration point on the mixing line. The genetic components and contribution ratios of the genetic components of the mixed-source oil are determined as the mixed origin of the mixed-source oil.

4. The method according to claim 1, characterized in that, The mutually exclusive feature pairs include: redox environment feature pairs, biological origin feature pairs, and isotope fractionation feature pairs; The redox environment characteristic pair is a combination of indicators, namely the plutophyte ratio (Pr / Ph) characterizing the oxidative environment and the gammacerane index characterizing the reductive salinization environment, used to establish a logical criterion for determining the incompatibility of sedimentary environments. The biogenic characteristics are compared to the olane index, which characterizes input from terrestrial higher plants, and the C, which characterizes algal origin. 30 4-Methylsterane and C 29 A combination of indicators for regular sterane ratios is used to identify causal conflicts caused by diversity in student input. The isotopic fractionation characteristic is an index of the isotopic fractionation difference between saturated hydrocarbon carbon isotopes and aromatic hydrocarbon carbon isotopes, used for in-depth verification through deviations from the genetic evolution benchmark.

5. The method according to claim 3, characterized in that, The step of comparing the second component characteristic parameters with the geologically exclusive feature set to determine whether the mutually exclusive feature pair exists in the crude oil sample to be tested, and determining whether the crude oil sample to be tested is a mixed-source oil based on the determination result, includes: Extract the target parameter values ​​corresponding to each feature pair from the second component feature parameters; The target parameter values ​​are compared with the preset mutual exclusion threshold range of the geological genesis mutual exclusion feature set to determine the logical state value of the crude oil sample to be tested on each feature pair. The logical state values ​​corresponding to each of the aforementioned feature pairs are detected. If at least one set of the aforementioned logical state values ​​that characterize mutually exclusive geological genesis attributes are detected in the crude oil sample to be tested, it is determined that the crude oil sample to be tested contains the aforementioned mutually exclusive feature pairs. Based on the detection results of the mutually exclusive feature pairs, the crude oil sample to be tested is determined to be a mixed-source oil.

6. The method according to claim 2, characterized in that, If the crude oil sample to be tested is determined to be a non-mixed source oil, the method further includes: Calculate the causal correlation evaluation parameters between the characteristic parameters of the second component and the characteristic parameters of the first component; Based on the genetic correlation evaluation parameters, a target reference end-member sample with genetic consistency with the component characteristics of the crude oil sample to be tested is determined. The origin of the target reference end-member sample is determined as the single origin of the crude oil sample to be tested.

7. The method according to claim 1, characterized in that, The step of performing component detection on the reference end-member sample and the crude oil sample to be tested, respectively, to determine the first component characteristic parameter corresponding to the reference end-member sample and the second component characteristic parameter corresponding to the crude oil sample to be tested, includes: Gas chromatography-mass spectrometry and stable carbon isotope detection were performed on the reference end-member sample and the crude oil sample to be tested, respectively, to obtain the corresponding biomarker fingerprint data and isotope composition data. Extract the peak area of ​​each biomarker in the biomarker fingerprint data and calculate the corresponding biomarker ratio index; and determine the stable carbon isotope values ​​in the isotopic composition data; Based on the bio-standard ratio index and the stable carbon isotope value, the first component characteristic parameters and the second component characteristic parameters are constructed.

8. The method according to claim 3, characterized in that, The method further includes: The genetic components and their contribution ratios are matched with the geological strata information in the target area to determine the genetic contribution weights of different strata source rocks to the crude oil sample to be tested. By comparing the genetic contribution weights of different hydrocarbon source rocks to the crude oil sample under test, the layers that meet the preset threshold are identified as the main hydrocarbon source layers that play a dominant role in hydrocarbon accumulation. Based on the spatial distribution characteristics of the main hydrocarbon source strata, favorable oil and gas exploration areas within the target region are determined.

9. A device for determining mixed-source oil, characterized in that, include: The sample acquisition module is used to acquire reference end-member samples and crude oil samples to be tested in the target area; The parameter determination module is used to perform component detection on the reference end-member sample and the crude oil sample to be tested, respectively, and determine the first component characteristic parameter corresponding to the reference end-member sample and the second component characteristic parameter corresponding to the crude oil sample to be tested. The feature set determination module is used to select mutually exclusive feature pairs under geological genesis conditions based on the feature parameters of the first component, and to construct a geological genesis mutually exclusive feature set based on the mutually exclusive feature pairs. The mixed-source oil determination module is used to compare the second component characteristic parameters with the geologically exclusive feature set, determine whether the mutually exclusive feature pairs exist in the crude oil sample to be tested, and determine whether the crude oil sample to be tested is a mixed-source oil based on the determination result.

10. A computer-readable storage medium, characterized in that, It stores computer instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 8.

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