Method and device for determining mineral content of shale oil reservoir

Abstract

The invention discloses a method and device for determining the mineral content of a shale oil reservoir. The method comprises the steps that natural gamma-ray spectrum logging data and lithologic density logging data of a target reservoir are obtained; based on the natural gamma-ray spectrum logging data and the lithologic density logging data, obtaining the volume content of a natural gamma-ray response component, natural gamma-ray spectrum logging skeleton data and lithologic density logging skeleton data of the target reservoir; based on the volume content of the natural gamma response component, correcting the lithologic density logging visual skeleton data and the natural gamma-ray spectrum logging visual skeleton data, and based on the corrected lithologic density logging visual skeleton data and the natural gamma-ray spectrum logging visual skeleton data, obtaining the volume content of the unnatural gamma response component of the target reservoir; and obtaining the mineral content of the target reservoir according to the volume content of the non-natural gamma component and the volume content of the natural gamma response component of the target reservoir. The method can be used for universally and effectively evaluating the mineral content of the shale oil reservoir.

Description

Technical Field

[0001] The present invention relates to the technical field of shale oil logging evaluation, and particularly relates to a method and device for determining the mineral content of a shale oil reservoir. Background Art

[0002] Since the mineral composition of shale is of great significance to shale gas reservoir engineering construction (drilling, drilling fluid and reservoir stimulation), the research on the shale mineral composition in the prior art has been paid great attention to and deeply studied. However, due to the strong complexity of the lithology of the shale oil reservoir, large longitudinal and lateral variations, strong heterogeneity in the distribution and maturity of organic matter, etc., the mineral composition of the shale oil reservoir is complex and variable. How to effectively identify the mineral composition of the shale oil reservoir is one of the difficult problems in shale oil exploration and development.

[0003] In the existing logging mineral content evaluation technologies for shale reservoirs, there are methods for evaluating the mineral content of shale oil reservoirs by using logging instruments such as the Element Capture Spectroscopy Tool ECSTM, the Geochemical Element Logging Tool GEMTM, the Formation Lithology Tool FLeXTM, etc. or by using laboratory testing technologies, methods for evaluating the mineral content of shale oil reservoirs through laboratory testing technologies such as core analysis, methods for identifying the mineral composition of shale oil reservoirs through cuttings logging, and methods for obtaining the mineral content of shale oil reservoirs through the intersection or transformation of multiple logging responses. Summary of the Invention

[0004] The inventors of the present application have found that the method of using logging instruments to determine the mineral content of shale oil reservoirs can achieve certain effects in evaluating the mineral content of shale oil reservoirs, but there are problems such as high cost of testing instruments, which do not meet the requirements of economic development of shale oil reservoirs; the core analysis method can intuitively identify mineral components, but this method is limited by the core recovery rate, testing efficiency and economic cost, and it is difficult to obtain a continuous profile of the entire well section; the mineral composition identification results based on cuttings logging are interfered by factors such as drilling conditions and complex lamination structures, and the depth and lithology identification accuracy that can be achieved by cuttings logging are still a challenge; the method of obtaining mineral identification results through the intersection or transformation of multiple logging responses can realize the continuous evaluation of the mineral content of the entire well section of the shale oil reservoir, but this method depends on laboratory core testing of mineral content to build a model and calibrate the empirical coefficients of the model, and its extended application ability and applicability depend on the quantity and representativeness of core experimental data in the region, and the universality is not high. Therefore, there is a lack of a method in the prior art that can achieve continuous evaluation of the mineral content of the entire well section of the shale oil reservoir and has high universality.

[0005] In view of the above problems, the present invention is proposed to provide a method and device for determining the mineral content of a shale oil reservoir that can overcome the above problems or at least partially solve the above problems.

[0006] An embodiment of the present invention provides a method for determining the mineral content of a shale oil reservoir, including:

[0007] Obtaining natural gamma ray spectroscopy logging data and litho-density logging data of the target reservoir;

[0008] Based on the natural gamma ray spectroscopy logging data, obtaining the volume content of the natural gamma ray response components of the target reservoir;

[0009] Based on the natural gamma ray spectroscopy logging data and the litho-density logging data, obtaining the apparent matrix data of the natural gamma ray spectroscopy logging and the apparent matrix data of the litho-density logging;

[0010] Based on the volume content of the natural gamma ray response components, correcting the apparent matrix data of the litho-density logging and the apparent matrix data of the natural gamma ray spectroscopy logging to obtain the corrected apparent matrix data of the litho-density logging and the corrected apparent matrix data of the natural gamma ray spectroscopy logging;

[0011] Based on the corrected apparent matrix data of the litho-density logging and the corrected apparent matrix data of the natural gamma ray spectroscopy logging, obtaining the volume content of the non-natural gamma ray response components of the target reservoir;

[0012] According to the volume content of the non-natural gamma ray components and the volume content of the natural gamma ray response components of the target reservoir, obtaining the mineral content of the target reservoir.

[0013] In an alternative embodiment, based on the natural gamma ray spectroscopy logging data, obtaining the volume content of the natural gamma ray response components of the target reservoir; including:

[0014] Establishing a first logging response matrix, a first volume content matrix of the natural gamma ray response components of the target measurement point to be predicted, and a first relationship expression of a first logging response prediction matrix of specified elements; the first logging response matrix includes the logging response data of the specified elements of different natural gamma ray response component matrices, the first volume content matrix includes the volumes of different natural gamma ray response components of the target measurement point, and the first logging response prediction matrix includes the logging response prediction data of the specified elements of the target measurement point;

[0015] Based on the natural gamma ray spectroscopy logging data, determining a first volume content matrix that satisfies a preset first constraint condition set for the first relationship expression, and obtaining the volume content of the natural gamma ray response components of the target measurement point;

[0016] According to the volume content of the natural gamma ray response components of each target measurement point, obtaining the volume content of the natural gamma ray response components of the target reservoir.

[0017] In an alternative embodiment, the first constraint condition set includes:

[0018] Constraint condition 1: Make the volume content of each natural gamma response component at the target measurement point not less than zero, and use the obtained shale volume content data of the target measurement point as the constraint threshold for the clay volume content in the natural gamma response components of the target measurement point;

[0019] Constraint condition 2: Determine the first fitting error of all measurement points within the depth window range where the target measurement point is located, and minimize the first fitting error; the first fitting error is the sum of the squares of the differences between the measured well logging response data of the specified element at all measurement points within the depth window range and the predicted well logging response data of the corresponding specified element.

[0020] In an alternative embodiment, the natural gamma response components include: clay, mica, and potassium feldspar; the clay includes: potassium-poor clay and potassium-rich clay; the specified elements are thorium and potassium;

[0021] The formula for the first relationship expression of the established first well logging response matrix, the first volume content matrix of the natural gamma response components of the target measurement point to be predicted, and the first well logging response prediction matrix of the specified element is as follows:

[0022]

[0023] In the formula, Th cal is the predicted thorium well logging response data of the target measurement point, K cal is the predicted potassium well logging response data of the target measurement point; V cl is the volume content of potassium-poor clay at the target measurement point; V cl2 is the volume content of potassium-rich clay at the target measurement point; V mat is the volume content of mica at the target measurement point; V Felk is the volume content of potassium feldspar at the target measurement point; Th cl1 is the thorium well logging response of the potassium-poor clay skeleton; Th cl2 is the thorium well logging response of the potassium-rich clay skeleton; Th mat is the thorium well logging response of the mica skeleton; Th Felk is the thorium well logging response of the potassium feldspar skeleton; K cl1 is the potassium well logging response of the potassium-poor clay skeleton; K cl2 is the potassium well logging response of the potassium-rich clay skeleton; K mat is the potassium well logging response of the mica skeleton; K Felk is the potassium well logging response of the potassium feldspar skeleton.

[0024] In an alternative embodiment, the method for determining the mineral content of the shale oil reservoir further includes: obtaining the shale volume content data of the target measurement point based on the uranium-free gamma well logging data of the target measurement point included in the natural gamma energy spectrum well logging data.

[0025] In an alternative embodiment, based on the natural gamma ray spectrometry logging data and the litho-density logging data, apparent skeleton data of the natural gamma ray spectrometry logging and apparent skeleton data of the litho-density logging are obtained, including:

[0026] Based on the litho-density, photoelectric cross-section index, and volume cross-section index included in the litho-density logging data and the thorium-potassium ratio logging response data included in the natural gamma ray spectrometry logging data, apparent skeleton litho-density, apparent skeleton photoelectric cross-section index, apparent skeleton volume cross-section index included in the apparent skeleton data of the litho-density logging, and apparent skeleton thorium-potassium ratio logging response data included in the apparent skeleton data of the natural gamma ray spectrometry logging are correspondingly obtained.

[0027] Correspondingly,

[0028] Based on the volume content of the natural gamma ray response components, the apparent skeleton data of the litho-density logging and the apparent skeleton data of the natural gamma ray spectrometry logging are corrected to obtain corrected apparent skeleton data of the litho-density logging and corrected apparent skeleton data of the natural gamma ray spectrometry logging.

[0029] Based on the corrected apparent skeleton data of the litho-density logging and the corrected apparent skeleton data of the natural gamma ray spectrometry logging, the volume content of the non-natural gamma ray response components of the target reservoir is obtained, including:

[0030] Based on the volume content of the natural gamma ray response components, the apparent skeleton litho-density, apparent skeleton photoelectric cross-section index, apparent skeleton volume cross-section index included in the apparent skeleton data of the litho-density logging, and the apparent skeleton thorium-potassium ratio logging response data included in the natural gamma ray spectrometry logging data are corrected to obtain corrected apparent skeleton litho-density, apparent skeleton photoelectric cross-section index, apparent skeleton volume cross-section index, and apparent skeleton thorium-potassium ratio logging response data.

[0031] Based on the corrected apparent skeleton litho-density, apparent skeleton photoelectric cross-section index, apparent skeleton volume cross-section index, and apparent skeleton thorium-potassium ratio logging response data, the volume content of the non-natural gamma ray response components of the target reservoir is obtained.

[0032] In an alternative embodiment, the correction of the apparent skeleton litho-density, apparent skeleton photoelectric cross-section index, apparent skeleton volume cross-section index included in the litho-density logging data, and the apparent skeleton thorium-potassium ratio logging response data included in the natural gamma ray spectrometry logging data based on the volume content of the natural gamma ray response components to obtain corrected apparent skeleton litho-density, apparent skeleton photoelectric cross-section index, apparent skeleton volume cross-section response, and apparent skeleton thorium-potassium ratio logging response includes:

[0033] Based on the volume content of the natural gamma response components of each target measurement point in the target reservoir and combined with the following formula, the corrected apparent matrix lithology density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index, and apparent matrix thorium-potassium ratio logging response data of each target measurement point in the target reservoir are obtained;

[0034]

[0035] In the formula, and (Th / K) corr are the corrected apparent matrix lithology density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index, and apparent matrix thorium-potassium ratio logging response data of the target measurement point, respectively; ρ ma , U ma , P ema and TH / K ma are the apparent matrix lithology density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section response index, and apparent matrix thorium-potassium ratio logging response data of the target measurement point, respectively; (ρ cl1 ) ma , (U cl1 ) ma , (P ecl1 ) ma and (Th / K cl1 ) ma are the lithology density, photoelectric cross-section index, volume cross-section index, and thorium-potassium ratio logging response data of the potassium-poor clay matrix, respectively; (ρ cl2 ) ma , (U cl2 ) ma , (P ecl2 ) ma and (Th / K cl2 ) ma are the lithology density, photoelectric cross-section index, volume cross-section index, and thorium-potassium ratio logging response data of the potassium-rich clay matrix, respectively; (ρ mat ) ma , (U mat ) ma , (P emat ) ma and (Th / K mat ) ma are the lithology density, photoelectric cross-section index, volume cross-section index, and thorium-potassium ratio logging response data of the mica matrix, respectively; (ρ Felk ) ma , (U Felk ) ma , (P Felk ) ma and (Th / K Felk ) ma are the lithology density, photoelectric cross-section index, volume cross-section index, and thorium-potassium ratio logging response data of the potassium feldspar matrix, respectively; Vcl1 is the volume content of potassium-poor clay at the target measurement point; V cl2 is the volume content of potassium-rich clay at the target measurement point; V mat is the volume content of mica at the target measurement point; V Felk is the volume content of potassium feldspar at the target measurement point.

[0036] In an alternative embodiment, based on the corrected apparent matrix lithology density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index, and apparent matrix thorium-potassium ratio logging response data, the volume content of the non-natural gamma ray response components of the target reservoir is obtained, including:

[0037] Construct a second logging response matrix, which includes: the response data of the corrected apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio of different non-natural gamma ray response components at the target measurement points in the target reservoir;

[0038] Establish a second relationship expression among the second logging response matrix, the second volume content matrix of the non-natural gamma ray response components at the target measurement points to be predicted, and the constructed second logging response prediction matrix; the second volume content matrix includes the volumes of different non-natural gamma ray response components at the target measurement points, and the second logging response prediction matrix includes the predicted response data of the corrected apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio at the target measurement points;

[0039] Based on the corrected apparent matrix lithology density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index, and apparent matrix thorium-potassium ratio logging response data, determine the second volume content matrix that satisfies the preset second constraint condition set for the second relationship expression, and obtain the volume content of the non-natural gamma ray response components at the target measurement points;

[0040] According to the volume content of the non-natural gamma ray response components at each target measurement point, obtain the volume content of the non-natural gamma ray response components of the target reservoir.

[0041] In an alternative embodiment, the second constraint condition set includes:

[0042] Constraint condition three: make the volume content of the non-natural gamma ray response components at each target measurement point in the target reservoir satisfy the material balance relationship with the volume content of the natural gamma ray response components; and make the volume content of the non-natural gamma ray response components at each target measurement point respectively satisfy the volume content threshold range corresponding to each non-natural gamma ray response component in the target reservoir;

[0043] Constraint Four: Determine the second fitting errors of all measurement points within the depth window where the target measurement point is located, and minimize the second fitting errors; the second fitting error is the sum of the squares of the differences between the corrected logging response data of the apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio of all target measurement points within the depth window and the corresponding predicted corrected logging response data of the apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio.

[0044] In an alternative embodiment, the non-natural gamma response components include: feldspar minerals other than potassium feldspar, quartz, calcite, and dolomite;

[0045] The formula expressed by the established second relationship is as follows:

[0046]

[0047] In the formula, is the predicted corrected apparent matrix lithology density of the target measurement point; is the predicted corrected apparent matrix volume cross-section index of the target measurement point; is the predicted corrected apparent matrix photoelectric cross-section index of the target measurement point; is the predicted corrected logging response data of the apparent matrix thorium-potassium ratio of the target measurement point; (ρ Fel ) ma , (U Fel ) ma , (P eFel ) ma and (TH / K Fel ) ma are the logging response data of the apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio of feldspar minerals other than potassium feldspar of the target measurement point, respectively; (ρ Qart ) ma , (U Qart ) ma , (P eQart ) ma and (TH / K Qart ) ma are the logging response data of the apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio of quartz of the target measurement point, respectively; (ρ Cal ) ma , (U Cal ) ma , (P eCal ) ma and (TH / K Cal ) maWell logging response data of apparent skeleton lithology density, apparent skeleton volume cross-section index, apparent skeleton photoelectric cross-section index, and apparent skeleton thorium-potassium ratio of calcite at the target measurement point, respectively; (ρ Dol ) ma 、(U Dol ) ma 、(P eDol ) ma And (TH / K Dol ) ma Well logging response data of apparent skeleton lithology density, apparent skeleton volume cross-section index, apparent skeleton photoelectric cross-section index, and apparent skeleton thorium-potassium ratio of dolomite at the target measurement point, respectively.

[0048] In an optional embodiment, the mineral content includes: clay volume content, felsic volume content, and carbonate volume content;

[0049] According to the volume content of the non-natural gamma response components and the volume content of the natural gamma response components of the target reservoir, the mineral content of the target reservoir is calculated, including:

[0050] The clay volume content of the target reservoir is obtained according to the volume content of the potassium-rich clay and the volume content of the potassium-poor clay in the target reservoir;

[0051] The felsic volume content of the target reservoir is calculated according to the volume content of the potassium feldspar, the volume content of the feldspar other than the potassium feldspar, and the volume content of quartz in the target reservoir;

[0052] The carbonate volume content of the target reservoir is calculated according to the volume content of the calcite and the volume content of the dolomite in the target reservoir.

[0053] Based on the same inventive concept, an embodiment of the present invention further provides a device for determining the mineral content of a shale oil reservoir, including:

[0054] A data acquisition module, configured to acquire natural gamma energy spectrum well logging data and lithology density well logging data of the target reservoir;

[0055] A first calculation module, configured to obtain the volume content of the natural gamma response components of the target reservoir based on the natural gamma energy spectrum well logging data;

[0056] A second calculation module, based on the natural gamma energy spectrum well logging data and the lithology density well logging data, obtains natural gamma energy spectrum well logging apparent skeleton data and lithology density well logging apparent skeleton data;

[0057] A third calculation module, which corrects the apparent matrix data of the litho-density logging and the apparent matrix data of the natural gamma-ray spectroscopy logging based on the volume content of the natural gamma-ray response component, to obtain the corrected apparent matrix data of the litho-density logging and the corrected apparent matrix data of the natural gamma-ray spectroscopy logging;

[0058] A fourth calculation module, which obtains the volume content of the non-natural gamma-ray response component of the target reservoir based on the corrected apparent matrix data of the litho-density logging and the corrected apparent matrix data of the natural gamma-ray spectroscopy logging;

[0059] A fifth calculation module, which is used to calculate the mineral content of the target reservoir according to the volume content of the non-natural gamma-ray component of the target reservoir and the volume content of the natural gamma-ray response component.

[0060] Based on the same inventive concept, an embodiment of the present invention further provides a computer storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the above-mentioned method for determining the mineral content of a shale oil reservoir is implemented.

[0061] Based on the same inventive concept, an embodiment of the present invention further provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the above-mentioned method for determining the mineral content of a shale oil reservoir as claimed in the claims is implemented.

[0062] The beneficial effects of the above technical solutions provided by the embodiments of the present invention at least include:

[0063] The method for determining the mineral content of a shale oil reservoir provided by the embodiment of the present invention proposes a method for inversely calculating the mineral content of a shale oil reservoir by using litho-density logging data and natural gamma-ray logging response data. Since the litho-density logging data and the natural gamma-ray logging response data are the logging data of the entire well section of the target reservoir, the mineral content of the target reservoir obtained by using the method for determining the mineral content of a shale oil reservoir provided by the embodiment of the present invention is the mineral content of the entire well section of the target reservoir; and this method calculates the mineral content based on the litho-density logging data and the natural gamma-ray logging response data of the target reservoir, without the need to establish a rock physical volume model for the target reservoir, thereby being able to solve the problem that it is difficult to establish a unified rock physical volume model due to the complex and diverse mineral components and strong spatial distribution heterogeneity of the shale oil reservoir, and further resulting in the difficulty in promoting the use of the local model established based on a large amount of core analysis and test data across regions, and has high universality.

[0064] Other features and advantages of the present invention will be set forth in the following description, and in part will be obvious from the description, or may be learned by practice of the present invention. The objectives and other advantages of the present invention may be realized and attained by the structure particularly pointed out in the written description, claims, as well as the appended drawings.

[0065] The technical solution of the present invention will be further described in detail below with reference to the drawings and embodiments. Description of the Drawings

[0066] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0067] Figure 1 is a schematic flow chart of the method for determining the mineral content of a shale oil reservoir in an embodiment of the present invention;

[0068] Figure 2 is a comparison chart of the mineral content structure of a certain target reservoir obtained by using the method for determining the mineral content of a shale oil reservoir provided in the embodiment of the present invention and the mineral content results obtained by core analysis;

[0069] Figure 3 is a schematic diagram of the device for determining the mineral content of a shale oil reservoir in an embodiment of the present invention. Detailed Embodiments

[0070] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art.

[0071] Due to the characteristics of complex diversity and strong spatial distribution heterogeneity of the mineral components in shale oil reservoirs, it is difficult to establish a unified rock physics volume model, and the local models established based on a large amount of core analysis test data are difficult to be popularized and used across regions. There is a lack of a general and effective method for evaluating the mineral components of shale oil reservoirs in the prior art. Therefore, in order to solve the problems existing in the prior art, the embodiments of the present invention innovatively utilize the sensitive parameters of mineral content logging responses to provide a method and device for determining the mineral content of a shale oil reservoir, which uses litho-density logging data and natural gamma-ray spectroscopy logging data to invert the mineral content in the reservoir.

[0072] The method for determining the mineral content of a shale oil reservoir provided in the embodiment of the present invention, the flow chart thereof refers to Figure 1 as shown, and includes the following steps:

[0073] Step S101: Obtain the natural gamma-ray spectrometry logging data and litho-density logging data of the target reservoir;

[0074] Step S102: Based on the natural gamma-ray spectrometry logging data, obtain the volume content of the natural gamma-ray response components of the target reservoir;

[0075] Step S103: Based on the natural gamma-ray spectrometry logging data and litho-density logging data, obtain the apparent matrix data of the natural gamma-ray spectrometry logging and the apparent matrix data of the litho-density logging;

[0076] Step S104: Based on the volume content of the natural gamma-ray response components, correct the litho-density logging data and the apparent matrix data of the natural gamma-ray spectrometry logging to obtain the corrected litho-density logging data and the apparent matrix data of the natural gamma-ray spectrometry logging;

[0077] Step S105: Based on the corrected apparent matrix data of the litho-density logging and the apparent matrix data of the natural gamma-ray spectrometry logging, obtain the volume content of the non-natural gamma-ray response components of the target reservoir;

[0078] Step S106: According to the volume content of the non-natural gamma-ray components and the volume content of the natural gamma-ray response components of the target reservoir, obtain the mineral content of the target reservoir.

[0079] The lithology of the shale oil reservoir includes felsic shale, carbonaceous shale, clay shale and mixed shale. Among them, in felsic, in addition to potassium feldspar, there are also feldspar components such as albite that do not contain radioactive potassium elements and quartz; in carbonaceous, calcite and dolomite are rich; in clay, all clay types are contained. In addition, the reservoir also contains a small amount of minerals such as mica and analcime. It should be noted that the natural gamma-ray response components in the embodiments of the present invention are the mineral components of the shale oil reservoir that can provide the main contribution to the potassium radioactive element in the natural gamma-ray spectrometry logging; the non-natural gamma-ray response components are the components that provide the background contribution or no contribution to the potassium radioactive element in the natural gamma-ray spectrometry logging; specifically, in the embodiments of the present invention, the contribution of radioactive potassium in the natural gamma-ray spectrometry only comes from clay minerals, potassium feldspar and mica; the mineral components other than this only provide the background contribution (base value contribution) to the potassium radioactivity response; the organic matter and oil and gas in the reservoir do not contribute to the response of radioactive thorium and potassium in the natural energy spectrum.

[0080] The method for inverting the mineral content of shale oil reservoirs using litho-density logging data and natural gamma logging response data provided by the embodiments of the present invention. Since the litho-density logging data and natural gamma logging response data are the logging data of the entire well section of the target reservoir, the mineral content of the target reservoir obtained by using the method for determining the mineral content of shale oil reservoirs provided by the embodiments of the present invention is the mineral content of the entire well section of the target reservoir. Moreover, this method calculates the mineral content based on the litho-density logging data and natural gamma logging response data of the target reservoir, without the need to establish a rock physics volume model for the target reservoir. Thus, it can solve the problem that it is difficult to establish a unified rock physics volume model due to the complex and diverse mineral components and strong spatial distribution heterogeneity of shale oil reservoirs, and the resulting local models established based on a large amount of core analysis and test data are difficult to be widely used across regions, and has high universality.

[0081] Among them, in step S101, the specific process of obtaining the natural gamma ray spectrometry logging data and litho-density logging data of the target reservoir can be as follows: Drill at least one well from the ground into the underground formation, with the drilling depth covering the shale oil reservoir (i.e., the target reservoir) to be studied, and select an economical and effective logging series to implement comprehensive logging. Among them, the logging series includes at least natural gamma ray spectrometry logging and litho-density logging to obtain natural gamma ray spectrometry logging data and litho-density logging data. Compared with the traditional natural gamma (GR) logging, which can only reflect the total effect of all radioactive nuclides in the formation and cannot distinguish the types and contents of radioactive nuclides contained in the formation, the method of natural gamma ray spectrometry logging can quantitatively measure the contents of uranium (U), thorium (Th), and potassium (K) in the formation and give the total gamma radioactivity intensity of the formation. The data measured by natural gamma ray spectrometry logging can be used to study the formation characteristics more accurately, and thus the data obtained when conducting mineral content analysis can be more accurate.

[0082] Optionally, in order to ensure the longitudinal resolution ability of the shale oil reservoir structure, the logging sampling (i.e., adjacent target measurement points) interval is controlled within 0.125 m, so as to distinguish the laminar combination of shale oil reservoirs with a thickness within 0.2 m.

[0083] In step S102, based on the natural gamma ray spectrometry logging data, obtain the volume content of the natural gamma response components of the target reservoir, including:

[0084] Establish the first relationship expression among the first logging response matrix, the first volume content matrix of the natural gamma response components of the target measurement point to be predicted, and the logging response prediction matrix of the specified element. Among them, the first logging response matrix includes the logging response data of the specified elements of different natural gamma response component skeletons; the first volume content matrix includes the volumes of different natural gamma response components of the target measurement point, and the first logging response prediction matrix includes the logging response prediction data of the specified elements of the target measurement point.

[0085] Based on the natural gamma ray spectrometry logging data, determine a volume content matrix that satisfies a preset first set of constraint conditions for the first relationship expression, and obtain the volume content of the natural gamma ray response components at the target measurement point;

[0086] According to the volume content of the natural gamma ray response components at each target measurement point, obtain the volume content of the natural gamma ray response components in the target reservoir.

[0087] Further, the first set of constraint conditions includes:

[0088] Constraint condition 1: The volume content of each natural gamma ray response component at the target measurement point is not less than zero, and the obtained shale volume content data of the target measurement point is used as the constraint threshold for the clay volume content in the natural gamma ray response components of the target measurement point;

[0089] Constraint condition 2: Determine the first fitting error for all measurement points within the depth window where the target measurement point is located, and minimize the first fitting error; the first fitting error is the sum of the squares of the differences between the measured logging response data of the specified element and the predicted logging response data of the corresponding specified element for all measurement points within the depth window where the target measurement point is located.

[0090] Among them, the expression of constraint condition 1 can be as follows:

[0091]

[0092] V Cl1 +V Cl2 ≤V SH

[0093] In formulas (1) and (2), V cl1 is the volume content of potassium-poor clay at the target measurement point; V cl2 is the volume content of potassium-rich clay at the target measurement point; V mat is the volume content of mica at the target measurement point; V Felk is the volume content of potassium feldspar at the target measurement point, V SH is the shale volume content at the target measurement point.

[0094] In an alternative embodiment, the specified elements when calculating the volume content of the natural gamma ray response components in the embodiments of the present invention include: thorium element and potassium element; correspondingly, the first fitting error is the sum of the squares of the differences between the measured thorium logging response data and the predicted thorium logging response data, and the measured potassium logging response data and the predicted potassium logging response data for all measurement points within the depth window; at this time, the calculation formula for the first fitting error is:

[0095]

[0096] Wherein, Φ is the first fitting error, N is the total number of measured points within a certain depth window, and are respectively the measured data and predicted data of the thorium logging response of the i-th target measured point within a certain depth window; and are respectively the measured data and predicted data of the potassium logging response of the i-th target measured point within a certain depth window; wherein, within a certain depth window is within the depth window where the target measured point is located, and the measured data of the thorium logging response and the measured data of the potassium logging response can be obtained according to the natural gamma ray spectroscopy logging data.

[0097] Optionally, the natural gamma ray response components of the embodiments of the present invention include: clay, mica and potassium feldspar; the clay includes: potassium-poor clay and potassium-rich clay; when solving the volume content of the natural gamma ray response components, the specified elements used are thorium element and potassium element; correspondingly,

[0098] The formula for expressing the first relationship among the first logging response matrix established, the first volume content matrix of the natural gamma ray response components of the target measured point to be predicted, and the first logging response prediction matrix of the specified elements is as follows:

[0099]

[0100] Wherein, Th cal is the predicted data of the thorium logging response of the target measured point, K cal is the predicted data of the potassium logging response of the target measured point, V cl1 is the volume content of potassium-poor clay of the target measured point; V cl2 is the volume content of potassium-rich clay of the target measured point; V mat is the volume content of mica of the target measured point; V Felk is the volume content of potassium feldspar of the target measured point; Th cl1 is the thorium logging response of the potassium-poor clay skeleton; Th cl2 is the thorium logging response of the potassium-rich clay skeleton; Th mat is the thorium logging response of the mica skeleton; Th Felk is the thorium logging response of the potassium feldspar skeleton; K cl1 is the potassium logging response of the potassium-poor clay skeleton; K cl2 is the potassium logging response of the potassium-rich clay skeleton; K mat is the potassium logging response of the mica skeleton; K Felk is the potassium logging response of the potassium feldspar skeleton. Among them, for the logging response data of the specified elements of the skeletons of different natural gamma ray response components in the formula, it can be specifically calculated through the mineral content skeleton data table, and for the specific calculation process of the skeleton data, reference can be made to the prior art, and the embodiments of the present invention do not limit this.

[0101] In an optional embodiment, before constructing Constraint Condition 1, it may further include: obtaining the shale volume data of the target measurement point based on the uranium-free gamma logging data of the target measurement point included in the natural gamma ray spectroscopy logging data.

[0102] Specifically, the shale volume data can be calculated by the following formula:

[0103]

[0104]

[0105] In the formula, GCUR is a dimensionless empirical coefficient; KTH is the uranium-free gamma logging data of the target measurement point of the target reservoir; KTH min is the uranium-free gamma logging data of the pure sandstone section of the target reservoir, API; KTH max is the uranium-free gamma logging data of the pure shale section of the target reservoir, API; SH is a dimensionless shale index; V SH is the shale volume content data of the target measurement point, %.

[0106] Among them, the dimensionless empirical coefficient GCUR can be an empirical value. For example, the dimensionless empirical coefficient for the Tertiary formation is 3.7, and for the old formation, the dimensionless empirical coefficient is 2.0; it can also be obtained by statistical analysis of actual data, and the embodiments of the present invention do not make specific limitations in this regard. Further, the uranium-free gamma logging data of the target measurement point of the target reservoir, the uranium-free gamma logging data of the pure sandstone section of the target reservoir, and the uranium-free gamma logging data of the pure shale section can be obtained from the natural gamma ray spectroscopy logging data obtained in the natural gamma ray spectroscopy logging.

[0107] Optionally, in step S103, based on the natural gamma ray spectroscopy logging data and the litho-density logging data, obtaining the natural gamma ray spectroscopy logging apparent matrix data and the litho-density logging apparent matrix data may specifically include: based on the litho-density, photoelectric cross-section index, and volume cross-section index included in the litho-density logging data and the thorium-potassium ratio logging response data included in the natural gamma ray spectroscopy logging data, correspondingly obtaining the apparent matrix litho-density, apparent matrix photoelectric cross-section index, and apparent matrix volume cross-section index included in the litho-density logging apparent matrix data and the apparent matrix thorium-potassium ratio logging response data included in the natural gamma ray spectroscopy logging apparent matrix data;

[0108] Among them, for the specific process of obtaining the natural gamma ray spectroscopy logging apparent matrix data from the natural gamma ray spectroscopy logging data, reference can be made to the prior art, and the embodiments of the present invention do not make specific limitations in this regard.

[0109] In an optional embodiment, in step S104, based on the volume content of the natural gamma response component, the apparent matrix data of the litho-density logging and the apparent matrix data of the natural gamma-ray spectrometry logging are corrected to obtain the corrected apparent matrix data of the litho-density logging and the apparent matrix data of the natural gamma-ray spectrometry logging; including:

[0110] Based on the volume content of the natural gamma response component, the apparent matrix litho-density, the apparent matrix photoelectric cross-section index, the apparent matrix volume cross-section index included in the apparent matrix data of the litho-density logging, and the apparent matrix thorium-potassium ratio logging response data included in the natural gamma-ray spectrometry logging data are corrected to obtain the corrected apparent matrix litho-density, the apparent matrix photoelectric cross-section index, the apparent matrix volume cross-section index, and the apparent matrix thorium-potassium ratio logging response data;

[0111] In step S105, based on the corrected apparent matrix data of the litho-density logging and the apparent matrix data of the natural gamma-ray spectrometry logging, the volume content of the non-natural gamma response component of the target reservoir is obtained; including:

[0112] Based on the corrected apparent matrix litho-density, the apparent matrix photoelectric cross-section index, the apparent matrix volume cross-section index, and the apparent matrix thorium-potassium ratio logging response data, the volume content of the non-natural gamma response component of the target reservoir is obtained.

[0113] Further, based on the volume content of the natural gamma response component, the apparent matrix litho-density, the apparent matrix photoelectric cross-section index, the apparent matrix volume cross-section index included in the litho-density logging data, and the apparent matrix thorium-potassium ratio logging response data included in the natural gamma-ray spectrometry logging data are corrected to obtain the corrected apparent matrix litho-density, the apparent matrix photoelectric cross-section index, the apparent matrix volume cross-section response, and the apparent matrix thorium-potassium ratio logging response; including:

[0114] Based on the volume content of the natural gamma response component of each target measurement point in the target reservoir and combined with the following formula, the corrected apparent matrix litho-density, the apparent matrix photoelectric cross-section index, the apparent matrix volume cross-section index, and the apparent matrix thorium-potassium ratio logging response data of each target measurement point in the target reservoir are obtained, which are the corrected apparent matrix litho-density, the apparent matrix photoelectric cross-section index, the apparent matrix volume cross-section index, and the apparent matrix thorium-potassium ratio logging response data measured at each target measurement point;

[0115]

[0116] In the formula, and (Th / K) corr are the corrected apparent matrix litho-density, the apparent matrix photoelectric cross-section index, the apparent matrix volume cross-section index, and the apparent matrix thorium-potassium ratio logging response data of the target measurement point respectively; ρ ma 、U ma 、P ema and TH / Kma They are the logging response data of the apparent matrix lithology density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section response index, and apparent matrix thorium-potassium ratio of the target measurement point; (ρ cl1 ) ma , (U cl1 ) ma , (P ecl1 ) ma , and (Th / K cl1 ) ma They are the logging response data of the lithology density, photoelectric cross-section index, volume cross-section index, and thorium-potassium ratio of the poor-potassium clay matrix; (ρ cl2 ) ma , (U cl2 ) ma , (P ecl2 ) ma , and (Th / K cl2 ) ma They are the logging response data of the lithology density, photoelectric cross-section index, volume cross-section index, and thorium-potassium ratio of the potassium-rich clay matrix; (ρ mat ) ma , (U mat ) ma , (P emat ) ma , and (Th / K mat ) ma They are the logging response data of the lithology density, photoelectric cross-section index, volume cross-section index, and thorium-potassium ratio of the mica matrix; (ρ Felk ) ma , (U Felk ) ma , (P Felk ) ma , and (Th / K Felk ) ma They are the logging response data of the lithology density, photoelectric cross-section index, volume cross-section index, and thorium-potassium ratio of the potassium feldspar matrix; V cl is the volume content of poor-potassium clay at the target measurement point; V cl is the volume content of potassium-rich clay at the target measurement point; V mat is the volume content of mica at the target measurement point; V Felk is the volume content of potassium feldspar at the target measurement point.

[0117] Among them, for the logging response data of the lithology density, photoelectric cross-section index, volume cross-section index, and thorium-potassium ratio of the matrices of poor-potassium clay, potassium-rich clay, potassium feldspar, and mica, they are determined values and can be obtained by referring to the means of the prior art. The embodiments of the present invention do not make specific limitations on this.

[0118] In an alternative embodiment, based on the corrected apparent matrix lithology density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index, and apparent matrix thorium-potassium ratio logging response data, the volume content of the non-natural gamma response components of the target reservoir is obtained, including:

[0119] Construct a second logging response matrix, where the second logging response matrix includes: the response data of the corrected apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio of different non-natural gamma response components at the target measurement points in the target reservoir;

[0120] Establish a second relationship expression among the second logging response matrix, the second volume content matrix of the non-natural gamma response components of the target measurement points to be predicted, and the second logging response prediction matrix constructed; the second volume content matrix includes the volumes of different non-natural gamma response components at the target measurement points, and the second logging response prediction matrix includes the response data of the predicted corrected apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio of the target measurement points;

[0121] Based on the corrected apparent matrix lithology density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index, and apparent matrix thorium-potassium ratio logging response data, determine the second volume content matrix that satisfies the preset second constraint condition set for the second relationship expression, and obtain the volume content of the non-natural gamma response components of the target measurement points;

[0122] According to the volume content of the non-natural gamma response components of each target measurement point, obtain the volume content of the non-natural gamma response components of the target reservoir.

[0123] In an alternative embodiment, the second constraint condition set includes:

[0124] Constraint condition three: make the volume content of the non-natural gamma response components of each target measurement point in the target reservoir satisfy the material balance relationship with the volume content of the natural gamma response components; and make the volume content of the non-natural gamma response components of each target measurement point respectively satisfy the volume content threshold range corresponding to each non-natural gamma response component in the target reservoir; among them, the volume content threshold range corresponding to each non-natural gamma response component in the target reservoir can be obtained through cuttings logging or core analysis.

[0125] Constraint condition four: determine the second fitting error of all measurement points within the depth window where the target measurement point is located, and minimize the second fitting error; the second fitting error is the sum of the squares of the differences between the corrected apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio logging response data of all target measurement points within the depth window and the corresponding predicted corrected apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio logging response data.

[0126] In an optional embodiment, the non-natural gamma response components include: feldspar minerals other than potassium feldspar, quartz, calcite, and dolomite; in Constraint 3, the volume contents of the non-natural gamma response components at each target measurement point are respectively made to satisfy the volume content threshold ranges corresponding to the non-natural gamma response components in the target reservoir, and the formula is as follows:

[0127]

[0128] The volume contents of the non-natural gamma response components at each target measurement point in the target reservoir and the volume contents of the natural gamma response components satisfy the following material balance relationship:

[0129] V Fel +V Qart +V Cal +V Dol =1-V Felk -V mat -V Cl1 -V Cl2 ;

[0130] In the formula, V Fel ,V Qart ,V Cal ,V Dol are respectively the volume contents of feldspar minerals other than potassium feldspar, quartz, calcite, and dolomite; V Fel (min),V Qart (min),V Cal (min),V Dol (min) are respectively the minimum values of the volume contents of feldspar minerals other than potassium feldspar, quartz, calcite, and dolomite in the target reservoir; V Fel (max),V Qart (max),V Cal (max),V Dol (max) are respectively the maximum values of the volume contents of feldspar minerals other than potassium feldspar, quartz, calcite, and dolomite in the target reservoir.

[0131] The formula for Constraint 4 is as follows:

[0132]

[0133] In the formula, Φ1 is the second fitting error, are respectively the measured corrected apparent matrix lithology density and the predicted corrected apparent matrix lithology density of the i-th target measurement point within a certain depth window range; are respectively the measured corrected apparent matrix volume cross-section index and the predicted corrected apparent matrix volume cross-section index of the i-th target measurement point within a certain depth window range;; The measured and corrected apparent skeleton photoelectric cross-section index and the predicted and corrected apparent skeleton photoelectric cross-section index of the i-th target measurement point within a certain depth window range, respectively; The measured and corrected apparent skeleton thorium-potassium ratio response data and the predicted and corrected apparent skeleton thorium-potassium ratio response data of the i-th target measurement point within a certain depth window range, respectively.

[0134] In an optional embodiment, the non-natural gamma response components include: feldspar minerals other than potassium feldspar, quartz, calcite, and dolomite;

[0135] The formula for constructing the second relationship expression is as follows:

[0136]

[0137] In the formula, is the predicted and corrected apparent skeleton litho-density of the target measurement point; is the predicted and corrected apparent skeleton volume cross-section index of the target measurement point; is the predicted and corrected apparent skeleton photoelectric cross-section index of the target measurement point; is the predicted and corrected apparent skeleton thorium-potassium ratio log response data of the target measurement point; (ρ Fel ) ma , (U Fel ) ma , (P eFel ) ma and (TH / K Fel ) ma are the log response data of the apparent skeleton litho-density, apparent skeleton volume cross-section index, apparent skeleton photoelectric cross-section index, and apparent skeleton thorium-potassium ratio of feldspar minerals other than potassium feldspar at the target measurement point; (ρ Qart ) ma , (U Qart ) ma , (P eQart ) ma and (TH / K Qart ) ma are the log response data of the apparent skeleton litho-density, apparent skeleton volume cross-section index, apparent skeleton photoelectric cross-section index, and apparent skeleton thorium-potassium ratio of quartz at the target measurement point; (ρ Cal ) ma , (U Cal ) ma , (P eCal ) ma and (TH / K Cal ) ma are the log response data of the apparent skeleton litho-density, apparent skeleton volume cross-section index, apparent skeleton photoelectric cross-section index, and apparent skeleton thorium-potassium ratio of calcite at the target measurement point; (ρ Dol) ma and (U Dol ) ma and (P eDol ) ma and (TH / K Dol ) ma are respectively the logging response data of the apparent skeleton lithology density, apparent skeleton volume cross-section index, apparent skeleton photoelectric cross-section index and apparent skeleton thorium-potassium ratio of dolomite at the target measurement point.

[0138] Among them, the logging response data of the apparent skeleton lithology density, apparent skeleton photoelectric cross-section index, apparent skeleton volume cross-section index and apparent skeleton thorium-potassium ratio of feldspar minerals except potassium feldspar, quartz, calcite and mica at the target measurement point can be obtained by referring to the means of the prior art, and the embodiments of the present invention do not make specific limitations thereon.

[0139] In an alternative embodiment, the mineral content of the shale oil target reservoir includes: clay volume content, felsic volume content and carbonate volume content; in step S106,

[0140] According to the volume content of the non-natural gamma response components and the volume content of the natural gamma response components of the target reservoir, the mineral content of the target reservoir is calculated, including:

[0141] The clay volume content of the target reservoir is obtained according to the volume content of the potassium-rich clay and the volume content of the potassium-poor clay in the target reservoir;

[0142] The felsic volume content of the target reservoir is calculated according to the volume content of potassium feldspar, the volume content of feldspar other than potassium feldspar and the volume content of quartz in the target reservoir;

[0143] The carbonate volume content of the target reservoir is calculated according to the volume content of calcite and the volume content of dolomite in the target reservoir.

[0144] Specifically, the following formula is used to sum the volume content of potassium-rich clay and the volume content of potassium-poor clay obtained for the target reservoir to obtain the clay volume content of the target reservoir:

[0145] V Cl =V Cl1 +V Cl2

[0146] In the formula, V Cl is the clay volume content in the target reservoir.

[0147] Specifically, the following formula is used to sum the volume content of potassium-rich feldspar and the volume content of feldspar other than potassium feldspar obtained for the target reservoir to obtain the total feldspar volume content in the target reservoir:

[0148] V tFel =VFel +V Felk

[0149] wherein, V tFel is the total volume content of feldspar in the target reservoir.

[0150] After obtaining the total volume content of feldspar, the following formula is used to sum up the volume content of the total feldspar and the volume content of quartz to obtain the volume content of felsic in the target reservoir:

[0151] V Fel_Qart = V tFel + V Qart ;

[0152] wherein, V Fel_Qart is the volume content of felsic in the target reservoir.

[0153] The following formula is used to sum up the volume content of calcite and the volume content of dolomite obtained to calculate the volume content of carbonate in the target reservoir.

[0154] V Carb = V Cal + V Dol ;

[0155] wherein, V Carb is the volume content of carbonate in the shale oil formation.

[0156] The method for determining the mineral content of a shale oil reservoir provided by the embodiment of the present invention, after obtaining the logging data of the target reservoir (including at least: natural gamma ray spectrometry logging data and litho-density logging data), calculates the shale volume content according to the natural gamma ray response in the natural gamma ray spectrometry logging data as the maximum value constraint of the volume content of clay (including potassium-poor clay and potassium-rich clay); according to the thorium and potassium responses of the skeletons of potassium-rich clay, potassium-poor clay, mica and potassium feldspar, and using the calculated shale volume content as a constraint, simultaneously inversely obtains the volume contents of potassium-rich clay, potassium-poor clay, mica and potassium feldspar by using the thorium response and potassium response in the natural gamma ray spectrometry logging data; based on the volume content results of the calculated clay, mica and potassium feldspar, corrects the apparent skeleton litho-density, apparent skeleton photoelectric cross-section index Pe, apparent skeleton volume cross-section response U included in the obtained litho-density logging apparent skeleton data, and the apparent skeleton thorium-potassium ratio response data in the natural gamma ray spectrometry logging apparent skeleton data, to obtain the corrected apparent skeleton photoelectric cross-section index Pe, apparent skeleton volume cross-section response U, apparent skeleton litho-density and apparent skeleton thorium-potassium ratio response data; constructs a constraint equation for the volume content according to the maximum and minimum volume fractions of the rock minerals in the entire target reservoir and the material balance equation, and inversely obtains the contents of feldspar other than potassium feldspar, calcite and dolomite outside quartz by using the logging response equations of the corrected apparent skeleton litho-density, apparent skeleton photoelectric cross-section index Pe, apparent skeleton volume cross-section index U and apparent skeleton thorium-potassium ratio response data; finally, sums the calculated potassium-rich clay and potassium-poor clay to obtain the total clay content of the target reservoir; sums the volume content of the obtained potassium-rich feldspar, the volume content of feldspar other than potassium feldspar and the volume content of quartz to obtain the felsic volume content of the target reservoir, and obtains the carbonate volume content of the target reservoir according to the calculated volume content of calcite and the volume content of dolomite; that is, by using the method provided by the embodiment of the present invention, the volume contents of clay, felsic and carbonate of the target reservoir can finally be output.

[0157] Refer to Figure 2 As shown in the figure, it is a schematic diagram of the comparison between the method for determining the shale mineral content provided by the embodiment of the present invention and the core analysis results for a certain section of the shale oil reservoir; specifically, in Figure 2Among them, the first column is the depth column of a certain shale oil reservoir section, the second and third columns are the logging curve data of this shale oil reservoir section, and the fourth, fifth, sixth, and seventh columns are the dolomite volume content data, calcite volume content data, feldspar volume content data other than potassium feldspar, and quartz volume content data of this shale oil reservoir section respectively; among them, the curves in the fourth, fifth, sixth, and seventh columns represent the dolomite, calcite, feldspar other than potassium feldspar, and quartz volume content data of this shale oil reservoir section obtained by the method of the embodiment of the present invention, and the straight lines represent the dolomite, calcite, feldspar other than potassium feldspar, and quartz volume content data of each target measuring point in this shale oil reservoir section obtained by core analysis.

[0158] From Figure 2 It can be seen that the coincidence rate of the volume content data of dolomite, calcite, feldspar other than potassium feldspar, and quartz obtained by the method of the embodiment of the present invention and the data measured by core analysis is very good. From this, it can be concluded that the method for determining the mineral content of the volume shale reservoir by using the method for determining the mineral content of the shale oil reservoir provided by the embodiment of the present invention is feasible and has high accuracy.

[0159] In view of the calculation problem of the volume content of mineral components in organic-rich shale oil reservoirs with complex and variable lithological mineral components and strong spatial distribution heterogeneity, the embodiment of the present invention proposes a method for determining the mineral content of shale oil reservoirs. By using natural gamma ray spectrometry logging and litho-density logging data, it calculates the contents of potassium-rich clay, potassium-poor clay, mica, potassium feldspar, quartz, albite, calcite, and dolomite in the shale oil reservoir, and realizes the logging calculation of the mineral content of the shale oil reservoir. The method provided by the embodiment of the present invention provides a convenient means for determining the mineral components of the shale oil reservoir by using natural gamma ray spectrometry and litho-density logging data, and various parameters in the present invention can be obtained based on logging data and laboratory sample test data. By using natural gamma ray spectrometry and litho-density logging data and the two-step inversion method, the volume content of the mineral components of the shale oil reservoir can be quickly and accurately inverted, with strong pertinence and practicability, enriching the logging lithology and lithofacies evaluation technical means for the exploration and development of shale oil reservoirs, and having great practical value in the exploration and development of shale oil.

[0160] Based on the same inventive concept, the embodiment of the present invention also provides a device for determining the mineral content of a shale oil reservoir. Referring to Figure 3 as shown, it includes:

[0161] A data acquisition module 11, configured to acquire natural gamma ray spectrometry logging data and litho-density logging data of a target reservoir;

[0162] A first calculation module 12, configured to obtain the volume content of the natural gamma ray response components of the target reservoir based on the natural gamma ray spectrometry logging data;

[0163] The second calculation module 13 obtains the natural gamma ray spectroscopy logging apparent matrix data and the litho-density logging apparent matrix data based on the natural gamma ray spectroscopy logging data and the litho-density logging data;

[0164] The third calculation module 14 corrects the litho-density logging apparent matrix data and the natural gamma ray spectroscopy logging apparent matrix data based on the volume content of the natural gamma ray response components, and obtains the corrected litho-density logging apparent matrix data and the natural gamma ray spectroscopy logging apparent matrix data;

[0165] The fourth calculation module 15 obtains the volume content of the non-natural gamma ray response components of the target reservoir based on the corrected litho-density logging apparent matrix data and the natural gamma ray spectroscopy logging apparent matrix data;

[0166] The fifth calculation module 16 is used to calculate the mineral content of the target reservoir according to the volume content of the non-natural gamma ray components and the volume content of the natural gamma ray response components of the target reservoir.

[0167] Regarding the shale oil reservoir mineral content determination device in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0168] Based on the same inventive concept, an embodiment of the present invention further provides a computer storage medium, in which computer executable instructions are stored, and when the computer executable instructions are executed by a processor, the above-mentioned shale oil reservoir mineral content determination method is implemented.

[0169] Based on the same inventive concept, an embodiment of the present invention further provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the above-mentioned shale oil reservoir mineral content determination method is implemented.

[0170] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0171] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general purpose computers, special purpose computers, embedded processors, or other programmable data processing devices to produce a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices produce means for implementing the functions specified in the flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more blocks.

[0172] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including instruction means for implementing the functions specified in the flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more blocks.

[0173] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are performed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in the flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more blocks.

[0174] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these changes and modifications.

Claims

1. A method for determining the mineral content of a shale oil reservoir, characterized in that, Including: Obtaining natural gamma ray spectrometry logging data and litho-density logging data of a target reservoir; Based on the natural gamma ray spectrometry logging data, obtaining the volume content of natural gamma ray response components of the target reservoir; Based on the natural gamma ray spectrometry logging data and the litho-density logging data, obtaining natural gamma ray spectrometry logging apparent matrix data and litho-density logging apparent matrix data; Based on the volume content of the natural gamma ray response components, correcting the litho-density logging apparent matrix data and the natural gamma ray spectrometry logging apparent matrix data to obtain corrected litho-density logging apparent matrix data and natural gamma ray spectrometry logging apparent matrix data; Based on the corrected litho-density logging apparent matrix data and the natural gamma ray spectrometry logging apparent matrix data, obtaining the volume content of non-natural gamma ray response components of the target reservoir; According to the volume content of non-natural gamma ray components and the volume content of natural gamma ray response components of the target reservoir, obtaining the mineral content of the target reservoir.

2. The method for determining the mineral content of a shale oil reservoir according to claim 1, characterized in that, Based on the natural gamma ray spectrometry logging data, obtaining the volume content of natural gamma ray response components of the target reservoir; including: Establishing a first relationship expression among a first logging response matrix, a first volume content matrix of natural gamma ray response components of a target measurement point to be predicted, and a first logging response prediction matrix of a specified element; the first logging response matrix includes logging response data of specified elements of different natural gamma ray response component matrices, the first volume content matrix includes the volumes of different natural gamma ray response components of the target measurement point, and the first logging response prediction matrix includes logging response prediction data of the specified element of the target measurement point; Based on the natural gamma ray spectrometry logging data, determining a first volume content matrix that satisfies a preset first constraint condition set for the first relationship expression to obtain the volume content of natural gamma ray response components of the target measurement point; According to the volume content of natural gamma ray response components of each target measurement point, obtaining the volume content of natural gamma ray response components of the target reservoir.

3. The method for determining the mineral content of a shale oil reservoir according to claim 2, characterized in that, The first constraint condition set includes: Constraint condition 1: Making the volume content of each natural gamma ray response component of the target measurement point not less than zero, and using the obtained shale volume content data of the target measurement point as the constraint threshold of the clay volume content in the natural gamma ray response components of the target measurement point; Constraint condition 2: Determining the first fitting error of all measurement points within the depth window range where the target measurement point is located to minimize the first fitting error; the first fitting error is the sum of squares of the differences between the measured logging response data of the specified element of all measurement points within the depth window range and the corresponding predicted logging response data of the specified element.

4. The method for determining the mineral content of a shale oil reservoir according to claim 2, characterized in that, The natural gamma ray response components include: clay, mica, and potassium feldspar; the clay includes: potassium-poor clay and potassium-rich clay; the specified elements are thorium element and potassium element; The formula of the first relationship expression established among the first logging response matrix, the first volume content matrix of natural gamma ray response components of the target measurement point to be predicted, and the first logging response prediction matrix of the specified element is as follows: where Th cal is the predicted data of thorium logging response at the target measurement point, and K cal is the predicted data of potassium logging response at the target measurement point; V cl1 is the volume content of potassium-poor clay at the target measurement point; V cl2 is the volume content of potassium-rich clay at the target measurement point; V mat is the volume content of mica at the target measurement point; V Felk is the volume content of potassium feldspar at the target measurement point; Th cl1 is the thorium logging response of the potassium-poor clay matrix; Th cl2 is the thorium logging response of the potassium-rich clay matrix; Th mat is the thorium logging response of the mica matrix; Th Felk is the thorium logging response of the potassium feldspar matrix; K cl1 is the potassium logging response of the potassium-poor clay matrix; K cl2 is the potassium logging response of the potassium-rich clay matrix; K mat is the potassium logging response of the mica matrix; K Felk is the potassium logging response of the potassium feldspar matrix.

5. The method for determining the mineral content of a shale oil reservoir according to claim 3, characterized in that, Also including: Based on the uranium-free gamma ray logging data of the target measurement point included in the natural gamma ray spectrometry logging data, obtaining the shale volume content data of the target measurement point.

6. The method for determining the mineral content of a shale oil reservoir according to claim 4, characterized in that, Based on the natural gamma ray spectrometry logging data and the litho-density logging data, obtain the apparent matrix data of the natural gamma ray spectrometry logging and the apparent matrix data of the litho-density logging, including: Based on the litho-density, photoelectric cross-section index, and volume cross-section index included in the litho-density logging data and the thorium-potassium ratio logging response data included in the natural gamma ray spectrometry logging data, correspondingly obtain the apparent matrix litho-density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index included in the apparent matrix data of the litho-density logging, and the apparent matrix thorium-potassium ratio logging response data included in the apparent matrix data of the natural gamma ray spectrometry logging; Correspondingly, Based on the volume content of the natural gamma ray response components, correct the apparent matrix data of the litho-density logging and the apparent matrix data of the natural gamma ray spectrometry logging to obtain the corrected apparent matrix data of the litho-density logging and the corrected apparent matrix data of the natural gamma ray spectrometry logging; Based on the corrected apparent matrix data of the litho-density logging and the corrected apparent matrix data of the natural gamma ray spectrometry logging, obtain the volume content of the non-natural gamma ray response components of the target reservoir, including: Based on the volume content of the natural gamma ray response components, correct the apparent matrix litho-density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index included in the apparent matrix data of the litho-density logging, and the apparent matrix thorium-potassium ratio logging response data included in the natural gamma ray spectrometry logging data to obtain the corrected apparent matrix litho-density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index, and apparent matrix thorium-potassium ratio logging response data; Based on the corrected apparent matrix litho-density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index, and apparent matrix thorium-potassium ratio logging response data, obtain the volume content of the non-natural gamma ray response components of the target reservoir.

7. The method for determining the mineral content of a shale oil reservoir according to claim 6, characterized in that, Based on the volume content of the natural gamma ray response components, correct the apparent matrix litho-density, apparent matrix photoelectric cross-section index, and apparent matrix volume cross-section index included in the litho-density logging data, and the apparent matrix thorium-potassium ratio logging response data included in the natural gamma ray spectrometry logging data to obtain the corrected apparent matrix litho-density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section response, and apparent matrix thorium-potassium ratio logging response, including: Based on the volume content of the natural gamma ray response components of each target measurement point in the target reservoir and combined with the following formula, obtain the corrected apparent matrix litho-density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index, and apparent matrix thorium-potassium ratio logging response data of each target measurement point in the target reservoir; Wherein, and (Th / K) corr are respectively the corrected apparent matrix lithology density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index and apparent matrix thorium-potassium ratio logging response data of the target measurement point; ρ ma , U ma , P ema and TH / K ma are respectively the apparent matrix lithology density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section response index and apparent matrix thorium-potassium ratio logging response data of the target measurement point; (ρ cl1 ) ma , (U cl1 ) ma , (P ecl1 ) ma and (Th / K cl1 ) ma are respectively the lithology density, photoelectric cross-section index, volume cross-section index and thorium-potassium ratio logging response data of the potassium-poor clay matrix; (ρ cl2 ) ma , (U cl2 ) ma , (P ecl2 ) ma and (Th / K cl2 ) ma are respectively the lithology density, photoelectric cross-section index, volume cross-section index and thorium-potassium ratio logging response data of the potassium-rich clay matrix; (ρ mat ) ma , (U mat ) ma , (P emat ) ma and (Th / K mat ) ma are respectively the lithology density, photoelectric cross-section index, volume cross-section index and thorium-potassium ratio logging response data of the mica matrix; (ρ Felk ) ma , (U Felk ) ma , (P Felk ) ma and (Th / K Felk ) ma are respectively the lithology density, photoelectric cross-section index, volume cross-section index and thorium-potassium ratio logging response data of the potassium feldspar matrix; V cl1 is the volume content of potassium-poor clay at the target measurement point; V cl2 is the volume content of potassium-rich clay at the target measurement point; V mat is the volume content of mica at the target measurement point; V Fel is the volume content of potassium feldspar at the target measurement point.

8. The method for determining the mineral content of a shale oil reservoir according to claim 6, wherein, Based on the corrected apparent matrix litho-density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index, and apparent matrix thorium-potassium ratio logging response data, obtain the volume content of the non-natural gamma ray response components of the target reservoir, including: Construct a second logging response matrix, where the second logging response matrix includes: the response data of the corrected apparent matrix litho-density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio of different non-natural gamma ray response components of the target measurement points in the target reservoir; Establish a second relational expression for the second logging response matrix, the second volume content matrix of the unnatural gamma response components of the target measurement points to be predicted, and the second logging response prediction matrix constructed; the second volume content matrix includes the volumes of different unnatural gamma response components of the target measurement points, and the second logging response prediction matrix includes the response data of the predicted corrected apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio of the target measurement points; Based on the corrected apparent matrix lithology density, apparent matrix photoelectric cross-section index, apparent matrix volume cross-section index, and apparent matrix thorium-potassium ratio logging response data, determine the second volume content matrix that makes the second relational expression satisfy the preset second constraint condition set, and obtain the volume content of the unnatural gamma response components of the target measurement points; According to the volume content of the unnatural gamma response components of each target measurement point, obtain the volume content of the unnatural gamma response components of the target reservoir.

9. The method for determining the mineral content of a shale oil reservoir according to claim 8, wherein, The second constraint condition set includes: Constraint condition three: Make the volume content of the unnatural gamma response components of each target measurement point in the target reservoir satisfy the material balance relationship with the volume content of the natural gamma response components; and make the volume content of the unnatural gamma response components of each target measurement point respectively satisfy the volume content threshold range corresponding to each unnatural gamma response component in the target reservoir; Constraint condition four: Determine the second fitting error of all measurement points within the depth window where the target measurement point is located, and minimize the second fitting error; the second fitting error is the sum of the squares of the differences between the corrected apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio logging response data of all target measurement points within the depth window and the corresponding predicted corrected apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio logging response data.

10. The method for determining the mineral content of a shale oil reservoir according to claim 9, wherein, The unnatural gamma response components include: feldspar minerals other than potassium feldspar, quartz, calcite, and dolomite; The formula for the established second relational expression is as follows: In the formula, is the corrected apparent matrix lithology density predicted for the target measurement point; is the corrected apparent matrix volume cross-section index predicted for the target measurement point; is the corrected apparent matrix photoelectric cross-section index predicted for the target measurement point; is the corrected apparent matrix thorium-potassium ratio logging response data predicted for the target measurement point; (ρ Fel ) ma , (U Fel ) ma , (P eFel ) ma and (TH / K Fel ) ma are the logging response data of the apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio of feldspar minerals other than potassium feldspar at the target measurement point; (ρ Qart ) ma , (U Qart ) ma , (P eQart ) ma and (TH / K Qart ) ma are the logging response data of the apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio of quartz at the target measurement point; (ρ Cal ) ma , (U Cal ) ma , (P eCal ) ma and (TH / K Cal ) ma are the logging response data of the apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio of calcite at the target measurement point; (ρ Dol ) ma , (U Dol ) ma , (P eDol ) ma and (TH / K Dol ) ma are the logging response data of the apparent matrix lithology density, apparent matrix volume cross-section index, apparent matrix photoelectric cross-section index, and apparent matrix thorium-potassium ratio of dolomite at the target measurement point.

11. The method for determining the mineral content of a shale oil reservoir according to claim 10, wherein, The mineral content includes: clay volume content, felsic volume content, and carbonate volume content; According to the volume content of the unnatural gamma response components and the volume content of the natural gamma response components of the target reservoir, calculate the mineral content of the target reservoir, including: Obtain the clay volume content of the target reservoir according to the volume content of the potassium-rich clay and the volume content of the potassium-poor clay in the target reservoir; Calculate the felsic volume content of the target reservoir according to the volume content of the potassium feldspar, the volume of feldspar other than potassium feldspar, and the volume content of quartz in the target reservoir; Calculate the carbonate volume content of the target reservoir according to the volume content of calcite and the volume content of dolomite in the target reservoir.

12. A device for determining the mineral content of a shale oil reservoir, wherein, Include: A data acquisition module for acquiring natural gamma ray spectrometry logging data and lithology density logging data of the target reservoir; A first calculation module for obtaining the volume content of the natural gamma response components of the target reservoir based on the natural gamma ray spectrometry logging data; A second calculation module, which obtains natural gamma-ray spectrometry logging apparent matrix data and litho-density logging apparent matrix data based on the natural gamma-ray spectrometry logging data and the litho-density logging data; A third calculation module, which corrects the litho-density logging apparent matrix data and the natural gamma-ray spectrometry logging apparent matrix data based on the volume content of the natural gamma-ray response components, to obtain corrected litho-density logging apparent matrix data and natural gamma-ray spectrometry logging apparent matrix data; A fourth calculation module, which obtains the volume content of the non-natural gamma-ray response components of the target reservoir based on the corrected litho-density logging apparent matrix data and the natural gamma-ray spectrometry logging apparent matrix data; A fifth calculation module, which is configured to calculate the mineral content of the target reservoir according to the volume content of the non-natural gamma-ray components of the target reservoir and the volume content of the natural gamma-ray response components.

13. A computer storage medium, wherein, The computer storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, the method for determining the mineral content of a shale oil reservoir according to any one of claims 1-11 is implemented.

14. A computer device, wherein, Including: A memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the method for determining the mineral content of a shale oil reservoir according to any one of claims 1-11 is implemented.

Images