Method and device for determining oil saturation under reservoir conditions, and storage medium

Abstract

The application discloses a method and device for determining oil saturation under reservoir conditions and a storage medium, and belongs to the technical field of oil and gas exploration and development. The method comprises the following steps: obtaining target micro-pore structure characteristics of a target well at a target depth, formation pore pressure, nuclear magnetic resonance logging T2 spectrum of the target well and a plurality of core samples; performing a dual-pressure nuclear magnetic joint measurement experiment on each core sample to construct a rock minimum connected pore diameter representation model; determining a rock minimum connected pore diameter according to the target micro-pore structure characteristics based on the rock minimum connected pore diameter representation model; determining a maximum capillary force according to the rock minimum connected pore diameter; determining an oil and gas charging minimum pore diameter according to the formation pore pressure, the maximum capillary force and the rock minimum connected pore diameter; determining a key relaxation time point according to the oil and gas charging minimum pore diameter; and determining the oil saturation according to the key relaxation time point and the nuclear magnetic resonance logging T2 spectrum. The application can improve the characterization accuracy of the oil saturation.

Description

Technical Field

[0001] This application relates to the field of oil and gas exploration and development technology, and specifically to a method, apparatus and storage medium for determining oil saturation under reservoir conditions. Background Technology

[0002] Due to the highly heterogeneous pore structure of tight reservoirs, accurately assessing their oil-bearing potential is a challenge in well logging interpretation. Accurately evaluating the oil saturation of a tight reservoir at a specific depth in a target well allows for the assessment of oil and gas reserves within that reservoir at that depth. Furthermore, it enables the development of corresponding oil and gas development plans for that reservoir at that depth. Therefore, determining the oil saturation of tight reservoirs is crucial. Existing technologies, whether for single or multiple reservoir types, use fixed cutoff values ​​to define theoretical macropores and micropores, and bound fluids and mobile fluids, thereby determining the oil saturation of a single or multiple reservoir types. However, the pore structure characteristics of tight reservoirs at different depths in a target well vary considerably. Using fixed cutoff values ​​fails to reflect these differences, making it difficult to accurately assess the oil-bearing potential of the target well at different depths using the calculated oil saturation value. Summary of the Invention

[0003] The purpose of this application is to provide a method, apparatus, and storage medium for determining oil saturation under reservoir conditions, in order to solve the problem in the prior art that it is difficult to accurately evaluate the oil content of tight reservoirs at different depths in a target well.

[0004] To achieve the above objectives, the first aspect of this application provides a method for determining oil saturation under reservoir conditions, the method comprising: The target well is obtained at the target depth. The target micropore structure characteristics, formation pore pressure, nuclear magnetic resonance logging T2 spectrum of the target well, and multiple core samples in the target well are obtained. The target micropore structure characteristics include at least one of sorting coefficient, interstitial material content, and microfracture development index. Dual-pressure nuclear magnetic resonance (NMR) experiments were conducted on multiple core samples from the target well to construct a rock minimum connectivity pore size characterization model. Based on the rock minimum connectivity pore size characterization model, the rock minimum connectivity pore size of the target well at the target depth is determined according to the target micropore structure characteristics. The rock minimum connectivity pore size is the minimum pore-throat diameter in the pore-throat connectivity network of the target well at the target depth under the preset maximum charging pressure differential. Determine the maximum capillary force of the target well at the target depth based on the minimum connecting aperture of the rock. Based on the minimum pore size characterization model for oil and gas injection, the minimum pore size for oil and gas injection at the target depth of the target well is determined according to the formation pore pressure, maximum capillary force and minimum interconnected pore size of the rock. Based on the pre-constructed correspondence between pore diameter and relaxation time point, the key relaxation time point is determined according to the minimum pore diameter for oil and gas injection. The oil saturation of the target well at the target depth is determined based on the key relaxation time point and the T2 spectrum of nuclear magnetic resonance logging.

[0005] A second aspect of this application provides an apparatus for determining oil saturation under reservoir conditions, comprising: The memory is configured to store instructions; and the processor is configured to retrieve instructions from memory and, when executing instructions, to: The target well is obtained at the target depth. The target micropore structure characteristics, formation pore pressure, nuclear magnetic resonance logging T2 spectrum of the target well, and multiple core samples from the target well are obtained. The target micropore structure characteristics include at least one of sorting coefficient, interstitial material content, and microfracture development index. Dual-pressure nuclear magnetic resonance (NMR) experiments were conducted on multiple core samples from the target well to construct a rock minimum connectivity pore size characterization model. Based on the rock minimum connectivity pore size characterization model, the rock minimum connectivity pore size of the target well at the target depth is determined according to the target micropore structure characteristics. The rock minimum connectivity pore size is the minimum pore-throat diameter in the pore-throat connectivity network of the target well at the target depth under the preset maximum charging pressure differential. Determine the maximum capillary force of the target well at the target depth based on the minimum connecting aperture of the rock. Based on the minimum pore size characterization model for oil and gas injection, the minimum pore size for oil and gas injection at the target depth of the target well is determined according to the formation pore pressure, maximum capillary force and minimum interconnected pore size of the rock. Based on the pre-constructed correspondence between pore diameter and relaxation time point, the key relaxation time point is determined according to the minimum pore diameter for oil and gas injection. The oil saturation of the target well at the target depth is determined based on the key relaxation time point and the T2 spectrum of nuclear magnetic resonance logging.

[0006] A third aspect of this application also provides a machine-readable storage medium storing instructions for causing a machine to execute the method described above for determining oil saturation based on reservoir conditions.

[0007] The above technical solution acquires the target well's microscopic pore structure characteristics at the target depth, formation pore pressure, nuclear magnetic resonance logging T2 spectrum of the target well, and multiple core samples from the target well. The target microscopic pore structure characteristics include at least one of sorting coefficient, interstitial material content, and microfracture development index. Dual-pressure nuclear magnetic resonance experiments are conducted on multiple core samples from the target well to construct a rock minimum connected pore size characterization model. Based on the rock minimum connected pore size model, the rock minimum connected pore size at the target depth can be accurately determined. The processor can also determine the maximum capillary force at the target depth based on the rock minimum connected pore size, i.e., the resistance that crude oil needs to overcome to pass through the rock minimum connected pore size. Based on this, the processor can determine the minimum pore size that crude oil in the target well can pass through under formation pore pressure at the target depth, i.e., the minimum pore size for oil and gas injection, according to formation pore pressure, maximum capillary force, and minimum rock connectivity pore size. This allows for the sequential determination of the key relaxation time point at the target well at the target depth. Furthermore, the oil saturation at the target well at the target depth can be determined based on the key relaxation time point and the well logging T2-ray nuclear magnetic resonance spectrum. Thus, compared to existing technologies, by considering the target well's microscopic pore structure characteristics at the target depth, the minimum rock connectivity pore size that oil and gas can pass through at the target well at the target depth can be determined, as well as the minimum oil and gas injection pore size. Moreover, based on the aforementioned minimum rock connectivity pore size and minimum oil and gas injection pore size, the oil saturation at the target well at the target depth can be accurately determined, improving the accuracy of characterizing the oil saturation at the target well at the target depth.

[0008] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0009] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings: Figure 1 The illustration shows a flowchart of a method for determining oil saturation under reservoir conditions according to an embodiment of this application; Figure 2 This schematic diagram illustrates a pressure vessel experimental apparatus according to a specific embodiment of the present application. Figure 3 This schematically illustrates characteristic curves showing the variation of oil saturation with oil and gas injection pressure differential in different core samples according to a specific embodiment of this application. Figure 4aThe illustration schematically shows the T1-T2 two-dimensional nuclear magnetic resonance spectra of a core sample from a fully saturated formation under different fluid saturation states according to a specific embodiment of this application; Figure 4b The illustration schematically shows the T1-T2 two-dimensional nuclear magnetic resonance spectra of a core sample from an incompletely saturated formation under different fluid saturation states according to a specific embodiment of this application. Figure 5a This illustration schematically shows a T2 NMR spectrum of a core sample from a fully saturated formation in a charged state according to a specific embodiment of this application. Figure 5b This schematic diagram illustrates the T2 NMR spectrum of a core sample from an unsaturated formation under a charging state, according to a specific embodiment of this application. Figure 6 A schematic diagram illustrating the quantitative relationship between the sorting coefficient and the minimum connecting aperture of the rock according to the first embodiment of this application is shown. Figure 7 A schematic diagram illustrating the quantitative relationship between the maximum capillary force and the minimum connecting aperture of the rock according to the first embodiment of this application is shown. Figure 8 A schematic diagram illustrating the quantitative relationship between the aperture difference and the effective charging pressure difference (maximum capillary force - formation pressure) according to the first embodiment of this application is shown. Figure 9 This diagram schematically illustrates the results of oil-bearing evaluation of Well X under sorting control according to the first embodiment of this application; Figure 10 This diagram schematically illustrates the evaluation results of a Y-well controlled by formation pressure according to the second embodiment of this application. Figure 11 A schematic diagram illustrating the quantitative relationship between the sorting coefficient and the minimum connecting aperture of the rock according to the third embodiment of this application is shown. Figure 12 A schematic diagram illustrating the quantitative relationship between the content of turbid zeolite and the minimum interconnected pore size component of rock according to a third embodiment of this application is shown. Figure 13 A schematic diagram illustrating the quantitative relationship between the maximum capillary force and the minimum connecting aperture of the rock according to the third embodiment of this application is shown. Figure 14 A schematic diagram illustrating the quantitative relationship between the effective charge pressure differential (maximum capillary force - formation pressure) and the difference between the two apertures according to the third embodiment of this application is shown. Figure 15 The diagram illustrates the evaluation results of Well Z under the dual control of sorting and turbidite according to the third embodiment of this application. Figure 16 A schematic diagram illustrating the quantitative relationship between clay content and minimum pore size of rock according to a fourth embodiment of this application is shown. Figure 17 A schematic diagram illustrating the quantitative relationship between the microcrack development index and the minimum interconnected pore size of rock according to the fourth embodiment of this application is shown. Figure 18 A schematic diagram illustrating the quantitative relationship between the maximum capillary force and the minimum connecting aperture of the rock according to the fourth embodiment of this application is shown. Figure 19 A schematic diagram illustrating the quantitative relationship between the effective charge pressure differential (maximum capillary force - formation pressure) and the difference between the two apertures according to the fourth embodiment of this application is shown. Figure 20 The diagram illustrates the evaluation results of well D, controlled by both clay content and microcrack development index, according to the fourth embodiment of this application. Detailed Implementation

[0010] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0011] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with relevant laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0012] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0013] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0014] Figure 1 The illustration schematically shows a flowchart of a method for determining oil saturation under reservoir conditions according to an embodiment of this application. Figure 1 As shown in the figure, this application provides a method for determining oil saturation based on reservoir conditions. Taking the application of this method to a processor as an example, the method may include the following steps.

[0015] In step S101, the target well's microstructure characteristics at the target depth, formation pore pressure, nuclear magnetic resonance logging T2 spectrum of the target well, and multiple core samples from the target well are obtained. The target microstructure characteristics include at least one of sorting coefficient, interstitial material content, and microfracture development index.

[0016] In step S102, dual-pressure nuclear magnetic resonance (NMR) experiments are performed on multiple core samples from the target well to construct a rock minimum connectivity pore size characterization model.

[0017] In step S103, based on the rock minimum connectivity pore size characterization model, the rock minimum connectivity pore size of the target well at the target depth is determined according to the target micropore structure characteristics. The rock minimum connectivity pore size is the minimum pore-throat diameter in the pore-throat connectivity network of the target well at the target depth under the preset maximum charging pressure differential.

[0018] In step S104, the maximum capillary force of the target well at the target depth is determined based on the minimum connecting aperture of the rock.

[0019] In step S105, based on the minimum pore size characterization model for oil and gas injection, the minimum pore size for oil and gas injection at the target depth of the target well is determined according to the formation pore pressure, maximum capillary force, and minimum interconnected pore size of the rock.

[0020] In step S106, based on the pre-constructed correspondence between pore diameter and relaxation time point, the key relaxation time point is determined according to the minimum pore diameter for oil and gas injection.

[0021] In step S107, the oil saturation of the target well at the target depth is determined based on the key relaxation time point and the nuclear magnetic resonance logging T2 spectrum.

[0022] It can be understood that the target well is a well intended for oil and gas development. The target micropore structure characteristics are the microscopic properties of the rock pore-throat system, and these characteristics may include at least one of the following: sorting coefficient, interstitial material content, and microfracture development index. The sorting coefficient characterizes the uniformity of rock particle or pore size distribution; a larger sorting coefficient indicates stronger heterogeneity of the rock sample. Interstitial material content refers to the content of non-skeleton particles such as cement and matrix in the rock; a higher interstitial material content makes the throats within the rock sample more easily blocked, resulting in poorer connectivity. The microfracture development index characterizes the degree of microfracture development in the rock; a larger microfracture development index indicates a greater contribution of microfractures to pore connectivity. Formation pore pressure is the pressure exerted on the fluid in the formation pores at a certain depth in the target well. The dual-pressure NMR spectroscopy experiment involves performing NMR measurements on a core sample under two pressure conditions: the inlet pressure and the outlet pressure. The outlet pressure is set as the paleostratus pore pressure at the start of hydrocarbon accumulation during the reservoir's formation period, while the inlet pressure is set as the current formation pore pressure. The preset maximum charging pressure differential is the maximum charging pressure differential that the dual-pressure NMR spectroscopy equipment can withstand. The rock minimum connected pore diameter characterization model is a mathematical model that takes the target well's microscopic pore structure characteristics at different depths as input and the rock minimum connected pore diameter at different depths as output. The minimum hydrocarbon charging pore diameter is the smallest pore throat diameter that hydrocarbons can enter under the actual formation pressure differential at the target depth, while the rock minimum connected pore diameter is the smallest pore throat diameter that hydrocarbons can enter under the preset maximum charging pressure differential at the target depth. Generally, the minimum hydrocarbon charging pore diameter is greater than or equal to the rock minimum connected pore diameter. Nuclear magnetic resonance (NMR) logging T2 spectrum is a NMR T2 spectrum obtained directly downhole using logging instruments, reflecting the fluid distribution under in-situ formation conditions. Maximum capillary force is the maximum capillary resistance that fluid must overcome to pass through the smallest connecting pore diameter in a rock pore-throat network. Key relaxation time point is the dynamic threshold that distinguishes movable oil from bound fluid. Oil saturation is the percentage of crude oil volume in the reservoir pores at the target depth in the target well, relative to the total pore volume.

[0023] Specifically, the processor can acquire the target well's microscopic pore structure characteristics at the target depth and the formation pore pressure at the target well's target depth. The processor can also acquire the target well's nuclear magnetic resonance (NMR) T2 spectrum and multiple core samples from the target well. A rock minimum connectivity pore size model is constructed by performing dual-pressure NMR spectroscopy on multiple core samples from the target well. Based on the aforementioned method for constructing the rock minimum connectivity pore size model, the rock minimum connectivity pore size at the target well's target depth can be determined according to the target well's microscopic pore structure characteristics at the target depth; that is, the minimum throat diameter that oil and gas can enter at the aforementioned target depth under a preset maximum charging pressure differential is determined. Thus, the processor can determine the maximum capillary force that oil and gas need to overcome at the target depth based on the minimum connected pore size of the rock. Furthermore, based on the oil and gas charging minimum pore size characterization model, the processor can determine the minimum oil and gas charging pore size of the target well at the target depth based on formation pore pressure, maximum capillary force, and the minimum connected pore size of the rock; that is, the minimum pore size through which oil and gas can pass under formation pore pressure at the target depth. The processor can determine the corresponding key relaxation time point based on the pre-built correspondence between pore diameter and relaxation time point, according to the minimum oil and gas charging pore size. Thus, the processor can determine the oil saturation of the target well at the target depth based on the key relaxation time point and the well logging T2 NMR spectrum.

[0024] The above technical solution acquires the target well's microscopic pore structure characteristics at the target depth, formation pore pressure, nuclear magnetic resonance logging T2 spectrum of the target well, and multiple core samples from the target well. The target microscopic pore structure characteristics include at least one of sorting coefficient, interstitial material content, and microfracture development index. Dual-pressure nuclear magnetic resonance experiments are conducted on multiple core samples from the target well to construct a rock minimum connected pore size characterization model. Based on the rock minimum connected pore size model, the rock minimum connected pore size at the target depth can be accurately determined. The processor can also determine the maximum capillary force at the target depth based on the rock minimum connected pore size, i.e., the resistance that crude oil needs to overcome to pass through the rock minimum connected pore size. Based on this, the processor can determine the minimum pore size that crude oil in the target well can pass through under formation pore pressure at the target depth, i.e., the minimum pore size for oil and gas injection, according to formation pore pressure, maximum capillary force, and minimum rock connectivity pore size. This allows for the sequential determination of the key relaxation time point at the target well at the target depth. Furthermore, the oil saturation at the target well at the target depth can be determined based on the key relaxation time point and the well logging T2-ray nuclear magnetic resonance spectrum. Thus, compared to existing technologies, by considering the target well's microscopic pore structure characteristics at the target depth, the minimum rock connectivity pore size that oil and gas can pass through at the target well at the target depth can be determined, as well as the minimum oil and gas injection pore size. Moreover, based on the aforementioned minimum rock connectivity pore size and minimum oil and gas injection pore size, the oil saturation at the target well at the target depth can be accurately determined, improving the accuracy of characterizing the oil saturation at the target well at the target depth.

[0025] In this embodiment, dual-pressure nuclear magnetic resonance (NMR) experiments are conducted on multiple core samples from the target well to construct a rock minimum connected pore size characterization model. This includes: acquiring the microscopic pore structure characteristics of each core sample, the paleostratum pore pressure at the start of hydrocarbon accumulation, and the corresponding current pore pressure; determining the simulated hydrocarbon charging pressure difference for each core sample based on the paleostratum pore pressure and the current pore pressure; conducting dual-pressure NMR experiments on each core sample to obtain the first NMR T2 spectrum of each core sample under fully water-saturated conditions and the corresponding simulated hydrocarbon charging pressure difference, and the second NMR T2 spectrum of each core sample under a preset maximum charging pressure difference; determining the rock minimum connected pore size of each core sample based on the first NMR T2 spectrum and the corresponding second NMR T2 spectrum; determining the weighting coefficients corresponding to each microscopic pore structure characteristic based on the rock minimum connected pore size and the corresponding microscopic pore structure characteristics of each core sample; and obtaining the rock minimum connected pore size characterization model corresponding to the target well based on the weighting coefficients.

[0026] It can be understood that microscopic pore structure characteristics refer to the microscopic properties of the pore-throat system within a rock sample. Microscopic pore structure characteristics can include at least one of the following: sorting coefficient, interstitial material content, and microfracture development index. Paleostratigraphic pore pressure refers to the formation pore pressure at the time of hydrocarbon accumulation during the reservoir-forming period corresponding to the core sample's burial history. Current formation pore pressure refers to the formation pore pressure at the target depth of the core sample in the current geological history stage. Simulated hydrocarbon charging pressure differential refers to the fluid pressure differential under simulated hydrocarbon charging conditions in the formation. The first nuclear magnetic resonance (NMR) T2 spectrum is the T2 spectrum obtained from measuring the rock sample under simulated hydrocarbon charging pressure differential, reflecting the distribution of mobile fluids under formation conditions. The second NMR T2 spectrum is the T2 spectrum obtained from measuring the rock sample under a preset maximum charging pressure differential, reflecting the distribution of fluids in all connected pores within the core. Complete water saturation refers to the state where the pores within the core sample are completely occupied by water. The weighting coefficients are the weighting coefficients corresponding to each micropore structure feature, reflecting the influence of each micropore structure feature on the minimum connected pore size of the rock. Each micropore structure feature corresponds to a weighting coefficient.

[0027] Specifically, the processor can acquire the microscopic pore structure characteristics of each core sample, and obtain the paleostratus pore pressure at the start of hydrocarbon accumulation and the corresponding current pore pressure. Based on this, the processor can determine the difference between the paleostratus pore pressure and the corresponding current pore pressure, thus obtaining the simulated hydrocarbon charging pressure differential for each core sample. The processor can perform dual-pressure NMR spectroscopy on each rock sample, determining the first NMR T2 spectrum of each core sample under fully water saturation and the corresponding simulated hydrocarbon charging pressure differential, as well as the second NMR T2 spectrum of each core sample under a preset maximum charging pressure differential. The processor can determine the minimum connected pore size of each core sample based on the first and second NMR T2 spectra. Thus, based on the minimum connected pore diameter and corresponding micropore structure characteristics of each core sample, the weight coefficients corresponding to each micropore structure characteristic are determined. Based on this, the processor can obtain the minimum connected pore diameter model of the target well according to the weight coefficients, that is, a general model for determining the minimum connected pore diameter of the rock at the target well is constructed.

[0028] The above technical solution introduces the microscopic pore structure characteristics of the reservoir where the target well is located, and constructs a rock minimum connectivity pore size model based on the microscopic pore structure characteristics. This rock minimum connectivity pore size model can accurately characterize the rock minimum connectivity pore size of oil and gas at the target depth, reduce the deviation between it and the actual minimum connectivity space of the reservoir, and accurately evaluate the oil saturation of the reservoir.

[0029] In this embodiment of the application, the rock minimum connectivity aperture characterization model includes:

[0030] in, The minimum connecting aperture of the rock in the target well. Sorting coefficient The regression function between the minimum connected aperture of the rock and the minimum connected aperture. interstitial content The regression function between the minimum connected aperture of the rock and the minimum connected aperture. Microcrack development index The regression function between the minimum connected aperture of the rock and the minimum connected aperture. , as well as Sorting coefficients interstitial content and microcrack development index The corresponding weighting coefficients, This is a constant term.

[0031] In this embodiment, the minimum connected pore size of each core sample is determined based on each first NMR T2 spectrum and the corresponding second NMR T2 spectrum, including: determining the measured oil phase signal area of ​​each core sample based on the second NMR T2 spectrum; performing inverse cumulative summation from the maximum relaxation time point of the first NMR T2 spectrum to determine the target relaxation time point of each core sample within the first NMR T2 spectrum, such that the oil phase signal area between the target relaxation time point and the maximum relaxation time point is equal to the measured oil phase signal area; and determining the minimum connected pore size of each core sample based on the target relaxation time point according to the pre-constructed correspondence between pore diameter and relaxation time point.

[0032] It can be understood that the measured oil phase signal area is the area under the T2 signal curve corresponding to the oil phase fluid actually measured under the preset maximum charging pressure difference, and can also be characterized as the theoretical maximum oil yield. The maximum relaxation time point is the time point with the largest value on the T2 time axis in the first nuclear magnetic resonance T2 spectrum. The target relaxation time point is obtained by inversely accumulating and summing from the maximum relaxation time point until the accumulated oil phase signal area equals the relaxation time point corresponding to the measured oil phase signal area. The pre-constructed correspondence between pore diameter and relaxation time point is the pre-constructed correspondence between pore diameter and relaxation time point.

[0033] Specifically, when measuring the second nuclear magnetic resonance (NMR) T2 spectrum of each core sample, the core samples are in an oil-saturated state, meaning all connected pores in the core sample are occupied by oil. Therefore, the signal intensity of the measured NMR T2 spectrum directly reflects the oil phase volume distribution. Based on this, the processor can integrate the signal intensity in the NMR T2 spectrum to obtain the measured oil phase signal area of ​​each core sample. By inversely accumulating and summing the maximum relaxation time points of the first NMR T2 spectrum, the process of oil phase filling from large pores to small pores can be simulated, determining the relaxation time required for theoretically produced oil to pass through the minimum throat under simulated formation pressure differential, i.e., the target relaxation time point of each core sample within the first NMR T2 spectrum. Furthermore, based on the pre-constructed correspondence between pore diameter and relaxation time points, the minimum connected pore diameter of each core sample is determined according to the target relaxation time point. The above technical solution achieves high-precision inversion of the true minimum connected pore size of core samples under formation pressure conditions through dual-pressure nuclear magnetic resonance experiments and inverse cumulative signal matching, and can accurately calculate the minimum connected pore size of each rock sample.

[0034] In this embodiment, dual-pressure NMR spectroscopy is performed on each core sample to obtain the first NMR T2 spectrum and the second NMR T2 spectrum of each core sample under a fully water-saturated state and the corresponding simulated hydrocarbon charging pressure differential. This includes: performing NMR spectroscopy on each core sample based on the simulated hydrocarbon charging pressure differential to obtain the first NMR T2 spectrum and the corresponding two-dimensional NMR spectrum of each core sample under a fully water-saturated state; and using heavy water to displace formation water in each core sample under a fully water-saturated state based on the simulated hydrocarbon charging pressure differential to obtain the second NMR T2 spectrum of each core sample under a preset maximum charging pressure differential. The third NMR T2 spectrum and the corresponding two-dimensional NMR spectrum under saturation conditions were obtained. Based on the simulated oil and gas injection pressure difference, crude oil was used to displace the heavy water in each core sample under heavy water saturation to obtain the fourth NMR T2 spectrum and the corresponding two-dimensional NMR spectrum of each core sample after the heavy water was displaced by crude oil. The simulated oil and gas injection pressure difference was increased, and crude oil was used to displace the heavy water in each core sample after the heavy water was displaced by crude oil, and NMR coupled-phase experiments were performed until the NMR T2 spectrum and the two-dimensional NMR spectrum in the NMR coupled-phase experiments no longer changed, so as to obtain the second NMR T2 spectrum and the corresponding two-dimensional NMR spectrum of each core sample under the preset maximum injection pressure difference.

[0035] It is understandable that heavy water produces almost no signal in conventional nuclear magnetic resonance (NMR) and is used to displace formation water. Heavy water saturation refers to a state where only heavy water, invisible to NMR, exists within the pores of the core sample. The third NMR T2 spectrum is the T2 spectrum obtained by measuring rock samples in a saturated heavy water state under simulated hydrocarbon charging pressure differentials. The fourth NMR T2 spectrum is the T2 spectrum measured by hydrocarbon displacement of heavy water in rock samples under simulated hydrocarbon charging pressure differentials. The two-dimensional NMR spectrum is a two-dimensional joint distribution map.

[0036] Specifically, the processor can perform nuclear magnetic resonance (NMR) experiments on each core sample based on the simulated oil and gas charging pressure difference to obtain the first NMR T2 spectrum and the corresponding two-dimensional NMR spectrum of each core sample under the fully water-saturated state. The processor can also use heavy water to displace the formation water in each core sample under the fully water-saturated state based on the simulated oil and gas charging pressure difference, and monitor the two-dimensional NMR spectrum of the core sample in real time until the two-dimensional NMR spectrum no longer changes. The processor can determine that the state of the core sample has reached the saturated heavy water state. At this time, the processor can obtain the third NMR T2 spectrum and the corresponding two-dimensional NMR spectrum of each core sample under the saturated heavy water state. Furthermore, the processor can also use crude oil to displace the heavy water in each core sample under saturated heavy water conditions, and monitor the two-dimensional nuclear magnetic resonance (NMR) spectrum of the core sample in real time during the crude oil displacement process until the two-dimensional NMR spectrum no longer changes. At this point, the processor can obtain the core samples after crude oil displacement of heavy water. Simultaneously, it monitors the nuclear magnetic resonance (NMR) T2 spectrum during the displacement process in real time until the NMR T2 spectrum no longer changes. At this point, the processor can obtain the fourth NMR T2 spectrum and the corresponding two-dimensional NMR spectrum of each core sample. The processor can also increase the simulated oil and gas charging pressure difference to guide oil and gas to further displace heavy water, and monitor the NMR T2 spectrum during the displacement process in real time until the NMR T2 spectrum and the two-dimensional NMR spectrum in the NMR spectroscopy experiment no longer change, or the increased simulated formation pressure difference equals the preset maximum charging pressure difference. At this point, the processor can obtain the second NMR T2 spectrum and the corresponding two-dimensional NMR spectrum of each core sample under the preset maximum charging pressure difference.

[0037] Based on the dual-pressure nuclear magnetic resonance (NMR) test, the first NMR T2 spectrum of each rock sample under fully water-saturated conditions can be accurately obtained, as well as the second NMR T2 spectrum of each rock sample under a preset maximum charging pressure difference. This provides reliable experimental data for the calculation of the minimum interconnected pore size and significantly improves the accuracy and reliability of the evaluation of oil saturation in the strongly heterogeneous reservoir where the target well is located.

[0038] In this embodiment of the application, the determination method further includes: determining the first simulated oil saturation of each core sample under simulated oil and gas charging pressure difference based on the first NMR T2 spectrum and the fourth NMR T2 spectrum; determining the second simulated oil saturation of each core sample under a preset maximum charging pressure difference based on the first NMR T2 spectrum and the second NMR T2 spectrum; determining the oil and gas charging state of each core sample as a saturated oil and gas charging state when the first simulated oil saturation is equal to the corresponding second simulated oil saturation; and determining the oil and gas charging state of each core sample as an unsaturated oil and gas charging state when the first simulated oil saturation is less than the corresponding second simulated oil saturation.

[0039] It can be understood that the first simulated oil saturation is the oil saturation obtained under simulated formation conditions. The second simulated oil saturation is the oil saturation under the simulated maximum charging pressure differential. The hydrocarbon charging state refers to the degree of saturation of hydrocarbons in the pores of the core sample. The hydrocarbon charging state includes saturated hydrocarbon charging and unsaturated hydrocarbon charging. Saturated hydrocarbon charging means that the hydrocarbon charging has reached saturation, that is, hydrocarbons have occupied all accessible connected pores in the core sample, reaching the charging limit. Unsaturated hydrocarbon charging means that the hydrocarbon charging has not reached saturation, that is, some space in the pores of the rock sample remains unoccupied by hydrocarbons, indicating that the hydrocarbon charging has not yet reached its limit.

[0040] Specifically, the processor can pre-determine the oil phase signal areas corresponding to the fourth and second NMR T2 spectra, respectively. By inversely accumulating and summing in the first NMR T2 spectrum, it determines the relaxation time point equal to the oil phase area of ​​the fourth NMR T2 spectrum. Based on this relaxation time point and the total water phase area of ​​the first NMR T2 spectrum, it determines the first simulated oil saturation of each core sample under the simulated oil and gas charging pressure differential. Similarly, it determines the second simulated oil saturation of each core sample under a preset maximum charging pressure differential. The processor can compare the first simulated oil saturation with the corresponding second simulated oil saturation. If the first simulated oil saturation equals the corresponding second simulated oil saturation, the processor determines that the oil and gas charging state of each core sample is a saturated oil and gas charging state, meaning that the oil and gas charging has reached its limit. When the first simulated oil saturation is less than the corresponding second simulated oil saturation, the hydrocarbon charging state of each core sample is determined to be unsaturated, meaning the hydrocarbon charging has not reached its limit. Under certain external force, the hydrocarbon can reach the small pore spaces. However, if the first simulated oil saturation is greater than the corresponding second simulated oil saturation, it indicates that there are certain experimental problems in the dual-pressure NMR spectroscopy experiment, and the experiment needs to be repeated.

[0041] The above technical solution can determine the oil and gas filling state of each core sample, determine the qualification level of the experiment in advance, and compare it with the oil saturation of the target well at the target depth. That is, the oil saturation determined by the experiment is compared with the oil saturation determined by the rock minimum connectivity pore size characterization model to determine the accuracy of the output of the rock minimum connectivity pore size characterization model.

[0042] In this embodiment, based on the minimum pore size characterization model for oil and gas injection, the minimum pore size for oil and gas injection at the target depth of the target well is determined according to the formation pore pressure, maximum capillary force, and minimum connecting pore size of the rock. This includes: when the formation pore pressure is greater than or equal to the maximum capillary force, the minimum connecting pore size of the rock is determined as the minimum pore size for oil and gas injection; when the formation pore pressure is less than the maximum capillary force, the minimum connecting pore size of the rock is corrected according to the formation pore pressure and the maximum capillary force to obtain the minimum pore size for oil and gas injection.

[0043] Specifically, the processor can compare formation pore pressure with maximum capillary force. If the formation pore pressure is greater than or equal to the maximum capillary force, it indicates that the formation pore pressure at the target depth of the target well is sufficient to overcome the maximum capillary force, meaning that oil and gas have been injected to the minimum connecting pore size of the rock. In this case, the minimum connecting pore size of the rock is determined as the minimum pore size for oil and gas injection. Conversely, if the formation pore pressure is less than the maximum capillary force, it indicates that the formation pore pressure at the target depth of the target well is insufficient to overcome the maximum capillary force. This means that oil and gas cannot enter the micropore spaces due to insufficient power, i.e., oil and gas cannot be injected to the minimum connecting pore size of the rock. In this case, the minimum connecting pore size of the rock is corrected based on the formation pore pressure and the maximum capillary force to obtain the minimum pore size for oil and gas injection. This technical solution reveals the minimum pore size that oil and gas can actually inject into the reservoir at different depths of the target well, more accurately reflecting the lower limit of pores that oil and gas can enter in the reservoir, thus providing a more precise evaluation of the reservoir's oil content.

[0044] In this embodiment of the application, the minimum connecting pore diameter of the rock is corrected based on the formation pore pressure and the maximum capillary force to obtain the minimum pore diameter for oil and gas injection. This includes: determining the deviation value between the formation pore pressure and the maximum capillary force; determining the correction value based on the deviation value; and determining the sum of the correction value and the minimum connecting pore diameter of the rock to obtain the minimum pore diameter for oil and gas injection.

[0045] Specifically, after determining that the formation pore pressure is less than the maximum capillary force, the processor indicates that the formation pore pressure is insufficient to overcome the maximum capillary force, and oil and gas cannot be injected into the minimum connected pore size of the rock. Based on this, the deviation between the formation pore pressure and the maximum capillary force is determined, a correction value is determined based on the deviation value, and the sum of the correction value and the minimum connected pore size of the rock is determined to obtain the minimum pore size for oil and gas injection. The above technical solution introduces the deviation value between the formation pore pressure and the maximum capillary force, establishing a quantitative relationship between dynamics and resistance. The minimum pore size for oil and gas injection obtained by correcting the minimum connected pore size of the rock more closely reflects the actual underground reservoir conditions.

[0046] In this embodiment of the application, determining the oil saturation of the target well at the target depth based on the key relaxation time point and the nuclear magnetic resonance logging T2 spectrum includes: determining the oil phase signal area corresponding to the key relaxation time point in the nuclear magnetic resonance logging T2 spectrum; determining the total signal area corresponding to the nuclear magnetic resonance logging T2 spectrum; and determining the ratio of the oil phase signal area to the total signal area to obtain the oil saturation of the target well at the target depth.

[0047] It is understandable that the oil phase signal area corresponding to the key relaxation time point is the total amount of mobile fluid (e.g., oil) in the formation, and the total signal area is the total amount of all fluids (e.g., oil + water) in the formation.

[0048] Specifically, the processor can determine the movable fluid signal area (i.e., the oil phase signal area) and the total signal area of ​​all fluids in the well logging nuclear magnetic resonance T2 spectrum, thus obtaining the proportion of oil volume to the total fluid volume under reservoir conditions, i.e., the oil saturation of the reservoir at the target depth in the target well. The above technical solution divides the data by key relaxation time points, achieving precise separation of the oil phase signal and improving the accuracy of oil saturation calculation.

[0049] This application provides a specific embodiment of a method for constructing a minimum connectivity pore size model for rocks. The method includes: selecting a highly heterogeneous tight reservoir where the oil-bearing capacity of different well areas and sections varies significantly, encompassing multiple controlling factors such as formation pressure variations, particle sorting differences, interstitial material (e.g., zeolite) filling, and microfracture development. First embodiment: selecting Well X, with relatively simple controlling factors. Well X has good reservoir properties, and its oil-bearing capacity is mainly controlled by formation pressure (a single external factor). Second embodiment: selecting Well Y, with relatively simple controlling factors. Well Y is mainly affected by particle sorting controlled by sedimentary microfacies (a single internal factor). Third embodiment: selecting Well Z, with significant interstitial material filling. The reservoir microstructure in this well area is simultaneously controlled by particle sorting and interstitial material (zeolite) content, requiring the establishment of a pore size characterization model coupled with dual internal factors. Fourth embodiment: Well D, whose macroscopic properties and oil content are both affected by the dual intrinsic factors of clay content (interstitial material) and microfracture development, was selected. Based on discrete data obtained from nuclear magnetic resonance joint experiments, multiple regression was performed using two geological parameters, clay content and microfracture development index, to construct a rock minimum connectivity pore size characterization model.

[0050] Regardless of the first, second, third, or fourth embodiment, all require targeted sampling and parameter determination based on geological research findings of the target layer, comprehensively considering its burial evolution history and reservoir lithofacies characteristics. The specific process is as follows: Core selection and pretreatment. Representative full-diameter core samples are selected from the target layer. The selection principle focuses on rocks with different sorting characteristics, including three typical rock types: well-sorted, moderately sorted, and poorly sorted, to ensure that the samples cover the main heterogeneous characteristics of the reservoir in this area. All samples undergo standard oil washing, salt washing, and drying treatment (drying temperature 105℃, for 48 hours) until constant weight is achieved to eliminate the influence of retained fluids in the core on subsequent tests.

[0051] Sorting coefficient ( The determination and calculation of the sorting coefficient (SCC) were performed on selected core samples for casting thin section identification and image grain size analysis. First, high-resolution microscopic images of the rock were acquired, and grain boundaries were identified using image segmentation algorithms. Second, the grain diameter across the entire field of view was statistically analyzed, and a cumulative grain size probability curve was plotted. Based on this curve, the sorting coefficient of each core sample was calculated using the following formula (SCC). ):

[0052] in, , , These are the particle diameters corresponding to content levels of 25%, 50% (median particle size), and 75% on the cumulative probability curve of particle size, respectively, in mm. denoted as the sorting coefficient for each core sample.

[0053] X-ray diffraction (XRD) analysis and casting thin section identification were performed on the selected core samples, and the mineral type of the interstitial material in the core was quantitatively determined to be zeolite. To apply the discrete core test results to subsequent continuous evaluation of the entire well section, a multiple regression analysis was performed on the measured zeolite content and the corresponding conventional logging curves to establish a zeolite content (… Well logging calculation model:

[0054] in, The content of interstitial material (%); To compensate for neutron logging values ​​(%); Formation density logging value ( ).

[0055] The pore throat characteristic parameters were determined using an AutoPore IV 9505 fully automated mercury intrusion porosimeter. The maximum mercury intrusion pressure was set to 200 MPa. Based on the Washburn equation, the recorded capillary pressure (…) was… Convert ) to the corresponding throat radius ( ):

[0056] in, The surface tension of mercury is taken as 0.48 N / m; The contact angle between mercury and rock is 130°. For capillary pressure, Let be the radius of the throat.

[0057] Determination of Formation Temperature and Pressure Conditions. Formation test data and burial history research results were collected within the region. Based on well temperature logging curves, the formation temperature of the target section was determined to be 85℃, serving as the simulation temperature for subsequent experiments. Based on burial and thermal evolution history, the key geological moment when large-scale hydrocarbon injection began (Late Early Jurassic) and its corresponding paleoburial depth (approximately 2400m) were determined. The paleoformation pressure at this depth was approximately 25 MPa, which is the "exit pressure" (paleosteoformation pore pressure at the start of hydrocarbon injection during the reservoir formation period) set in the dual-pressure NMR spectroscopy experiment. Simultaneously, based on measured formation pressure data, the current formation pore pressure of the target section was determined. The pressure is 37 MPa, which is the "inlet pressure" (current formation pore pressure) set in the dual-pressure NMR spectroscopy experiment. Figure 2 As shown, the above geological parameters clarify the pressure boundary conditions (i.e., inlet pressure) for subsequent dual-pressure NMR spectroscopy experiments. export pressure ).

[0058] The specific steps of the dual-pressure NMR spectroscopy experiment are as follows: First, collect the T2 NMR spectrum under saturated water conditions. Firstly, the core samples, after washing oil and salt and drying, are fully saturated with formation water at room temperature and pressure, and the T2 and two-dimensional NMR spectra are measured. Then, the saturated samples are heated and pressurized to simulated formation pressure differential, and the T2 and two-dimensional NMR spectra are measured again, which will serve as the benchmark for subsequent calculations of oil saturation and calibration of pore throat distribution. Second, paleotemperature-pressure simulation and heavy water (… Replacement. In order to accurately extract the oil phase signal in nuclear magnetic resonance experiments, heavy water ( ) Shielding water signals. First, paleostratigraphic environment reconstruction was performed. The sample was placed in a high-temperature, high-pressure core holder, the confining pressure was restored to 60 MPa, and the temperature was raised to the formation temperature of 85℃ determined in step 1. The sample was then held at this temperature for 2 hours to ensure thermal equilibrium. Next, heavy water replacement was performed. Heavy water was injected using a high-pressure pump at a flow rate of 0.1 mL / min. This process displaces formation water from the pores until the density of the effluent at the outlet is consistent with that of heavy water and NMR signal detection shows that the water signal has essentially disappeared (i.e., the NMR T2 spectrum amplitude is close to baseline noise). At this point, the rock pores are filled with heavy water, and the aqueous phase will not be visible in subsequent tests. In the third stage, to simulate current formation conditions, simulated oil (with the same viscosity as underground crude oil) is injected at the inlet, and the inlet pressure is gradually increased. When the inlet pressure reaches 37 MPa, the effective charging pressure difference ( The initial pressure was 12 MPa, corresponding to the current formation dynamics in the well area. After displacement equilibrium was reached, the nuclear magnetic resonance (NMR) T2 spectrum was acquired at this point, representing the "oil and gas charging state under formation conditions." Fourth stage: To simulate the physical limit state, after completing the 12 MPa measurement, the inlet pressure was further increased, widening the charging pressure differential (e.g., to 15 MPa, 20 MPa, etc.), and the changes in the NMR T2 spectrum were monitored in real time. When the oil saturation (i.e., the NMR T2 spectrum morphology) no longer changed with increasing pressure differential, the core was considered to have reached the "saturated oil state." Figure 3 As shown, this reflects the oil-bearing capacity of cores with different physical properties under different charging forces. The figure marks the current formation pore pressure points to determine whether the formation has reached a fully saturated state. The solid line represents the charging stage in the paleostratigraphic state, and the dashed line represents the fully charged stage under pressurization. The square circle indicates that the core has reached a saturated state in the paleostratigraphic state, and the circled pore pressure point indicates that the core has reached a saturated state under pressurization. The nuclear magnetic resonance T2 spectrum collected at this time represents the maximum degree of charging allowed by rock physics, i.e., the "minimum connected pore size state of the rock".

[0059] Dual-pressure NMR spectroscopy experiments showed that for some samples with poor sorting coefficients, the effective filling pressure difference ( The oil saturation at this level is significantly lower than that at saturated oil levels, indicating that it is in an incompletely saturated state under current geological conditions. Figure 4a As shown, after the water phase signal in a fully saturated formation core was completely shielded using heavy water, the two-dimensional NMR signal representing the oil phase gradually appeared with increasing oil-driven water pressure (displacement state 1). When the effective charging pressure differential was reached, the distribution range of the oil phase signal on its T1-T2 spectrum and the total NMR signal (displacement state 2) basically coincided with the spectrum when the pressure was further increased to the ultimate pressure differential (displacement state 3). This indicates that the current charging dynamics of the formation are sufficient to overcome the capillary resistance of the smallest pore throat in the rock sample, and the oil and gas have been completely charged to the limit of the micropores allowed by rock physics. Figure 4b As shown, in incompletely saturated formation cores under effective charging pressure differential (displacement state 2), the oil phase signal on the two-dimensional NMR spectrum is mainly concentrated in the medium-long T2 region, representing larger pores, but the amplitude is relatively small. When the charging pressure differential continues to increase to the physical limit (displacement state 3), the signal amplitude in the long T2 region is significantly enhanced. This dynamic extension characteristic of the two-dimensional NMR signal distribution with pressure differential reveals that under the current conditions of insufficient formation dynamics, there are still a large number of interconnected micropores in the rock pore network that have failed to enter the oil due to insufficient dynamics.

[0060] Using dual-pressure NMR spectroscopy experiments, the minimum interconnected pore size of the core sample, the minimum pore size for hydrocarbon charging under formation conditions, and the relationship between the two were determined. Since the water signal is shielded in the core under saturated heavy water conditions, the NMR T2 distribution of oil-driven water under different charging pressure differentials directly reflects the distribution of oil-phase fluids entering the core. (This text is repeated in the original.) Figure 5a As shown, Figure 5a This demonstrates the characteristics of a fully saturated formation. At this point, the current formation pore pressure is sufficient to overcome the maximum capillary force of the rock. The minimum pore size for hydrocarbon injection under formation conditions and the minimum interconnected pore size of rocks completely overlap on the nuclear magnetic resonance T2 spectrum, indicating that hydrocarbons have been injected to the minimum porosity limit allowed by rock physics; Figure 5b As shown, Figure 5b This demonstrates the characteristics of an incompletely saturated formation. At this point, the current formation pore pressure is insufficient to overcome the capillary resistance of all interconnected pores. This results in the "minimum pore size for oil and gas injection under formation conditions" being significantly larger than the "minimum connected pore size of the rock". The difference between the two represents the tiny pore spaces that, although the rock pores are connected, failed to receive oil due to insufficient injection power, thus intuitively revealing the formation mechanism of unsaturated strata.

[0061] To accurately convert the experimentally measured "oil phase signal area" into the "pore size lower limit," the "area inverse accumulation method" was used to process the T2 spectrum (i.e., the first NMR T2 spectrum) of heated and pressurized saturated water. Based on the N=200 discrete relaxation time points contained in the NMR T2 spectrum, the amplitude of the measured NMR T2 spectrum signal in the fully saturated water state was adjusted from the maximum relaxation time point (…). Start performing cumulative summation forward to find a key time point. This makes the cumulative signal area after that point equal to the total area of ​​the oil phase signal measured under the preset maximum charge pressure difference (i.e., the oil phase signal area of ​​the second nuclear magnetic resonance T2 spectrum).

[0062] Based on the pre-constructed correspondence between pore diameter and relaxation time point, Converted to the minimum connected pore size of the rock, the correspondence between the pre-constructed pore diameter and the relaxation time point is as follows:

[0063] in, The pore diameter is expressed in units of 1000 mm. , This is the conversion factor, in units of... , The relaxation time point is expressed in units of 1 / 2000. .

[0064] The conversion factor can be determined by the following formula:

[0065] in, This is the conversion factor, in units of... , The surface tension of mercury, The contact angle between mercury and rock. The relaxation time point, This refers to capillary pressure.

[0066] Minimum connecting aperture of rock ( The determination of ) . When the oil phase area is taken as the total area of ​​the oil phase signal measured under the preset maximum charging pressure differential. ， When the core reaches its physical limit (saturated oil state, i.e., maximum injection pressure difference), the pore diameter calculated based on the pre-constructed correspondence between the pore diameter and the relaxation time point is the minimum connected pore diameter of the rock. As shown in Table 1, the minimum interconnected pore size of rock sample No. 4 was calculated. It is 0.0184 The corresponding sorting coefficient is 1.684; the minimum connected pore size of rock in sample No. 3 is... It is 0.0406 The corresponding sorting coefficient is 2.205. The data shows that the smaller the sorting coefficient, the better. The larger the pressure difference, the better. This is achieved using simulations to obtain the current formation pressure differential. The experimental data below, combined with the measured maximum capillary force ( ) and current formation pore pressure ( Comparative judgment: Taking sample No. 1 as an example, when the sample is in a fully saturated state, its current formation pore pressure... (112.77 MPa) is much greater than the maximum capillary force. (37.61 MPa) indicates sufficient displacement force and that the formation is in a fully saturated state. At this point, the minimum pore size for hydrocarbon injection under these formation conditions is equal to the minimum interconnected pore size of the rock, i.e. When the sample is not fully saturated, taking sample No. 5 as an example, its current formation pore pressure... (36.596 MPa) is less than the maximum capillary force of the rock. (42.446 MPa) indicates that the current dynamics are insufficient to overcome the resistance of the minimum pore throat, and the formation is in an incompletely saturated state. At this point, the minimum pore size that can actually be used for oil and gas injection under these formation conditions is... Larger than its rock minimum connecting aperture .

[0067] Table 1 Relevant data of core samples

[0068] Taking the first embodiment as an example: The X well in this embodiment is a sorting coefficient-controlled reservoir, where interstitial material and microfractures are not well-developed. Therefore, the weighting coefficient corresponding to the interstitial material content is set as follows: The weighting coefficient corresponding to the microcrack development index is The weighting coefficient corresponding to the sorting coefficient is The minimum interconnected pore size of the rock samples from each core sample in Well X. With the corresponding sorting coefficient By performing linear regression, we can obtain the minimum connected pore size model of the rock corresponding to well X, such as... Figure 6 As shown, with the increase of the sorting coefficient, the lower limit of the minimum connected pore size of the rock shows a decreasing trend, and the two have a good linear correlation.

[0069] 9 in, The minimum connecting aperture of the rock. This is the sorting coefficient.

[0070] Furthermore, construct the maximum capillary force ( (Model conversion) The minimum interconnected pore size of each core sample is converted. Corresponding to the measured maximum capillary force Perform regression analysis. For example... Figure 7 As shown in the figure, the maximum capillary force increases as the lower limit of the minimum open diameter of the rock decreases, and is used to calculate the breakthrough pressure required for the rock under extreme conditions. The conversion formula is established as follows:

[0071] in, For maximum capillary force, This represents the minimum connected pore size in the rock. This conversion formula quantifies the inverse relationship between pore size and pressure, and provides a pressure threshold standard for subsequent determination of formation charging status.

[0072] Minimum pore size for oil and gas injection under formation conditions ( Segmented model. Incorporating current formation pore pressure. As an external variable, a segmented model was constructed based on experimental data: when At that time, the geological dynamics were sufficient, and the setting was... ;when At that time, the oil and gas injection capacity was insufficient. The pore size difference of the unsaturated sample was utilized ( ) and unsaturated pressure difference ( Regression is performed. For example... Figure 8 The figure shows the relationship between the difference between the "minimum pore size for oil and gas injection under formation conditions" and the "minimum interconnected pore size in rock" as a function of the difference between the maximum capillary force and the formation pressure:

[0073] in, Minimum orifice diameter for oil and gas filling. The minimum connecting aperture of the rock. For maximum capillary force, This represents the current pore pressure of the formation.

[0074] In summary, the final stratigraphic condition limit model is as follows:

[0075] in, Minimum orifice diameter for oil and gas filling. The minimum connecting aperture of the rock. For maximum capillary force, This represents the current pore pressure of the formation.

[0076] Based on the aforementioned formation condition limit model, the sorting coefficient and current formation pore pressure of well X at the target depth can be obtained, and the minimum connected pore size of the reservoir rock at the target depth can be determined. Therefore, the maximum capillary force can be determined based on the minimum connected pore size. Furthermore, based on the minimum connected pore size, maximum capillary force, and current formation pore pressure, the minimum pore size for hydrocarbon injection in well X at the target depth can be determined. Well logging NMR T2 spectra of well X at multiple depths are obtained. Thus, the key relaxation time points in the well logging NMR T2 spectra can be determined based on the minimum pore size for hydrocarbon injection, and the conversion coefficients at each depth point can be used... ,Will The curve is converted into a continuous variable T2 cutoff value curve. ):

[0077] in, This is the key relaxation time point. Let X be the conversion coefficient of well X at the target depth. The minimum pore size for oil and gas injection at the target depth in well X.

[0078] The oil saturation of the target well at the target depth is determined based on the key relaxation time points and the T2 spectrum of the well logging nuclear magnetic resonance. From this, a continuous oil saturation curve for the entire well section of well X can be obtained. Figure 9 As shown, Figure 9 The diagram shows the interpretation of well X, illustrating the core parameters of basic logging, controlling factors, and the coupling between the dual minimum aperture and pressure. Comparative analysis confirms that the oil saturation calculated using the variable T2 cutoff model in this application is far superior to traditional methods, and highly consistent with core sampling measurements and oil testing conclusions.

[0079] Traditional methods, which use a single T2 cutoff value to calculate oil saturation, generally result in low overall levels. Well X's average saturation is approximately 35%, significantly lower than the saturation data measured in closed coring (closed coring saturation channel, average approximately 45%), and it fails to accurately reflect the heterogeneous changes in oil content within the formation. In contrast, the oil saturation calculated using the variable T2 cutoff value model of this invention (variable cutoff value saturation channel) not only shows a very high degree of agreement with the measured data from closed coring (black dots) (average relative error less than 5%), but also accurately depicts the oil content variation trend controlled by the sorting coefficient. Furthermore, during production verification, the well section was identified as a high-yield oil layer (rightmost test conclusion channel), consistent with the oil content evaluation results disclosed in this application, verifying the high reliability and practicality of this application's embodiment in complex tight reservoir formations.

[0080] The second embodiment will be used as an example for illustration: Figure 10As shown, to address the contradiction of similar physical properties but vastly different production capacities in the upper and lower sections, this application's embodiment accurately calculates the oil saturation of the section with insufficient oil and gas charging power (3400-308m). The results are highly consistent with the oil testing conclusions, effectively compensating for the shortcomings of the traditional fixed cutoff value method. Taking Well Y as an example, the upper reservoir (above 3450m) in this well area has poor sorting and low formation pore pressure, resulting in insufficient oil and gas charging and low oil saturation; the lower reservoir (below 3470m) has good sorting and high formation pore pressure, resulting in sufficient oil and gas charging power and high oil saturation. However, the saturation calculated using the traditional fixed cutoff value method for the upper and lower reservoirs is basically consistent. The oil test results showed that the upper test section (3395-3410m) used twice the proppant as the lower test section (3470-3485m). The oil production in the upper test section was only 2.41 tons / day (including the oil-water layer), while the oil production in the lower test section reached 5.95 tons / day (oil-water co-layer). Continuous evaluation using the variable T2 cutoff value model of this application effectively solved the engineering problem of the contradiction between traditional methods and actual production capacity.

[0081] Taking the third embodiment as an example: For the Z well area, the reservoir heterogeneity is quite complex. Oil-bearing capacity is not only controlled by sorting but also significantly affected by the high content of turbidite (interstitial material). To accurately characterize this type of reservoir, this embodiment of the application simultaneously utilizes the sorting coefficient weighting (… ) and interstitial weight ( ), and construct a quantitative characterization model with two-factor coupling.

[0082] In the Z well area, sorting coefficients were calculated using electrical imaging logging data. Furthermore, zeolite, as an authigenic mineral, exhibits a unique dual effect on pore structure: in the early stages of diagenesis, zeolite extensively fills intergranular pores, leading to overall rock density and a significant decrease in effective porosity. However, in the later stages of diagenesis, due to its unstable chemical properties, it readily undergoes selective dissolution, resulting in the formation of large-sized secondary dissolution pores in localized areas. This mechanism leads to the heterogeneous reservoir characteristic of "low total porosity but large local pore sizes." Based on this mechanism, independent regression analysis of the experimentally obtained discrete pore size parameters confirmed this phenomenon.

[0083] like Figure 11 As shown, it illustrates the core parameters of basic logging, controlling factors, and the coupling between the dual minimum pore size and pressure, indicating a significant linear negative correlation between the minimum connected pore size of the rock and the sorting coefficient:

[0084] In the formula, Aperture component controlled by sorting coefficient ( S is the sorting coefficient (dimensionless) calculated from the electro-imaging data. This formula ( This directly quantifies the fundamental control effect of particle sorting on pore structure: the smaller the sorting coefficient (i.e., the better the sorting), the more uniform the particle packing, and the larger the effective connectivity pore size of the rock microstructure. This basic framework, combined with the subsequent zeolite filling-dissolution process, will jointly determine the final true connectivity of the reservoir.

[0085] Through discrete data regression, the minimum connected pore size of the rock and the content of zeolite exhibit a highly significant parabolic relationship, such as... Figure 12 As shown in the figure, the pore size exhibits a parabolic relationship of first increasing and then decreasing with the increase of zeolite content. This reveals that when zeolite is present in an appropriate amount, selective dissolution occurs to enlarge the pore size, while when the content is too high, physical filling and blockage predominate, leading to a sharp decrease in pore size.

[0086]

[0087] in, Pore ​​size component controlled by zeolite content ( ); The content of zeolite is expressed as a decimal. The formula indicates that when the zeolite content is moderate, late-stage selective dissolution dominates, and secondary dissolution pores cause the effective pore size to increase with the increase of content; however, when the content is too high, early physical filling and blocking effects dominate, leading to a sharp reduction in pore size.

[0088] Constructing the minimum connected pore size of rocks with dual intrinsic coupling ( The model is described in this application. Well Z, the target well in this embodiment, is a reservoir controlled by both sorting and zeolite content, but with poorly developed microfractures. A microfracture weighting coefficient is set. =0. The correlation coefficients of the effects of zeolite and sorting coefficient on the minimum interconnected pore size of the rock are both greater than 0.6, therefore... and Since both exist, the calculation model for the minimum connected pore size of the rock is simplified to a bivariate regression model. The core samples corresponding to well Z are then analyzed. Multiple regression analysis was performed on the values ​​and corresponding sorting coefficients and zeolite content to obtain the weight coefficients of the two factors, establishing a quantitative characterization formula. The sorting coefficient showed a significant monotonically negative correlation with the minimum connected pore size of the rock. However, zeolite exhibits a unique bidirectional effect on pore structure (when zeolite content is low, its dissolution effect is dominant, improving pore quality; conversely, when zeolite content is sufficiently high, it clogs pores, severely damaging the pore structure). Therefore, a piecewise bivariate regression model is needed.

[0089] When the zeolite content is below 15%, the zeolite content shows a positive correlation with the minimum interconnected pore size of the rock:

[0090] in, The content of zeolite is expressed as a decimal. The minimum connecting aperture of the rock. This is the sorting coefficient.

[0091] When the zeolite content is higher than 15%, both the zeolite content and the sorting coefficient show a negative correlation with the minimum connected pore size of the rock.

[0092] in, The content of zeolite is expressed as a decimal. The minimum connecting aperture of the rock. This is the sorting coefficient.

[0093] The minimum interconnected pore size of the rock samples corresponding to well Z is determined. ) and the corresponding measured maximum capillary force ( Perform regression analysis. For example... Figure 13 As shown, the maximum capillary force exhibits a significant linear decrease with increasing minimum pore size in the rock, demonstrating the direct control of the microscopic pore throat scale over the macroscopic capillary driving force. Based on this, a pressure-pore size conversion model is established:

[0094] in, This represents the maximum capillary force (MPa). Minimum diameter of the connecting hole in the rock ( ), This model quantifies the relationship between maximum capillary force and minimum pore size under dual-factor control, providing a benchmark pressure threshold for subsequent determination of the true filling state of the target layer.

[0095] Minimum pore size for oil and gas injection under formation conditions ( Segmented model. For example... Figure 14 As shown, the positive correlation between the two reveals that the stronger the heterogeneity of the rock pore structure (i.e., the greater the difference between the two pore sizes), the greater the effective additional driving pressure difference that needs to be overcome when fluid is filled or flows between pores of different sizes.

[0096] Introducing current formation pore pressure ( ) as an external dependent variable. When At that time, the oil and gas were fully charged and set ;when At that time, insufficient oil and gas filling prevented the oil and gas from filling to the smallest pores. The "dual pore size difference" of the unsaturated sample was utilized. ")" and "unsaturated pressure difference" Based on the regression relationship of "), an empirical formula is established:

[0097] in, Minimum pore size for oil and gas injection under formation conditions ( ), Minimum diameter of the connecting hole in the rock ( ), This represents the current pore pressure of the formation (MPa). This represents the maximum capillary force (MPa). This formula allows for the dynamic calculation of the lower limit of the actual formation oil and gas injection pore size under two-factor control.

[0098] Constructing a nonlinear variable T2 cutoff value ( The transformation model is different from the first embodiment (single transformation coefficient). Unlike other conditions, under the influence of two factors, the pore throat structure becomes extremely complex, and the relationship between pore size and T2 relaxation time is no longer a simple linear one. Based on core high-pressure mercury intrusion porosimetry and nuclear magnetic resonance (NMR) data, this application establishes a piecewise power function transformation model.

[0099] When the pore size is small (micropores dominated by sorting and compaction):

[0100] in, This is the key relaxation time point. Minimum pore size for oil and gas injection under formation conditions ( ).

[0101] When the pore size is large (secondary macropores dominated by zeolite dissolution):

[0102] in, This is the key relaxation time point. Minimum pore size for oil and gas injection under formation conditions ( ).

[0103] Based on this, the oil saturation of the target well at the target depth is determined according to the key relaxation time points and the T2 spectrum of the well logging nuclear magnetic resonance. Thus, a continuous oil saturation curve for the entire well section of Well Z can be obtained. This application's embodiment uses... Figure 15Taking Well Z as an example, the application effect is analyzed. The reservoir in this well area has extremely strong heterogeneity. Its oil-bearing capacity is not only controlled by the sorting of sedimentary particles, but also modified by the complex diagenetic processes of interstitial materials such as zeolite. Addressing the contradiction between the low-porosity and tight characteristics observed in conventional logging, and the complex reservoir exhibiting "low total porosity and high local productivity" due to early filling and late selective dissolution of zeolite, this application's embodiment establishes a dynamic correction model controlled by the coupling of two intrinsic factors: "sorting coefficient + zeolite content," achieving accurate evaluation of this type of reservoir.

[0104] This application utilizes well logging data to continuously invert reservoir sorting parameters and identify zeolite-developed sections. Combined with current formation pore pressure, it determines the oil and gas charging dynamics, thereby dynamically outputting a variable T2 cutoff value that changes with the micropore structure. This model can accurately identify the sudden increase in the true effective pore size caused by zeolite dissolution, effectively classifying dissolution macropores originally obscured by "low-porosity pseudomorphs" as effective oil-bearing spaces. This significantly improves the accuracy of oil-bearing calculations for such dissolution sections, identifying "poorly dense layers" that are easily missed by traditional fixed cutoff value methods as high-saturation oil-bearing "sweet spots." Actual oil testing results show that, after re-evaluating the oil-bearing properties of the target sections at depths of 4385-4400m and 4320-4410m in this application, high-yield industrial oil and gas flows of 24.17 tons of oil / 63,300 cubic meters of gas per day and 27.26 tons of oil / 230,200 cubic meters of gas per day were obtained, respectively.

[0105] Taking the fourth embodiment as an example: For well D, on the one hand, clay has a physical filling and spatial separation effect on the reservoir pore structure, which will refine the effective pores and increase the specific surface area, thereby increasing the formation bound water saturation. Independent regression analysis of discrete experimental data confirms that the clay content ( There is a significant linear negative correlation between the minimum connected pore size of the rock and the minimum connected pore size, such as... Figure 16 As shown in the following formula:

[0106] in, It is the clay content. Minimum connecting aperture of the rock ( ).

[0107] On the other hand, the extensive development of microfractures greatly improves the seepage network of tight reservoirs, connecting previously isolated micropores and effectively altering the original capillary confinement state. For example... Figure 17 As shown, discrete data regression reveals a pattern: the more developed the microfractures, the smaller the breakthrough force required for reservoir displacement fluids, and the significantly smaller the minimum interconnected pore size in the rock. Microfracture development index (… The minimum connected pore size of the rock exhibits a highly significant exponential negative correlation with the rock's minimum connected pore size, as shown in the following formula:

[0108] in, This refers to the microcrack development index. Minimum connecting aperture of the rock ( ).

[0109] A dual-factor coupled rock minimum connected pore size model for well D is constructed. Since a single factor cannot fully characterize the true state of the pore structure of the reservoir where well D is located, this embodiment comprehensively considers the influence of clay content and microfracture development. Using regression statistics, the experimentally obtained rock minimum connected pore size is subjected to multiple linear regression analysis with clay content and the microfracture development index (logarithmic form), constructing a dual-factor characterization formula to directly predict the rock minimum connected pore size:

[0110] in, It is the clay content. This refers to the microcrack development index. Minimum connecting aperture of the rock ( ).

[0111] The regression statistics show that the correlation coefficient of this multiple regression model is as high as 0.9257, which significantly improves the goodness of fit and prediction accuracy compared with the single-factor model (correlation coefficient between 0.60 and 0.78).

[0112] Constructing maximum capillary force ( ) conversion model. In conventional procedures, the maximum capillary force is usually obtained through high-pressure mercury intrusion porosimetry (HIP) experiments. Given the lack of HIP data in well D, this embodiment utilizes nuclear magnetic resonance (NMR) data to reflect the characteristics of reservoir pore structure, selecting the geometric mean of NMR T2, which is closely related to the average pore throat radius of the reservoir. Using as the independent variable, a regression analysis was performed on the measured maximum capillary force of the core sample and the corresponding geometric mean of NMR T2. Figure 18 It can be seen that the two exhibit a clear exponential decay relationship:

[0113] in, Maximum capillary force (MPa); Minimum connecting aperture of the rock ( ).

[0114] It is evident that the larger the geometric mean of T2, the better the macroscopic physical properties and microscopic connectivity of the reservoir, and the smaller the maximum capillary force required for fluid to break through the rock pore throat, thus enabling effective prediction of the maximum capillary force of the formation without mercury pressure data.

[0115] Furthermore, a segmented model of the minimum pore size for hydrocarbon injection under formation conditions is constructed. Current formation pore pressure is introduced. As an external factor driving hydrocarbon accumulation, and combined with the maximum capillary force obtained above ( To determine the true filling state of the formation: when At this point, it indicates that the current formation dynamics are sufficient, and oil and gas have been injected to the minimum limit allowed by rock physics. At this time, the "minimum pore size for oil and gas injection under formation conditions" is equal to the obtained "minimum interconnected pore size of the rock" (i.e., ).

[0116] when This indicates that the current formation charging power is insufficient, and oil and gas cannot enter the partially connected micropores. The difference between the "minimum pore size for oil and gas charging" and the "minimum connected pore size in the rock" is defined as the "dual-pore size difference" (or "dual-pore size difference"). Using experimental data from incompletely saturated samples, the "dual-aperture difference" and the "unsaturated pressure difference" were compared. Perform linear regression, such as Figure 19 As shown, the following empirical formula is established:

[0117] in, Minimum orifice diameter for oil and gas filling. The minimum connecting aperture of the rock. This represents the maximum capillary force (MPa). This represents the current pore pressure of the formation.

[0118] The above formula intuitively reflects the phenomenon that the smaller the effective charging pressure differential, the higher the proportion of micropores that fail to inject oil, thus leading to a larger offset in the cutoff value. Based on the above mechanisms, a segmented dynamic characterization model for the minimum pore size of oil and gas charging under the formation conditions of well D is finally constructed:

[0119] in, Minimum orifice diameter for oil and gas filling. The minimum connecting aperture of the rock. This represents the maximum capillary force (MPa). This represents the current pore pressure of the formation.

[0120] Finally, a linear transformation model between the variable aperture and the NMR T2 relaxation time was used to obtain continuous variable T2 cutoff values, and the NMR logging T2 spectrum of the entire D well section was dynamically processed. For each depth point, the oil phase signal component greater than the cutoff value was integrated and substituted into the basic model described above, thus accurately calculating the oil saturation curve under actual formation conditions. Figure 20 As shown, the oil testing data for the 7955-8035m section indicates a maximum daily oil production of 21.5t, a maximum daily gas production of 0.095 million m3, and a maximum daily water production of 119.52 m3, concluding that it is an oil-water-bearing layer. The oil testing data for the 8214-8260m section indicates a daily oil production of 174.81t and a daily gas production of 1,074,790 m3, concluding that it is a co-existing oil and gas layer. The injectable oil saturation under formation conditions calculated using the method described in this application is consistent with the oil testing data, effectively guiding the fluid identification and evaluation of deep and complex reservoirs.

[0121] This application also provides an apparatus for determining oil saturation under reservoir conditions, comprising: The memory is configured to store instructions; and the processor is configured to retrieve instructions from memory and, when executing instructions, to: The target well is obtained at the target depth. The target micropore structure characteristics, formation pore pressure, nuclear magnetic resonance logging T2 spectrum of the target well, and multiple core samples from the target well are obtained. The target micropore structure characteristics include at least one of sorting coefficient, interstitial material content, and microfracture development index. Dual-pressure nuclear magnetic resonance (NMR) experiments were conducted on multiple core samples from the target well to construct a rock minimum connectivity pore size characterization model. Based on the rock minimum connectivity pore size characterization model, the rock minimum connectivity pore size of the target well at the target depth is determined according to the target micropore structure characteristics. The rock minimum connectivity pore size is the minimum pore-throat diameter in the pore-throat connectivity network of the target well at the target depth under the preset maximum charging pressure differential. Determine the maximum capillary force of the target well at the target depth based on the minimum connecting aperture of the rock. Based on the minimum pore size characterization model for oil and gas injection, the minimum pore size for oil and gas injection at the target depth of the target well is determined according to the formation pore pressure, maximum capillary force and minimum interconnected pore size of the rock. Based on the pre-constructed correspondence between pore diameter and relaxation time point, the key relaxation time point is determined according to the minimum pore diameter for oil and gas injection. The oil saturation of the target well at the target depth is determined based on the key relaxation time point and the T2 spectrum of nuclear magnetic resonance logging.

[0122] This application also provides a machine-readable storage medium storing instructions for causing a machine to execute either the method described above for constructing a rock minimum interconnected pore size model or the method described above for determining oil saturation.

[0123] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0124] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0125] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0126] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0127] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0128] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0129] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0130] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0131] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for determining oil saturation under reservoir conditions, characterized in that, The determination method includes: The target well is obtained at the target depth, including the target micropore structure characteristics, formation pore pressure, nuclear magnetic resonance logging T2 spectrum of the target well, and multiple core samples from the target well. The target micropore structure characteristics include at least one of sorting coefficient, interstitial material content, and microfracture development index. Dual-pressure nuclear magnetic resonance (NMR) experiments were conducted on multiple core samples from the target well to construct a rock minimum interconnected pore size characterization model. Based on the rock minimum connectivity pore size characterization model, the rock minimum connectivity pore size of the target well at the target depth is determined according to the target micropore structure characteristics, wherein the rock minimum connectivity pore size is the minimum pore throat diameter in the pore-throat connectivity network of the target well at the target depth under the preset maximum charging pressure differential; The maximum capillary force of the target well at the target depth is determined based on the minimum connecting aperture of the rock. Based on the minimum pore size characterization model for oil and gas injection, the minimum pore size for oil and gas injection of the target well at the target depth is determined according to the formation pore pressure, the maximum capillary force, and the minimum interconnected pore size of the rock. Based on the pre-constructed correspondence between pore diameter and relaxation time point, the key relaxation time point is determined according to the minimum pore diameter for oil and gas injection. The oil saturation of the target well at the target depth is determined based on the key relaxation time point and the nuclear magnetic resonance logging T2 spectrum.

2. The method according to claim 1, characterized in that, The method of conducting dual-pressure nuclear magnetic resonance (NMR) experiments on multiple core samples from the target well to construct a rock minimum connectivity pore size characterization model includes: The microstructure characteristics of each core sample, the paleostratus pore pressure at the beginning of hydrocarbon accumulation, and the current pore pressure of the formation were obtained. The simulated hydrocarbon injection pressure difference for each core sample is determined based on the paleostrata pore pressure and the present strata pore pressure. Dual-pressure nuclear magnetic resonance (NMR) experiments were performed on each core sample to obtain the first NMR T2 spectrum of each core sample under a fully water-saturated state and at the corresponding simulated oil and gas injection pressure difference, and the second NMR T2 spectrum of each core sample under the preset maximum injection pressure difference. The minimum pore size of the rock in each core sample is determined based on the first nuclear magnetic resonance T2 spectrum and the corresponding second nuclear magnetic resonance T2 spectrum. Based on the minimum connected pore size of each core sample and the corresponding micropore structure characteristics, determine the weighting coefficients corresponding to each micropore structure characteristic. The minimum connected aperture characterization model of the rock corresponding to the target well is obtained based on the weighting coefficients.

3. The method according to claim 2, characterized in that, The rock minimum connectivity aperture characterization model includes: in, The minimum connecting aperture of the rock in the target well. Sorting coefficient The regression function between the minimum connected aperture of the rock and the minimum connected aperture. interstitial content The regression function between the minimum connected aperture of the rock and the minimum connected aperture. Microcrack development index The regression function between the minimum connected aperture of the rock and the minimum connected aperture. , as well as Sorting coefficients interstitial content and microcrack development index The corresponding weighting coefficients, This is a constant term.

4. The method according to claim 2, characterized in that, The step of determining the minimum connected pore size of each core sample based on the first nuclear magnetic resonance T2 spectrum and the corresponding second nuclear magnetic resonance T2 spectrum includes: The measured oil phase signal area of ​​each core sample was determined based on the second nuclear magnetic resonance T2 spectrum; By performing inverse cumulative summation from the maximum relaxation time point of the first nuclear magnetic resonance T2 spectrum, the target relaxation time point of each core sample within the first nuclear magnetic resonance T2 spectrum is determined, such that the oil phase signal area between the target relaxation time point and the maximum relaxation time point is equal to the measured oil phase signal area. Based on the pre-constructed correspondence between pore diameter and relaxation time point, the minimum connected pore diameter of each core sample is determined according to the target relaxation time point.

5. The method according to claim 2, characterized in that, The method of performing dual-pressure nuclear magnetic resonance (NMR) experiments on each core sample to obtain the first NMR T2 spectrum of each core sample under a fully water-saturated state and at the corresponding simulated oil and gas injection pressure differential, and the second NMR T2 spectrum of each core sample under the preset maximum injection pressure differential, includes: Based on the simulated oil and gas injection pressure difference, nuclear magnetic resonance (NMR) tests were conducted on each of the core samples to obtain the first NMR T2 spectrum and the corresponding two-dimensional NMR spectrum of each core sample under a fully water-saturated state. Based on the simulated oil and gas injection pressure difference, heavy water was used to displace the formation water in each of the core samples under a fully water-saturated state, so as to obtain the third nuclear magnetic resonance T2 spectrum and the corresponding two-dimensional nuclear magnetic spectrum of each core sample under heavy water saturation. Based on the simulated oil and gas injection pressure difference, crude oil was used to displace the heavy water in each of the core samples under heavy water saturation, so as to obtain the fourth nuclear magnetic resonance T2 spectrum and the corresponding two-dimensional nuclear magnetic spectrum of each of the core samples after the heavy water was displaced by crude oil. Increase the simulated oil and gas charging pressure difference, use crude oil to displace the heavy water in each of the core samples after the crude oil has displaced the heavy water, and conduct nuclear magnetic resonance (NMR) tests until the nuclear magnetic resonance T2 spectrum and two-dimensional NMR spectrum in the NMR tests no longer change, so as to obtain the second nuclear magnetic resonance T2 spectrum and the corresponding two-dimensional NMR spectrum of each of the core samples under the preset maximum charging pressure difference.

6. The method according to claim 5, characterized in that, The determination method further includes: Based on the first nuclear magnetic resonance T2 spectrum and the fourth nuclear magnetic resonance T2 spectrum, the first simulated oil saturation of each core sample under the simulated oil and gas injection pressure difference is determined. Based on the first nuclear magnetic resonance T2 spectrum and the second nuclear magnetic resonance T2 spectrum, the second simulated oil saturation of each core sample under the preset maximum charging pressure difference is determined; When the first simulated oil saturation is equal to the corresponding second simulated oil saturation, the oil and gas charging state of each core sample is determined to be a saturated oil and gas charging state. When the first simulated oil saturation is less than the corresponding second simulated oil saturation, the oil and gas charging state of each core sample is determined to be an unsaturated oil and gas charging state.

7. The method according to claim 1, characterized in that, The oil and gas injection minimum pore size characterization model determines the minimum oil and gas injection pore size of the target well at the target depth based on the formation pore pressure, the maximum capillary force, and the minimum interconnected pore size of the rock, including: When the formation pore pressure is greater than or equal to the maximum capillary force, the minimum connecting pore diameter of the rock is determined as the minimum pore diameter for oil and gas injection. When the formation pore pressure is less than the maximum capillary force, the minimum connecting pore diameter of the rock is corrected according to the formation pore pressure and the maximum capillary force to obtain the minimum pore diameter for oil and gas injection.

8. The method according to claim 7, characterized in that, The step of correcting the minimum pore size of the rock based on the formation pore pressure and the maximum capillary force to obtain the minimum pore size for oil and gas injection includes: Determine the deviation between the formation pore pressure and the maximum capillary force; Determine the correction value based on the deviation value; The sum of the correction value and the minimum connecting pore diameter of the rock is determined to obtain the minimum pore diameter for oil and gas injection.

9. The method according to claim 1, characterized in that, The determination of the oil saturation of the target well at the target depth based on the key relaxation time point and the nuclear magnetic resonance logging T2 spectrum includes: Determine the oil phase signal area corresponding to the key relaxation time point in the nuclear magnetic resonance logging T2 spectrum; Determine the total signal area corresponding to the T2 spectrum of the nuclear magnetic resonance logging; The ratio of the oil phase signal area to the total signal area is determined to obtain the oil saturation of the target well at the target depth.

10. A device for determining oil saturation under reservoir conditions, characterized in that, include: The memory is configured to store instructions; as well as A processor for recalling the instructions from the memory and, when executing the instructions, configuring the processor to: The target well is obtained at the target depth, including the target micropore structure characteristics, formation pore pressure, nuclear magnetic resonance logging T2 spectrum of the target well, and multiple core samples from the target well. The target micropore structure characteristics include at least one of sorting coefficient, interstitial material content, and microfracture development index. Dual-pressure nuclear magnetic resonance (NMR) experiments were conducted on multiple core samples from the target well to construct a rock minimum interconnected pore size characterization model. Based on the rock minimum connectivity pore size characterization model, the rock minimum connectivity pore size of the target well at the target depth is determined according to the target micropore structure characteristics, wherein the rock minimum connectivity pore size is the minimum pore throat diameter in the pore-throat connectivity network of the target well at the target depth under the preset maximum charging pressure differential; The maximum capillary force of the target well at the target depth is determined based on the minimum connecting aperture of the rock. Based on the minimum pore size characterization model for oil and gas injection, the minimum pore size for oil and gas injection of the target well at the target depth is determined according to the formation pore pressure, the maximum capillary force, and the minimum interconnected pore size of the rock. Based on the pre-constructed correspondence between pore diameter and relaxation time point, the key relaxation time point is determined according to the minimum pore diameter for oil and gas injection. The oil saturation of the target well at the target depth is determined based on the key relaxation time point and the nuclear magnetic resonance logging T2 spectrum.

11. The apparatus according to claim 10, characterized in that, The processor is further configured to: The microstructure characteristics of each core sample, the paleostratus pore pressure at the beginning of hydrocarbon accumulation, and the current pore pressure of the formation were obtained. The simulated hydrocarbon injection pressure difference for each core sample is determined based on the paleostrata pore pressure and the present strata pore pressure. Dual-pressure nuclear magnetic resonance (NMR) experiments were performed on each core sample to obtain the first NMR T2 spectrum of each core sample under a fully water-saturated state and at the corresponding simulated oil and gas injection pressure difference, and the second NMR T2 spectrum of each core sample under the preset maximum injection pressure difference. The minimum pore size of the rock in each core sample is determined based on the first nuclear magnetic resonance T2 spectrum and the corresponding second nuclear magnetic resonance T2 spectrum. Based on the minimum connected pore size of each core sample and the corresponding micropore structure characteristics, determine the weighting coefficients corresponding to each micropore structure characteristic. The minimum connected aperture characterization model of the rock corresponding to the target well is obtained based on the weighting coefficients.

12. The apparatus according to claim 11, characterized in that, The rock minimum connectivity aperture characterization model includes: in, The minimum connecting aperture of the rock in the target well. Sorting coefficient The regression function between the minimum connected aperture of the rock and the minimum connected aperture. interstitial content The regression function between the minimum connected aperture of the rock and the minimum connected aperture. Microcrack development index The regression function between the minimum connected aperture of the rock and the minimum connected aperture. , as well as Sorting coefficients interstitial content and microcrack development index The corresponding weighting coefficients, This is a constant term.

13. The apparatus according to claim 11, characterized in that, The processor is further configured to: The measured oil phase signal area of ​​each core sample was determined based on the second nuclear magnetic resonance T2 spectrum; By performing inverse cumulative summation from the maximum relaxation time point of the first nuclear magnetic resonance T2 spectrum, the target relaxation time point of each core sample within the first nuclear magnetic resonance T2 spectrum is determined, such that the oil phase signal area between the target relaxation time point and the maximum relaxation time point is equal to the measured oil phase signal area. Based on the pre-constructed correspondence between pore diameter and relaxation time point, the minimum connected pore diameter of each core sample is determined according to the target relaxation time point.

14. The apparatus according to claim 11, characterized in that, The processor is further configured to: Based on the simulated oil and gas injection pressure difference, nuclear magnetic resonance (NMR) tests were conducted on each of the core samples to obtain the first NMR T2 spectrum and the corresponding two-dimensional NMR spectrum of each core sample under a fully water-saturated state. Based on the simulated oil and gas injection pressure difference, heavy water was used to displace the formation water in each of the core samples under a fully water-saturated state, so as to obtain the third nuclear magnetic resonance T2 spectrum and the corresponding two-dimensional nuclear magnetic spectrum of each core sample under heavy water saturation. Based on the simulated oil and gas injection pressure difference, crude oil was used to displace the heavy water in each of the core samples under heavy water saturation, so as to obtain the fourth nuclear magnetic resonance T2 spectrum and the corresponding two-dimensional nuclear magnetic spectrum of each of the core samples after the heavy water was displaced by crude oil. Increase the simulated oil and gas charging pressure difference, use crude oil to displace the heavy water in each of the core samples after the crude oil has displaced the heavy water, and conduct nuclear magnetic resonance (NMR) tests until the nuclear magnetic resonance T2 spectrum and two-dimensional NMR spectrum in the NMR tests no longer change, so as to obtain the second nuclear magnetic resonance T2 spectrum and the corresponding two-dimensional NMR spectrum of each of the core samples under the preset maximum charging pressure difference.

15. The apparatus according to claim 14, characterized in that, The processor is further configured to: Based on the first nuclear magnetic resonance T2 spectrum and the fourth nuclear magnetic resonance T2 spectrum, the first simulated oil saturation of each core sample under the simulated oil and gas injection pressure difference is determined. Based on the first nuclear magnetic resonance T2 spectrum and the second nuclear magnetic resonance T2 spectrum, the second simulated oil saturation of each core sample under the preset maximum charging pressure difference is determined; When the first simulated oil saturation is equal to the corresponding second simulated oil saturation, the oil and gas charging state of each core sample is determined to be a saturated oil and gas charging state. When the first simulated oil saturation is less than the corresponding second simulated oil saturation, the oil and gas charging state of each core sample is determined to be an unsaturated oil and gas charging state.

16. The apparatus according to claim 10, characterized in that, The processor is further configured to: When the formation pore pressure is greater than or equal to the maximum capillary force, the minimum connecting pore diameter of the rock is determined as the minimum pore diameter for oil and gas injection. When the formation pore pressure is less than the maximum capillary force, the minimum connecting pore diameter of the rock is corrected according to the formation pore pressure and the maximum capillary force to obtain the minimum pore diameter for oil and gas injection.

17. The apparatus according to claim 16, characterized in that, The processor is further configured to: Determine the deviation between the formation pore pressure and the maximum capillary force; Determine the correction value based on the deviation value; The sum of the correction value and the minimum connecting pore diameter of the rock is determined to obtain the minimum pore diameter for oil and gas injection.

18. The apparatus according to claim 10, characterized in that, The processor is further configured to: Determine the oil phase signal area corresponding to the key relaxation time point in the nuclear magnetic resonance logging T2 spectrum; Determine the total signal area corresponding to the T2 spectrum of the nuclear magnetic resonance logging; The ratio of the oil phase signal area to the total signal area is determined to obtain the oil saturation of the target well at the target depth.

19. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores instructions for causing the machine to perform the method for determining oil saturation based on reservoir conditions according to any one of claims 1 to 9.

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