Method and device for predicting gas saturation of reservoir

Abstract

The application provides a reservoir gas saturation prediction method and device, and relates to the technical field of reservoir evaluation. The method comprises the following steps: obtaining measurement data of a target rock sample in a target reservoir, wherein the measurement data comprises total porosity, irreducible water saturation, nuclear magnetic resonance T2 spectrum of saturated water state, and nuclear magnetic resonance T2 spectrum of partially saturated water state; determining a fractal dimension value of a nuclear magnetic resonance T2 spectrum pore volume integral logarithmic discrete curve of a movable fluid part of the target rock sample according to the measurement data; determining a plurality of water saturation fractal dimension equation coefficients of the target rock sample according to the fractal dimension value; determining a plurality of target equation coefficients according to the fractal dimension value and the irreducible water saturation; and calculating the gas saturation at the depth of the target rock sample in the target reservoir according to the fractal dimension value, the irreducible water saturation, a gas saturation equation, the plurality of water saturation fractal dimension equation coefficients, and the plurality of target equation coefficients. The calculation precision of the gas saturation can be effectively improved.

Description

Technical Field

[0001] This application relates to the field of reservoir evaluation technology, and in particular to a method and apparatus for predicting reservoir gas saturation. Background Technology

[0002] Reservoir gas saturation refers to the percentage of natural gas volume in the reservoir relative to the volume of interconnected pores under original conditions. Estimating reservoir gas saturation is a key factor in calculating the resource size of tight sandstone gas reservoirs.

[0003] In some implementations, gas saturation in sandstone reservoirs is calculated using Archie's formula and a modified function model based on Archie's formula. For example, gas saturation is calculated from resistivity logging data based on the relationship between sandstone resistivity, porosity, and water saturation.

[0004] However, the accuracy of gas saturation calculations for tight sandstone reservoirs based on resistivity logging data is relatively low. Summary of the Invention

[0005] This application provides a method and apparatus for predicting reservoir gas saturation, which solves the technical problem of low accuracy in calculating the gas saturation of tight sandstone reservoirs based on resistivity logging data.

[0006] In a first aspect, this application provides a method for predicting the gas saturation of a reservoir. The method includes: acquiring measurement data of a target rock sample in a target reservoir, the measurement data including total porosity, bound water saturation, nuclear magnetic resonance T2 spectrum of saturated water state and nuclear magnetic resonance T2 spectrum of partially saturated water state; wherein, the partially saturated water state includes at least two states of the target rock sample, and the partially saturated water state includes the state corresponding to the bound water saturation of the target rock sample.

[0007] The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid portion of the target rock sample is determined based on the measurement data.

[0008] The coefficients of multiple water saturation fractal dimension equations for the target rock sample are determined based on the fractal dimension values; and the coefficients of multiple target equations are determined based on the fractal dimension values ​​and the bound water saturation.

[0009] The gas saturation at the depth of the target rock sample in the target reservoir is calculated based on the fractal dimension value, bound water saturation, gas saturation equation, coefficients of multiple water saturation fractal dimension equations, and coefficients of multiple target equations.

[0010] In one possible implementation, the gas saturation equation is:

[0011] S g =1-[c1·(D v -d1·S wi+d2) 2 +c2·(D v -d1·S wi +d2)+c3]

[0012] Among them, S g D represents the gas saturation at the depth where the target rock sample is located in the target reservoir. v S represents the fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid component; wi d1 represents the bound water saturation; d2 represents the coefficients of the first objective equation; c1 represents the coefficients of the fractal dimension equation for the first water saturation; c2 represents the coefficients of the fractal dimension equation for the second water saturation; and c3 represents the coefficients of the fractal dimension equation for the third water saturation.

[0013] In one possible implementation, the fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid portion of the target rock sample is determined based on measurement data, including:

[0014] The pore volume integral discrete curves of the NMR T2 spectra of the target rock sample in saturated and partially saturated water states were determined based on the total porosity, the NMR T2 spectra in saturated water state, and the NMR T2 spectra in partially saturated water state.

[0015] The logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid component is determined based on the pore volume integral discrete curve of the nuclear magnetic resonance T2 spectrum of the target rock sample in the states of bound water saturation and saturated and partially saturated water.

[0016] Based on the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid part and the fractal dimension function equation, the fractal dimension value of the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid part is obtained by the least squares method.

[0017] The fractal dimension function equation satisfies:

[0018] Log 10 (S v (t))=A·Log 10 (t)+B, t∈[T2cut, T2_max]

[0019] Among them, S v (t) represents the numerical value of the T2 spectrum pore volume integral discrete curve at time t; t is the T2 relaxation time; T2_max is the maximum T2 time of the T2 spectrum discrete curve; T2cut is the cutoff time; A is the coefficient of the first fractal dimension equation, and B is the coefficient of the second fractal dimension equation.

[0020] The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part satisfies the formula:

[0021] D v =3-A

[0022] Among them, D v The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid component is given.

[0023] In one possible implementation, the discrete curves of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states satisfy the following:

[0024]

[0025] Among them, S v (t) represents the discrete curve of the pore volume integral of the T2 spectrum at time t; S T2 (t) represents the pore amplitude of the T2 spectrum at time t; T2_min represents the minimum T2 time of the discrete curve of the pore volume integral of the T2 spectrum; φ t S represents the total porosity. w Water saturation of the target rock sample.

[0026] In one possible implementation, the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum for the movable fluid portion is determined based on the bound water saturation and the discrete curves of the pore volume integral of the nuclear magnetic resonance T2 spectrum for the saturated and partially saturated water states of the target rock sample, including:

[0027] The cutoff time is determined based on the bound water saturation and the pore volume integral discrete curve of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states.

[0028] Based on the deadline and the discrete curves of the pore volume integral of the NMR T2 spectrum of the target rock sample in both saturated and partially saturated water states, the piecewise curves of the pore volume integral logarithmic discrete curves of the NMR T2 spectrum of the target rock sample in both saturated and partially saturated water states are determined; wherein, the piecewise curves satisfy:

[0029]

[0030] Among them, S v (t) represents the value of the T2 spectrum pore volume integral discrete curve at time t; T2_min is the minimum T2 time of the T2 spectrum discrete curve; T2_max is the maximum T2 time of the T2 spectrum discrete curve; T2cut is the cutoff time.

[0031] The discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part is the piecewise curve corresponding to t∈[T2cut,T2_max].

[0032] In one possible implementation, the coefficients of multiple fractal dimension equations for the water saturation of the target rock sample are determined based on the fractal dimension values, including:

[0033] The relative value of the fractal dimension is determined based on the numerical value of the fractal dimension, where the relative value of the fractal dimension satisfies the formula:

[0034] ΔD v =D v -D v，sw＝1

[0035] Where, ΔD v D is the relative value of the fractal dimension. v，sw＝1 The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid portion of the target rock sample in saturated water state.

[0036] Based on the relative value of the fractal dimension and the fractal dimension equation of water saturation, multiple coefficients of the fractal dimension equation of water saturation are obtained through the least squares method. The fractal dimension equation of water saturation satisfies the following:

[0037] S w =c1·ΔD v 2 +c2·ΔD v +c3

[0038] Among them, S w ΔD represents the water saturation of the target rock sample. v The water saturation is S w The relative values ​​of the fractal dimension of the rock sample; c1 is the coefficient of the fractal dimension equation for the first water saturation, c2 is the coefficient of the fractal dimension equation for the second water saturation, and c3 is the coefficient of the fractal dimension equation for the third water saturation.

[0039] In one possible implementation, multiple objective equation coefficients are determined based on the fractal dimension value and the bound water saturation, including:

[0040] Based on the fractal dimension value, the bound water saturation, and the equation relating the fractal dimension of saturated water to the bound water saturation, the coefficients of multiple objective equations are determined by the least squares method.

[0041] The equation relating the saturated water volume dimension to the bound water saturation degree satisfies:

[0042] D v，sw＝1 =d1·S wi +d2

[0043] Among them, Swi d1 represents the bound water saturation; d2 represents the coefficients of the first objective equation; and d2 represents the coefficients of the second objective equation.

[0044] Secondly, this application provides a reservoir gas saturation prediction device, which includes an acquisition module, a first determination module, a second determination module, and a calculation module, wherein...

[0045] The acquisition module is used to acquire measurement data of target rock samples in the target reservoir. The measurement data includes total porosity, bound water saturation, nuclear magnetic resonance T2 spectrum of saturated water state and nuclear magnetic resonance T2 spectrum of partially saturated water state; wherein, the partially saturated water state includes at least two states of the target rock sample, and the partially saturated water state includes the state corresponding to the bound water saturation of the target rock sample.

[0046] The first determining module is used to determine the fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part of the target rock sample based on the measurement data.

[0047] The second determining module is used to determine the coefficients of multiple water saturation fractal dimension equations of the target rock sample based on the fractal dimension values; and to determine the coefficients of multiple target equations based on the fractal dimension values ​​and the bound water saturation.

[0048] The calculation module is used to calculate the gas saturation at the depth of the target rock sample in the target reservoir based on the fractal dimension value, bound water saturation, gas saturation equation, coefficients of multiple water saturation fractal dimension equations, and coefficients of multiple target equations.

[0049] In one possible implementation, the gas saturation equation is:

[0050] S g =1-[c1·(D v -d1·S wi +d2) 2 +c2·(D v -d1·S wi +d2)+c3]

[0051] Among them, S g D represents the gas saturation at the depth where the target rock sample is located in the target reservoir. v S represents the fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid component; wi d1 represents the bound water saturation; d2 represents the coefficients of the first objective equation; c1 represents the coefficients of the fractal dimension equation for the first water saturation; c2 represents the coefficients of the fractal dimension equation for the second water saturation; and c3 represents the coefficients of the fractal dimension equation for the third water saturation.

[0052] In one possible implementation, the first determining module is specifically used for:

[0053] The pore volume integral discrete curves of the NMR T2 spectra of the target rock sample in saturated and partially saturated water states were determined based on the total porosity, the NMR T2 spectra in saturated water state, and the NMR T2 spectra in partially saturated water state.

[0054] The logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid component is determined based on the pore volume integral discrete curve of the nuclear magnetic resonance T2 spectrum of the target rock sample in the states of bound water saturation and saturated and partially saturated water.

[0055] Based on the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid part and the fractal dimension function equation, the fractal dimension value of the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid part is obtained by the least squares method.

[0056] The fractal dimension function equation satisfies:

[0057] Log 10 (S v (t))=A·Log 10 (t)+B, t∈[T2cut, T2_max]

[0058] Among them, S v (t) represents the numerical value of the T2 spectrum pore volume integral discrete curve at time t; t is the T2 relaxation time; T2_max is the maximum T2 time of the T2 spectrum discrete curve; T2cut is the cutoff time; A is the coefficient of the first fractal dimension equation, and B is the coefficient of the second fractal dimension equation.

[0059] The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part satisfies the formula:

[0060] D v =3-A

[0061] Among them, D v The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid component is given.

[0062] In one possible implementation, the discrete curves of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states satisfy the following:

[0063]

[0064] Among them, S v (t) represents the discrete curve of the pore volume integral of the T2 spectrum at time t; S T2(t) represents the pore amplitude of the T2 spectrum at time t; T2_min represents the minimum T2 time of the discrete curve of the pore volume integral of the T2 spectrum; φ t S represents the total porosity. w The water saturation of the target rock sample.

[0065] In one possible implementation, the first determining module is specifically used for:

[0066] The cutoff time is determined based on the bound water saturation and the pore volume integral discrete curve of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states.

[0067] Based on the deadline and the discrete curves of the pore volume integral of the NMR T2 spectrum of the target rock sample in both saturated and partially saturated water states, the piecewise curves of the pore volume integral logarithmic discrete curves of the NMR T2 spectrum of the target rock sample in both saturated and partially saturated water states are determined; wherein, the piecewise curves satisfy:

[0068]

[0069] Among them, S v (t) represents the value of the T2 spectrum pore volume integral discrete curve at time t; T2_min is the minimum T2 time of the T2 spectrum discrete curve; T2_max is the maximum T2 time of the T2 spectrum discrete curve; T2cut is the cutoff time.

[0070] The discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part is the piecewise curve corresponding to t∈[T2cut,T2_max].

[0071] In one possible implementation, the second determining module is specifically used for

[0072] The relative value of the fractal dimension is determined based on the numerical value of the fractal dimension, where the relative value of the fractal dimension satisfies the formula:

[0073] ΔD v =D v -D v，sw＝1

[0074] Where, ΔD v D is the relative value of the fractal dimension. v，sw＝1 The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid portion of the target rock sample in saturated water state.

[0075] Based on the relative value of the fractal dimension and the fractal dimension equation of water saturation, multiple coefficients of the fractal dimension equation of water saturation are obtained through the least squares method. The fractal dimension equation of water saturation satisfies the following:

[0076] Sw =c1·ΔD v 2 +c2·ΔD v +c3

[0077] Among them, S w ΔD represents the water saturation of the target rock sample. v The water saturation is S w The relative values ​​of the fractal dimension of the rock sample; c1 is the coefficient of the fractal dimension equation for the first water saturation, c2 is the coefficient of the fractal dimension equation for the second water saturation, and c3 is the coefficient of the fractal dimension equation for the third water saturation.

[0078] In one possible implementation, the second determining module is specifically used for:

[0079] Based on the fractal dimension value, the bound water saturation, and the equation relating the fractal dimension of saturated water to the bound water saturation, the coefficients of multiple objective equations are determined by the least squares method.

[0080] The equation relating the saturated water volume dimension to the bound water saturation degree satisfies:

[0081] D v，sw＝1 =d1·S wi +d2

[0082] Among them, S wi d1 represents the bound water saturation; d2 represents the coefficients of the first objective equation; and d2 represents the coefficients of the second objective equation.

[0083] Thirdly, this application provides an electronic device, including: a processor and a memory; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, causing the processor to perform the reservoir gas saturation prediction method as described in the first aspect or any possible implementation of the first aspect.

[0084] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the reservoir gas saturation prediction method as described in the first aspect or any possible implementation thereof.

[0085] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the reservoir gas saturation prediction method as described in the first aspect or any possible implementation thereof.

[0086] In this application, by obtaining the total porosity, bound water saturation, and nuclear magnetic resonance (NMR) T2 spectra of the target rock sample in the target reservoir under saturated water conditions, as well as the NMR T2 spectra of the target rock sample under partially saturated water conditions, the fractal dimension value, coefficients of multiple water saturation fractal dimension equations, and coefficients of multiple target equations are determined. Based on these fractal dimension values, bound water saturation, gas saturation equations, coefficients of multiple water saturation fractal dimension equations, and coefficients of multiple target equations, the gas saturation at the depth of the target rock sample in the target reservoir is calculated. Since NMR logging is less affected by the rock skeleton, this quantitative calculation of the gas saturation of the target rock sample based on its NMR T2 spectra can effectively improve the accuracy of gas saturation calculations. Attached Figure Description

[0087] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0088] Figure 1 A schematic diagram of a reservoir gas saturation prediction system architecture is provided for an embodiment of this application;

[0089] Figure 2 A flowchart illustrating a method for predicting reservoir gas saturation provided in this application embodiment;

[0090] Figure 3 A schematic diagram of the nuclear magnetic resonance T2 spectrum of a target rock sample under different water saturation conditions provided in an embodiment of this application;

[0091] Figure 4 A flowchart illustrating another method for predicting reservoir gas saturation provided in this application embodiment;

[0092] Figure 5 A schematic diagram of the integral logarithmic discrete curves of pore volume in the nuclear magnetic resonance T2 spectra of a target rock sample in saturated and partially saturated water states, provided in an embodiment of this application. Figure 1 ;

[0093] Figure 6 A schematic diagram of the integral logarithmic discrete curves of pore volume in the nuclear magnetic resonance T2 spectra of a target rock sample in saturated and partially saturated water states, provided in an embodiment of this application. Figure 2 ;

[0094] Figure 7 A schematic diagram of the fractal dimension equation curve of the water saturation of a target rock sample provided in an embodiment of this application;

[0095] Figure 8 A schematic diagram of the relationship between the saturated water volume dimension and bound water saturation of a target rock sample provided in an embodiment of this application;

[0096] Figure 9 A schematic diagram illustrating the prediction results of gas saturation in tight sandstone reservoirs using nuclear magnetic resonance logging, provided as an embodiment of this application.

[0097] Figure 10 A schematic diagram of a reservoir gas saturation prediction device provided in an embodiment of this application;

[0098] Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0099] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0100] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the embodiments of this application. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0101] In the embodiments of this application, terms such as "first" and "second" are used to distinguish identical or similar items with essentially the same function and purpose. For example, "first chip" and "second chip" are used only to distinguish different chips and do not limit their order of execution. Those skilled in the art will understand that terms such as "first" and "second" do not limit the quantity or execution order, and that "first" and "second" do not necessarily imply that they are different.

[0102] It should be noted that, in the embodiments of this application, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0103] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, a--c, bc, or abc, where a, b, and c can be single or multiple.

[0104] It should be understood that although the steps in the flowcharts of this application's embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the figures may include at least one sub-step or at least one stage. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0105] Tight sandstone gas reservoirs refer to low-permeability natural gas reservoirs hosted in sandstone with low porosity and low permeability, belonging to unconventional oil and gas reservoirs. Tight sandstone gas reservoirs are extremely abundant; therefore, accurately calculating their reserves is of great significance. Reservoir gas saturation refers to the percentage of natural gas volume in the reservoir's interconnected pore volume under its original state. Estimating reservoir gas saturation is a key aspect in calculating the resource size of tight sandstone gas reservoirs.

[0106] In some implementations, gas saturation in sandstone reservoirs is calculated using Archie's formula and a modified function model based on Archie's formula. For example, gas saturation is calculated from resistivity logging data based on the relationship between sandstone resistivity, porosity, and water saturation. However, the lithology and pore structure of tight sandstone reservoirs are typically complex and diverse, increasing the ambiguity of resistivity logging interpretation and resulting in lower accuracy of gas saturation calculations from rock resistivity logging data.

[0107] In other implementations, reservoir gas saturation is calculated based on array acoustic logging data, taking into account the acoustic characteristics of the rock. However, tight sandstone has high bound water saturation and low gas saturation, which, under the influence of factors such as lithology and clay content, further reduces the gas-bearing response of the rock acoustics, thus limiting the application of rock acoustic characteristics in evaluating gas reservoir gas saturation.

[0108] In other implementations, nuclear magnetic resonance (NMR) rock sample experimental data is used to evaluate the gas saturation of gas reservoirs by assessing adsorbed and free gas. However, this method is mainly used to evaluate the gas saturation of shale gas reservoirs and cannot be applied to NMR logging data.

[0109] In other implementations, a standard for calculating gas saturation using two-dimensional nuclear magnetic resonance (NMR) is established based on the longitudinal and transverse two-dimensional relaxation characteristics of the rock, thereby calculating the reservoir gas saturation. However, the high cost of two-dimensional NMR logging acquisition limits the applicability of this method.

[0110] To address the aforementioned issues, this application provides a method for predicting reservoir gas saturation. This method utilizes the bound water saturation, NMR T2 spectra of saturated water, and NMR T2 spectra of partially saturated water in rock samples from tight sandstone reservoirs to determine the fractal dimension, coefficients of multiple water saturation fractal dimension equations, and coefficients of multiple target equations. Then, it quantitatively calculates the gas saturation at the depth of the rock sample using the gas saturation equation. Since NMR logging is less affected by the rock framework, this method of quantitatively calculating the gas saturation of rock samples based on their NMR T2 spectra effectively improves the accuracy of gas saturation calculations. Furthermore, this method can be used to predict the gas saturation of actual tight sandstone reservoirs, laying the foundation for rock physics and reservoir logging evaluation research.

[0111] For example, Figure 1 A schematic diagram of a reservoir gas saturation prediction system architecture provided in an embodiment of this application is shown. Figure 1 As shown, the architecture includes at least one of a receiving device 101, a processor 102, and a display device 103.

[0112] It is understood that the architecture illustrated in the embodiments of this application does not constitute a specific limitation on the architecture of a reservoir gas saturation prediction system. In other feasible embodiments of this application, the architecture may include more or fewer components than illustrated, or combine some components, or split some components, or arrange different components, which can be determined according to the actual application scenario and is not limited here. Figure 1 The components shown can be implemented in hardware, software, or a combination of both.

[0113] In the specific implementation process, the receiving device 101 can be an input / output interface or a communication interface.

[0114] The processor 102 can acquire measurement data of the target rock sample in the target reservoir. The measurement data includes total porosity, bound water saturation, nuclear magnetic resonance T2 spectrum in saturated water state, and nuclear magnetic resonance T2 spectrum in partially saturated water state. Based on the measurement data, the processor determines the fractal dimension value of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part of the target rock sample. Based on the fractal dimension value, the processor determines the coefficients of multiple water saturation fractal dimension equations of the target rock sample. Based on the fractal dimension value and bound water saturation, the processor determines the coefficients of multiple target equations. Based on the fractal dimension value, bound water saturation, gas saturation equation, multiple water saturation fractal dimension equation coefficients, and multiple target equation coefficients, the processor calculates the gas saturation at the depth of the target rock sample in the target reservoir.

[0115] The display device 103 can be used to display the above results, etc.

[0116] The display device 103 may also be a touch screen, used to receive user commands while displaying the above content, so as to realize interaction with the user.

[0117] It should be understood that the aforementioned processor can be implemented by reading instructions from memory and executing those instructions, or it can be implemented through chip circuitry.

[0118] Furthermore, the network architecture and business scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0119] The technical solutions shown in this application will now be described in detail through specific embodiments. It should be noted that the following embodiments may exist independently or in combination with each other; identical or identical content will not be repeated in different embodiments.

[0120] For example, Figure 2 This diagram illustrates a flowchart of a reservoir gas saturation prediction method provided in an embodiment of this application. The execution entity of this embodiment can be... Figure 1 The processor 102 in the code can be specifically executed based on the actual application scenario. For example... Figure 2 As shown, the method may include:

[0121] S201: Obtain measurement data of the target rock sample in the target reservoir. The measurement data includes total porosity, bound water saturation, nuclear magnetic resonance T2 spectrum of saturated water state and nuclear magnetic resonance T2 spectrum of partially saturated water state. The partially saturated water state includes at least two states of the target rock sample, and the partially saturated water state includes the state corresponding to the bound water saturation of the target rock sample.

[0122] In this embodiment, the target reservoir can be a tight sandstone reservoir, or an unconventional gas reservoir such as shale, low-porosity, low-permeability sandstone, or volcanic rock. This embodiment uses a tight sandstone reservoir as an example for illustrative purposes. Tight sandstone is an unconventional sandstone, generally composed of dense clastic rocks, mainly including siltstone, fine sandstone, and some medium- to coarse sandstone. The target rock sample can be a representative rock sample from the target reservoir.

[0123] The total porosity of the target rock sample refers to the ratio of the sum of the volumes of all pore spaces in the target rock sample to the total volume of the target rock sample. The measurement of total porosity can be performed according to the procedures specified in the standard method for determining the porosity and permeability of rocks under overburden, and this application does not specifically limit this.

[0124] The bound water saturation of the target rock sample can be obtained through nuclear magnetic resonance (NMR) experiments. Specifically, the experimental results can be obtained according to the procedures specified in the laboratory measurement standards for nuclear magnetic resonance parameters of rock samples. This application does not impose specific limitations on this aspect.

[0125] In a possible implementation, the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated water state and the nuclear magnetic resonance T2 spectrum of the target rock sample in partially saturated water state are obtained through multiple centrifugation experiments and nuclear magnetic resonance experiments.

[0126] For example, at least two target rock samples are selected, and the pores of the target rock samples are filled with water. At this time, the water saturation S of the target rock samples is... w To obtain the T2 NMR spectrum of the target rock sample with a water saturation of 1, a nuclear magnetic resonance (NMR) experiment was performed on the target rock sample at a water saturation level of 1. Multiple centrifugation experiments were conducted on the target rock sample to obtain different water saturations. After each centrifugation experiment, the target rock sample was subjected to NMR again to obtain the T2 NMR spectrum of the target rock sample at different water saturation levels. When the water saturation of the target rock sample reaches the bound water saturation level S... wi At this point, the centrifugation experiment is stopped and a nuclear magnetic resonance (NMR) experiment is performed on the target rock sample to obtain the NMR T2 spectrum of the target rock sample under bound water conditions. The centrifugation and NMR experiments of the target rock sample are then concluded. After the above multiple centrifugation and NMR experiments, NMR T2 spectra of the target rock sample under at least three water saturation conditions are obtained. The three water saturation conditions may include: S... w =1,Swi w <1、S w =S wi .

[0127] Please refer to the T2 NMR spectra of the target rock sample obtained under different water saturation conditions after multiple centrifugation and NMR experiments. Figure 3 Exemplary Figure 3 This document illustrates schematic diagrams of the nuclear magnetic resonance (NMR) T2 spectra of a target rock sample under different water saturation conditions, as provided in an embodiment of this application. Figure 3 As shown in the figure, this figure illustrates the relationship between the transverse relaxation time T2 and the pore amplitude (also known as the pore component) S(T2) of the target rock sample under various water saturation conditions. The various water saturations of the target rock sample include: S w =100%, S w =46.61%, S w =28.11%, S w =18.32%, S w =16.72%.

[0128] S202: Determine the fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid portion of the target rock sample based on the measurement data.

[0129] The state of fluids in the pores of dense sandstone can be divided into movable fluids and bound fluids. Movable fluids refer to free fluids that can overcome capillary forces or viscous forces and participate in flow under certain external forces (i.e., the force exerted by the pore throat surface is relatively weak). Bound fluids generally exist in micropores and dead pores and are fluids that cannot be made to flow under external forces (i.e., the force exerted by the pore throat surface is relatively strong).

[0130] In a possible implementation, the pore volume integral discrete curves of the NMR T2 spectra of the target rock sample in saturated and partially saturated water states are determined based on the total porosity, the NMR T2 spectrum of the saturated water state, and the NMR T2 spectrum of the partially saturated water state. Then, the bound water saturation S of the target rock sample is used as the basis for further analysis. wi The logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the target rock sample is determined by the discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states. Then, based on the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states and the fractal dimension equation, the coefficients of the fractal dimension equation are determined. Finally, based on the coefficients of the fractal dimension equation, the fractal dimension value of the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states is determined.

[0131] ​S203: Determine the coefficients of multiple water saturation fractal dimension equations for the target rock sample based on the fractal dimension values; and determine the coefficients of multiple target equations based on the fractal dimension values ​​and bound water saturation.

[0132] In a possible implementation, multiple coefficients of the fractal dimension equation for the target rock sample's water saturation are determined based on the fractal dimension value and the fractal dimension equation for water saturation. Furthermore, multiple target equation coefficients are determined based on the fractal dimension value, bound water saturation, and the equation relating the fractal dimension of saturated water to bound water saturation.

[0133] S204: Calculate the gas saturation at the depth of the target rock sample in the target reservoir based on the fractal dimension value, bound water saturation, gas saturation equation, coefficients of multiple water saturation fractal dimension equations, and coefficients of multiple target equations.

[0134] In a possible implementation, the gas saturation equation is:

[0135] S g =1-[c1·(D v -d1·S wi +d2) 2 +c2·(D v -d1·S wi +d2)+c3]

[0136] Among them, S g D represents the gas saturation value at the depth where the target rock sample is located in the target reservoir; v S represents the fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid component; wi d1 represents the bound water saturation; d2 represents the coefficients of the first objective equation; c1 represents the coefficients of the fractal dimension equation for the first water saturation; c2 represents the coefficients of the fractal dimension equation for the second water saturation; and c3 represents the coefficients of the fractal dimension equation for the third water saturation.

[0137] In this embodiment, by acquiring the total porosity, bound water saturation, NMR T2 spectrum of the target rock sample in the target reservoir under saturated water conditions, and the NMR T2 spectrum of the target rock sample under partially saturated water conditions, the fractal dimension value, multiple water saturation fractal dimension equation coefficients, and multiple target equation coefficients are determined. Based on the fractal dimension value, bound water saturation, gas saturation equation, multiple water saturation fractal dimension equation coefficients, and multiple target equation coefficients, the gas saturation at the depth of the target rock sample in the target reservoir is calculated. Since NMR logging is less affected by the rock skeleton, this quantitative calculation of the gas saturation of the target rock sample based on its NMR T2 spectrum can effectively improve the accuracy of gas saturation calculation.

[0138] Based on the above embodiments, in order to more clearly describe the technical solution of this application, please refer to the exemplary embodiments. Figure 4 , Figure 4 This illustration shows a flowchart of another reservoir gas saturation prediction method provided in an embodiment of this application. The execution entity of this embodiment can be... Figure 1 The processor 102 in the document can be specifically executed based on the actual application scenario. This embodiment uses 19 rock samples of tight sandstone from the Shahejie Formation in the Nanpu Depression of the Bohai Bay Basin as examples for illustrative purposes. This example does not constitute a specific limitation on the embodiments of this application. Figure 4 As shown, the method may include:

[0139] S401: Obtain measurement data of target rock samples in the target reservoir. The measurement data includes total porosity, bound water saturation, nuclear magnetic resonance T2 spectrum of saturated water state and nuclear magnetic resonance T2 spectrum of partially saturated water state.

[0140] This step is similar to or the same as step S201 above, and will not be repeated here.

[0141] S402: Determine the pore volume integral discrete curves of the NMR T2 spectra of the target rock sample in saturated and partially saturated water states based on the total porosity, the NMR T2 spectra in saturated water state, and the NMR T2 spectra in partially saturated water state.

[0142] In a possible implementation, the discrete curves of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states satisfy the following:

[0143]

[0144] Among them, S v (t) represents the discrete curve of the pore volume integral of the T2 spectrum at time t; S T2 (t) represents the pore amplitude of the T2 spectrum at time t; T2_min is the minimum T2 time of the discrete curve of the pore volume integral of the T2 spectrum, in milliseconds (ms); φ t S represents the total porosity of the target rock sample. w The water saturation of the target rock sample.

[0145] Furthermore, the cutoff time is determined based on the pore volume integral discrete curve of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states and the bound water saturation.

[0146] For example, the linear interpolation method is used to determine when S v (t)=S wi The time T2 corresponding to the time is the cutoff time T2cut.

[0147] S403: Determine the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid portion based on the saturation of bound water and the discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states.

[0148] In a possible implementation, the pore volume integral logarithmic discrete curves of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states are obtained based on the discrete curves of the nuclear magnetic resonance T2 spectrum pore volume integral of the target rock sample in saturated and partially saturated water states.

[0149] For example, the integral logarithmic discrete curves of the pore volume of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states satisfy the following:

[0150]

[0151] Furthermore, based on the cutoff time and the discrete curves of the pore volume integral of the nuclear magnetic resonance T2 spectra of the target rock sample in saturated and partially saturated water states, piecewise curves of the discrete curves of the pore volume integral of the nuclear magnetic resonance T2 spectra of the target rock sample in saturated and partially saturated water states are determined; wherein, the piecewise curves satisfy:

[0152]

[0153] Where T2_max is the maximum T2 time of the T2 spectrum discrete curve, and its unit is ms; T2cut is the cutoff time, and its unit is ms.

[0154] For example, Figure 5 This illustration shows the integral logarithmic discrete curves of pore volume in the T2 NMR spectra of a target rock sample in saturated and partially saturated water states, as provided in an embodiment of this application. Figure 1 .like Figure 5 As shown, with the cutoff time T2cut as the boundary, the NMR T2 spectrum pore volume integral logarithmic discrete curves of the target rock sample in saturated water and partially saturated water states are divided into the NMR T2 spectrum pore volume integral logarithmic discrete curves of the movable fluid part and the NMR T2 spectrum pore volume integral logarithmic discrete curves of the bound fluid part.

[0155] The discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part is the piecewise curve corresponding to t∈[T2cut,T2_max].

[0156] The integral logarithmic discrete curve of the pore volume of the movable fluid portion of the target rock sample using nuclear magnetic resonance T2 spectrum can be referenced. Figure 6 For example, Figure 6 This illustration shows the integral logarithmic discrete curves of pore volume in the T2 NMR spectra of a target rock sample in saturated and partially saturated water states, as provided in an embodiment of this application. Figure 2 . Figure 6 for Figure 5 The curved segment within the dashed box, such as Figure 6 As shown, the nuclear magnetic resonance T2 spectrum pore volume integral logarithmic discrete curves of the movable fluid portion of the target rock sample under different water saturation conditions are fitted to obtain the corresponding linear equations, such as the water saturation S. w When the water saturation is 100%, the linear equation is y = 0.52254x - 1.39726. The goodness of fit (also known as the correlation coefficient) R between this linear equation and the discrete curve of the nuclear magnetic resonance T2 spectrum pore volume integral logarithm of the movable fluid part is 0.961; the water saturation S w When the water saturation is 46.61%, the linear equation is y = 0.25679x - 0.63246. The goodness of fit R between this linear equation and the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part is 0.8451; the water saturation S w When the concentration is 28.11%, the linear equation is y = 0.17273x - 0.4211. The goodness of fit R between this linear equation and the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid component is 0.83734; the water saturation S w When the concentration is 18.32%, the linear equation is y = 0.039x - 0.10514. The goodness of fit R between this linear equation and the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part is 0.58372; the water saturation S w When the content is 16.72%, the linear equation is y = 0.02356x - 0.10212. The goodness of fit R between this linear equation and the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part is 0.64787.

[0157] S404: Based on the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid part and the fractal dimension function equation, the fractal dimension value of the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid part is obtained by the least squares method.

[0158] The fractal dimension function equation satisfies:

[0159] Log 10 (S v (t))=A·Log 10 (t)+B, t∈[T2cut, T2_max]

[0160] Where A is the coefficient of the first fractal dimension equation, and B is the coefficient of the second fractal dimension equation;

[0161] The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part satisfies the formula:

[0162] D v =3-A

[0163] Among them, D v The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid component is given.

[0164] It is understandable that different water saturation levels in the target rock sample correspond to different fractal dimension values. For an example, please refer to [link to example]. Figure 6 When the water saturation S w When the value is 100%, the linear equation is y = 0.52254x⁻¹ - 39726. At this point, the coefficient A of the first fractal dimension equation is 0.52254. Therefore, the fractal dimension value D is... v It is 3-A, which is 2.47746; when the water saturation S w When the fractal dimension is 46.61%, the linear equation is y = 0.25679x - 0.63246. At this point, the coefficient A of the first fractal dimension equation is 0.25679. Therefore, the fractal dimension value D is... v It is 3-A, which is 2.74321.

[0165] S405: Determine the relative value of the fractal dimension based on the fractal dimension value.

[0166] The relative value of the fractal dimension satisfies the formula:

[0167] ΔD v =D v -D v，sw＝1

[0168] Where, ΔD v D is the relative value of the fractal dimension. v，sw＝1 The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid portion of the target rock sample in saturated water state.

[0169] S406: Based on the relative value of fractal dimension and the fractal dimension equation of water saturation, the coefficients of multiple fractal dimension equations of water saturation are obtained by the least squares method.

[0170] The fractal dimension equation for water saturation satisfies:

[0171] Sw=c1·ΔD v 2 +c2·ΔD v +c3

[0172] Among them, S w ΔD represents the water saturation of the target rock sample. v The water saturation is S wThe relative values ​​of the fractal dimension of the rock sample; c1 is the coefficient of the fractal dimension equation for the first water saturation, c2 is the coefficient of the fractal dimension equation for the second water saturation, and c3 is the coefficient of the fractal dimension equation for the third water saturation.

[0173] Please refer to the fractal dimension equation for water saturation. Figure 7 For example, Figure 7 This illustration shows a schematic diagram of the fractal dimension equation curve of the water saturation of a target rock sample provided in an embodiment of this application. Figure 7 As shown, the quadratic equation fitted to the fractal dimension equation of water saturation using the least squares method is y = 0.97679 - 2.98267*x - 2.75926*x 2 The goodness of fit R is 0.9778.

[0174] S407: Based on the fractal dimension value, bound water saturation, and the equation relating the fractal dimension of saturated water to bound water saturation, the coefficients of multiple objective equations are determined using the least squares method.

[0175] The equation relating the saturated water volume dimension to the bound water saturation degree satisfies:

[0176] D v，sw＝1 =d1·S wi +d2

[0177] Among them, D v，sw＝1 The fractal dimension of the nuclear magnetic resonance T2 spectrum of the movable fluid portion of the target rock sample under saturated water conditions; S wi d1 represents the bound water saturation of the target rock sample; d2 represents the coefficient of the first objective equation; and d2 represents the coefficient of the second objective equation.

[0178] Please refer to the equation relating the saturated water volumetric dimension to the bound water saturation. Figure 8 For example, Figure 8 This paper illustrates a schematic diagram of the relationship between the saturated water volume dimension and bound water saturation of a target rock sample provided in an embodiment of this application. Figure 8 As shown, the linear equation fitted by the least squares method to the equation relating the water volume dimension and the bound water saturation is y = -0.00781x + 3.61315, with a goodness of fit R of 0.92865.

[0179] S408: Calculate the gas saturation at the depth of the target rock sample in the target reservoir based on the fractal dimension value, bound water saturation, gas saturation equation, coefficients of multiple water saturation fractal dimension equations, and coefficients of multiple target equations.

[0180] This step is similar to or the same as step S204 above, and will not be repeated here.

[0181] In this embodiment, by acquiring the total porosity, bound water saturation, and NMR T2 spectra of the target rock sample in the target reservoir under saturated water conditions, as well as the NMR T2 spectra of the target rock sample under partially saturated water conditions, the fractal dimension value, multiple water saturation fractal dimension equation coefficients, and multiple target equation coefficients are determined. Based on these fractal dimension values, bound water saturation, gas saturation equations, multiple water saturation fractal dimension equation coefficients, and multiple target equation coefficients, the gas saturation at the depth of the target rock sample in the target reservoir is calculated. Since NMR logging is less affected by the rock skeleton, this quantitative calculation of the gas saturation of the target rock sample based on its NMR T2 spectrum can effectively improve the accuracy of gas saturation calculation, thus promoting comprehensive reservoir evaluation and rock physics research.

[0182] Based on the above embodiments, in a possible implementation, the nuclear magnetic resonance T2 spectrum of the target reservoir at different depths and the bound water saturation curve are processed to obtain the fractal dimension value, bound water saturation, multiple water saturation fractal dimension equation coefficients and multiple target equation coefficients, and the gas saturation value at each depth point of the target reservoir is calculated according to the gas saturation equation.

[0183] In a possible implementation, the steps of processing the nuclear magnetic resonance T2 spectrum at each depth of the target reservoir to obtain the fractal dimension value, the coefficients of multiple water saturation fractal dimension equations, and the coefficients of multiple target equations can refer to the above steps S402 to S407, and will not be repeated here.

[0184] In a possible implementation, nuclear magnetic resonance logging data is acquired and processed from the target reservoir to obtain nuclear magnetic resonance logging T2 spectrum curve data and bound water saturation curves at the target reservoir depth.

[0185] Among them, the nuclear magnetic resonance logging T2 spectrum curve data includes the nuclear magnetic resonance logging T2 spectrum of the target reservoir at each depth, and the bound water saturation curve includes the bound water saturation of the target reservoir at each depth.

[0186] For example, nuclear magnetic resonance (NMR) logging data is acquired from the target reservoir using the procedures specified in the calibration specifications of the NMR logging tool and the technical specifications for NMR logging operations. Then, the NMR logging data is processed using the procedures specified in the specifications for processing and interpretation of NMR logging data, thereby obtaining the T2 spectrum curve data and bound water saturation curve of the NMR logging data at the target reservoir depth range.

[0187] In this embodiment of the application, the gas saturation of the target reservoir at each depth is quantitatively calculated using nuclear magnetic resonance logging data. Since nuclear magnetic resonance logging is less affected by the rock skeleton, it can effectively improve the calculation accuracy of the gas saturation of the target reservoir, especially the tight sandstone reservoir.

[0188] For example, Figure 9 This diagram illustrates the prediction results of gas saturation in tight sandstone reservoirs using nuclear magnetic resonance (NMR) logging, as provided in an embodiment of this application. The diagram includes NMR logging results corresponding to reservoir depths of 4385 meters to 4425 meters, and uses a reservoir depth of 4400 meters to 4410 meters as an example for illustrative purposes. Figure 9 As shown, the first channel is the natural gamma ray (GR) logging curve, the second channel is the depth channel, the third channel is the geological logging channel, the fourth channel is the resistivity channel, the fifth channel is the three-porosity curve channel, the sixth channel is the nuclear magnetic resonance logging T2 spectrum curve data, the seventh channel is the permeability (perm) curve, the eighth channel is the fractal dimension numerical channel, the ninth channel is the bound water saturation curve, the tenth channel is the gas saturation curve calculated based on resistivity, and the eleventh channel is the gas saturation curve calculated based on nuclear magnetic resonance logging T2 spectrum curve data and bound water saturation curve. The geological logging data may include siltstone, mudstone, and fine sandstone; the resistivity channel may include shallow lateral resistivity curves and deep lateral resistivity curves; the three porosity curve channels may include density logging curves, neutron logging curves, and sonic logging curves; the fractal dimension numerical channel may include the fractal dimension numerical Dv curve of the nuclear magnetic resonance T2 spectrum pore volume integral logarithmic discrete curve of the movable fluid portion of the reservoir, the fractal dimension numerical Dvb curve of the nuclear magnetic resonance T2 spectrum pore volume integral logarithmic discrete curve of the bound fluid portion of the reservoir, and the fractal dimension numerical Dv,sw=1 curve of the nuclear magnetic resonance T2 spectrum pore volume integral logarithmic discrete curve of the movable fluid portion of the reservoir under saturated water conditions; the discrete points in channels 9 to 11 are experimentally measured and can be understood as the actual gas saturation values ​​at the corresponding depth points.

[0189] like Figure 9 As shown, the gas saturation calculated in the embodiments of this application is compared with the gas saturation value calculated from the experimental bound water saturation (1-S). wi The error is 13.24% compared to the result calculated using Archie's formula, which has an error of 34.22%. Therefore, the accuracy of the gas saturation result calculated in this embodiment is significantly higher than that calculated using Archie's formula based on resistivity logging.

[0190] In this embodiment, the gas saturation of the target reservoir at each depth is quantitatively calculated by acquiring and processing NMR logging T2 spectrum curves and bound water saturation curves. This overcomes the problem of low calculation accuracy of the existing Archie formula in non-Archie phenomena and can be applied to tight sandstone gas layers, low-porosity and low-permeability sandstone gas layers, and even shale gas layers, demonstrating strong scalability. Furthermore, compared to the acquisition of two-dimensional NMR logging data, the acquisition cost of NMR logging data is lower, thus helping to reduce the cost of reservoir gas saturation prediction.

[0191] Figure 10 A schematic diagram of a reservoir gas saturation prediction device provided in this application embodiment is shown below. Figure 10 As shown, the reservoir gas saturation prediction device 100 includes: an acquisition module 1001, a first determination module 1002, a second determination module 1003, and a calculation module 1004. The reservoir gas saturation prediction device 100 can be the processor 102 itself, or a chip or integrated circuit that implements the functions of the processor 102. It should be noted that the division of the acquisition module 1001, the first determination module 1002, the second determination module 1003, and the calculation module 1004 is only a logical functional division; physically, they can be integrated or independent.

[0192] The acquisition module 1001 is used to acquire measurement data of the target rock sample in the target reservoir. The measurement data includes total porosity, bound water saturation, nuclear magnetic resonance T2 spectrum of saturated water state and nuclear magnetic resonance T2 spectrum of partially saturated water state. The partially saturated water state includes at least two states of the target rock sample, and the partially saturated water state includes the state corresponding to the bound water saturation of the target rock sample.

[0193] The first determining module 1002 is used to determine the fractal dimension value of the nuclear magnetic resonance T2 spectrum pore volume integral logarithmic discrete curve of the movable fluid part of the target rock sample based on the measurement data.

[0194] The second determining module 1003 is used to determine the coefficients of multiple water saturation fractal dimension equations of the target rock sample based on the fractal dimension values; and to determine multiple target equation coefficients based on the fractal dimension values ​​and the bound water saturation.

[0195] The calculation module 1004 is used to calculate the gas saturation at the depth of the target rock sample in the target reservoir based on the fractal dimension value, bound water saturation, gas saturation equation, coefficients of multiple water saturation fractal dimension equations, and coefficients of multiple target equations.

[0196] In one possible implementation, the gas saturation equation is:

[0197] S g=1-[c1·(D v -d1·S wi +d2) 2 +c2·(D v -d1·S wi +d2)+c3]

[0198] Among them, S g D represents the gas saturation at the depth where the target rock sample is located in the target reservoir. v S represents the fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid component; wi d1 represents the bound water saturation; d2 represents the coefficients of the first objective equation; c1 represents the coefficients of the fractal dimension equation for the first water saturation; c2 represents the coefficients of the fractal dimension equation for the second water saturation; and c3 represents the coefficients of the fractal dimension equation for the third water saturation.

[0199] In one possible implementation, the first determining module 1002 is specifically used for:

[0200] The pore volume integral discrete curves of the NMR T2 spectra of the target rock sample in saturated and partially saturated water states were determined based on the total porosity, the NMR T2 spectra in saturated water state, and the NMR T2 spectra in partially saturated water state.

[0201] The logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid component is determined based on the pore volume integral discrete curve of the nuclear magnetic resonance T2 spectrum of the target rock sample in the states of bound water saturation and saturated and partially saturated water.

[0202] Based on the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid part and the fractal dimension function equation, the fractal dimension value of the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid part is obtained by the least squares method.

[0203] The fractal dimension function equation satisfies:

[0204] Log 10 (S v (t))=A·Log 10 (t)+B, t∈[T2cut, T2_max]

[0205] Among them, S v (t) represents the numerical value of the T2 spectrum pore volume integral discrete curve at time t; t is the T2 relaxation time; T2_max is the maximum T2 time of the T2 spectrum discrete curve; T2cut is the cutoff time; A is the coefficient of the first fractal dimension equation, and B is the coefficient of the second fractal dimension equation.

[0206] The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part satisfies the formula:

[0207] D v =3-A

[0208] Among them, D v The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid component is given.

[0209] In one possible implementation, the discrete curves of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states satisfy the following:

[0210]

[0211] Among them, S v (t) represents the discrete curve of the pore volume integral of the T2 spectrum at time t; S T2 (t) represents the pore amplitude of the T2 spectrum at time t; T2_min represents the minimum T2 time of the discrete curve of the pore volume integral of the T2 spectrum; φt represents the total porosity; S w The water saturation of the target rock sample.

[0212] In one possible implementation, the first determining module 1002 is specifically used for:

[0213] The cutoff time is determined based on the bound water saturation and the pore volume integral discrete curve of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states.

[0214] Based on the deadline and the discrete curves of the pore volume integral of the NMR T2 spectrum of the target rock sample in both saturated and partially saturated water states, the piecewise curves of the pore volume integral logarithmic discrete curves of the NMR T2 spectrum of the target rock sample in both saturated and partially saturated water states are determined; wherein, the piecewise curves satisfy:

[0215]

[0216] Among them, S v (t) represents the value of the T2 spectrum pore volume integral discrete curve at time t; T2_min is the minimum T2 time of the T2 spectrum discrete curve; T2_max is the maximum T2 time of the T2 spectrum discrete curve; T2cut is the cutoff time.

[0217] The discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid part is the piecewise curve corresponding to t∈[T2cut,T2_max].

[0218] In one possible implementation, the second determining module 1003 is specifically used for

[0219] The relative value of the fractal dimension is determined based on the numerical value of the fractal dimension, where the relative value of the fractal dimension satisfies the formula:

[0220] ΔD v =D v -D v，sw＝1

[0221] Where, ΔD v D is the relative value of the fractal dimension. v，sw＝1 The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid portion of the target rock sample in saturated water state.

[0222] Based on the relative value of the fractal dimension and the fractal dimension equation of water saturation, multiple coefficients of the fractal dimension equation of water saturation are obtained through the least squares method. The fractal dimension equation of water saturation satisfies the following:

[0223] S w =c1·ΔD v 2 +c2·ΔD v +c3

[0224] Among them, S w ΔD represents the water saturation of the target rock sample. v The water saturation is S w The relative values ​​of the fractal dimension of the rock sample; c1 is the coefficient of the fractal dimension equation for the first water saturation, c2 is the coefficient of the fractal dimension equation for the second water saturation, and c3 is the coefficient of the fractal dimension equation for the third water saturation.

[0225] In one possible implementation, the second determining module 1003 is specifically used for:

[0226] Based on the fractal dimension value, the bound water saturation, and the equation relating the fractal dimension of saturated water to the bound water saturation, the coefficients of multiple objective equations are determined by the least squares method.

[0227] The equation relating the saturated water volume dimension to the bound water saturation degree satisfies:

[0228] D v，sw＝1 =d1·S wi +d2

[0229] Among them, S wi d1 represents the bound water saturation; d2 represents the coefficients of the first objective equation; and d2 represents the coefficients of the second objective equation.

[0230] The reservoir gas saturation prediction device 100 provided in this application embodiment can execute the technical solution shown in the above-described reservoir gas saturation prediction method embodiment. Its implementation principle and beneficial effects are similar, and will not be described again here.

[0231] Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Please refer to... Figure 11 The electronic device 110 includes a memory 1101, a processor 1102, a communication component 1103, and a bus 1104. The memory 1101, the processor 1102, and the communication component 1103 are interconnected via the bus 1104.

[0232] Memory 1101 stores computer-executed instructions;

[0233] The processor 1102 executes the computer execution instructions stored in the memory 1101, causing the processor 1102 to execute the above-mentioned reservoir gas saturation prediction method.

[0234] The communication component 1103 can be applied to, but is not limited to, transceiver devices such as transceivers, to enable communication between the electronic device 110 and other devices or communication networks.

[0235] Bus 1104 may include a pathway for transmitting information between various components of electronic device 110 (e.g., memory 1101, processor 1102, communication component 1103).

[0236] Figure 11 The electronic device shown in the embodiment can execute the technical solution shown in the above embodiment of the reservoir gas saturation prediction method. Its implementation principle and beneficial effects are similar, and will not be described again here.

[0237] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the above-described reservoir gas saturation prediction method.

[0238] This application also provides a computer program product, including a computer program that, when executed by a processor, can implement the above-described method for predicting reservoir gas saturation.

[0239] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the appended claims.

[0240] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for predicting reservoir gas saturation, characterized in that, include: Acquire measurement data of target rock samples in the target reservoir. The measurement data includes total porosity, bound water saturation, nuclear magnetic resonance T2 spectrum of saturated water state, and nuclear magnetic resonance T2 spectrum of partially saturated water state. The partially saturated water state includes at least two states of the target rock sample, and the partially saturated water state includes the state corresponding to the bound water saturation of the target rock sample. The fractal dimension of the integral logarithmic discrete curve of the pore volume of the movable fluid portion of the target rock sample is determined based on the measurement data. Based on the fractal dimension value, determine the coefficients of multiple water saturation fractal dimension equations for the target rock sample; and based on the fractal dimension value and the bound water saturation, determine the coefficients of multiple target equations. The gas saturation at the depth of the target rock sample in the target reservoir is calculated based on the fractal dimension value, the bound water saturation, the gas saturation equation, the coefficients of the multiple water saturation fractal dimension equations, and the coefficients of the multiple target equations. The step of determining the fractal dimension of the integral logarithmic discrete curve of the pore volume of the movable fluid portion of the target rock sample based on the measurement data includes: The pore volume integral discrete curves of the NMR T2 spectra of the target rock sample in saturated and partially saturated water states are determined based on the total porosity, the NMR T2 spectrum in the saturated water state, and the NMR T2 spectrum in the partially saturated water state. The nuclear magnetic resonance T2 spectrum pore volume integral logarithmic discrete curve of the movable fluid portion is determined based on the bound water saturation and the nuclear magnetic resonance T2 spectrum pore volume integral discrete curve of the target rock sample in saturated and partially saturated water states. Based on the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid part and the fractal dimension function equation, the fractal dimension value of the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid part is obtained by the least squares method. The fractal dimension function equation satisfies: in, The value of the T2 spectrum pore volume integral discrete curve at time t is the T2 time; t is the T2 relaxation time. The maximum T2 time is the T2 time of the T2 spectrum discrete curve; A represents the deadline; A is the coefficient of the first fractal dimension equation, and B is the coefficient of the second fractal dimension equation. The fractal dimension of the discrete curve of the nuclear magnetic resonance T2 spectrum pore volume integral logarithm of the movable fluid portion satisfies the formula: in, The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid component is given.

2. The method according to claim 1, characterized in that, The gas saturation equation is: in, The gas saturation at the depth where the target rock sample is located in the target reservoir; The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid component; The bound water saturation; The coefficients of the first objective equation are... The coefficients of the second objective equation; The coefficients of the fractal dimension equation for the first water saturation level are... The coefficients of the fractal dimension equation for the second water saturation level are... represents the coefficients of the fractal dimension equation for the third water saturation level.

3. The method according to claim 1, characterized in that, The NMR T2 spectral pore volume integral discrete curves of the target rock sample in saturated and partially saturated water states satisfy the following: in, The numerical values ​​of the T2 spectrum pore volume integral discrete curve at time t are given. The pore amplitude of the T2 spectrum at time t is the T2 time. The minimum T2 time is the discrete curve of the pore volume integral of the T2 spectrum; The total porosity; The water saturation of the target rock sample is given.

4. The method according to claim 3, characterized in that, The determination of the nuclear magnetic resonance T2 spectrum pore volume integral logarithmic discrete curve of the movable fluid portion based on the bound water saturation and the saturated and partially saturated water states of the target rock sample includes: The cutoff time is determined based on the bound water saturation and the nuclear magnetic resonance T2 spectrum pore volume integral discrete curve of the target rock sample in saturated and partially saturated water states. Based on the cutoff time and the discrete curves of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states, a piecewise curve of the discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the target rock sample in saturated and partially saturated water states is determined; wherein, the piecewise curve satisfies: in, The numerical values ​​of the T2 spectrum pore volume integral discrete curve at time t are given. The minimum T2 time for the T2 spectrum discrete curve; T2 is the maximum T2 time of the T2 spectrum discrete curve; T2cut is the cutoff time. The nuclear magnetic resonance T2 spectrum pore volume integral logarithmic discrete curve of the movable fluid part is as follows: The corresponding piecewise curve.

5. The method according to claim 4, characterized in that, The determination of multiple water saturation fractal dimension equation coefficients for the target rock sample based on the fractal dimension value includes: The relative value of the fractal dimension is determined based on the numerical value of the fractal dimension, wherein the relative value of the fractal dimension satisfies the formula: in, The relative value of the fractal dimension; The fractal dimension of the integral logarithmic discrete curve of the pore volume of the nuclear magnetic resonance T2 spectrum of the movable fluid portion of the target rock sample in a saturated water state is given. Based on the relative values ​​of the fractal dimensions and the fractal dimension equation for water saturation, the coefficients of the multiple fractal dimension equations for water saturation are obtained using the least squares method. The fractal dimension equations for water saturation satisfy the following: in, The water saturation of the target rock sample; The water saturation level is The relative value of the fractal dimension of the rock sample; The coefficients of the fractal dimension equation for the first water saturation level are... The coefficients of the fractal dimension equation for the second water saturation level are... represents the coefficients of the fractal dimension equation for the third water saturation level.

6. The method according to any one of claims 1-5, characterized in that, The determination of multiple objective equation coefficients based on the fractal dimension value and the bound water saturation includes: Based on the fractal dimension value, the bound water saturation, and the equation relating the fractal dimension of saturated water to the bound water saturation, the coefficients of the multiple objective equations are determined using the least squares method. The equation relating the saturated water volume dimension to the bound water saturation degree satisfies: in, The bound water saturation; The coefficients of the first objective equation are... These are the coefficients of the second objective equation.

7. A reservoir gas saturation prediction device, characterized in that, It includes an acquisition module, a first determination module, a second determination module, and a calculation module, wherein, The acquisition module is used to acquire measurement data of target rock samples in the target reservoir. The measurement data includes total porosity, bound water saturation, nuclear magnetic resonance T2 spectrum of saturated water state, and nuclear magnetic resonance T2 spectrum of partially saturated water state. The partially saturated water state includes at least two states of the target rock sample, and the partially saturated water state includes the state corresponding to the bound water saturation of the target rock sample. The first determining module is used to determine the fractal dimension of the integral logarithmic discrete curve of the pore volume of the nuclear magnetic resonance T2 spectrum of the movable fluid portion of the target rock sample based on the measurement data. The second determining module is used to determine multiple water saturation fractal dimension equation coefficients of the target rock sample based on the fractal dimension value; and to determine multiple target equation coefficients based on the fractal dimension value and the bound water saturation. The calculation module is used to calculate the gas saturation at the depth of the target rock sample in the target reservoir based on the fractal dimension value, the bound water saturation, the coefficients of the multiple water saturation fractal dimension equations, the coefficients of the multiple target equations, and the gas saturation equation. The first determining module is specifically used for: The pore volume integral discrete curves of the NMR T2 spectra of the target rock sample in saturated and partially saturated water states are determined based on the total porosity, the NMR T2 spectrum in the saturated water state, and the NMR T2 spectrum in the partially saturated water state. The nuclear magnetic resonance T2 spectrum pore volume integral logarithmic discrete curve of the movable fluid portion is determined based on the bound water saturation and the nuclear magnetic resonance T2 spectrum pore volume integral discrete curve of the target rock sample in saturated and partially saturated water states. Based on the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid part and the fractal dimension function equation, the fractal dimension value of the logarithmic discrete curve of the pore volume integral of the nuclear magnetic resonance T2 spectrum of the movable fluid part is obtained by the least squares method. The fractal dimension function equation satisfies: in, The value of the T2 spectrum pore volume integral discrete curve at time t is the T2 time; t is the T2 relaxation time. The maximum T2 time is the T2 time of the T2 spectrum discrete curve; A represents the deadline; A is the coefficient of the first fractal dimension equation, and B is the coefficient of the second fractal dimension equation. The fractal dimension of the discrete curve of the nuclear magnetic resonance T2 spectrum pore volume integral logarithm of the movable fluid portion satisfies the formula: in, The fractal dimension of the discrete curve of the pore volume integral logarithm of the nuclear magnetic resonance T2 spectrum of the movable fluid component is given.

8. An electronic device, characterized in that, include: Processor, memory; The memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that, when executed by a processor, are used to implement the method as described in any one of claims 1-6.

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