Heating well spacing evaluation method and system for in-situ fluid heating oil shale

Abstract

The invention discloses a heating well spacing evaluation method and system for in-situ fluid heating of oil shale, and the method comprises the steps: measuring basic parameters of a rock mass according to an oil shale sample of an oil shale in-situ region to be evaluated; performing a pyrolysis experiment on the oil shale sample to obtain the composition of each simulated product and the components of each simulated product changing along with the temperature, and fitting a pre-constructed kerogen pyrolysis-based multi-step total reaction model on the basis of the composition and the components, so as to obtain fitted model coefficients and reaction kinetic parameters; setting well pattern modes based on different well spacing for the mining heating area; predicting a formation temperature field formed on the basis of a heating condition of high-temperature fluid injection in the current in-situ formation, and predicting yield change curves under different well pattern modes on the basis of the formation temperature field in combination with the solved model coefficients and reaction kinetic parameters and the different well pattern modes; and establishing a target index calculation model for evaluating the quality of the well pattern modes, and obtaining corresponding target indexes according to the yield change curves in different well pattern modes, thereby optimizing the optimal well spacing.

Description

Technical Field

[0001] The present invention relates to the technical field of in-situ mining of oil shale, and in particular to a method and system for evaluating the spacing of heating wells used for in-situ fluid heating of oil shale. Background Art

[0002] In-situ heating of oil shale and thermal upgrading of low-maturity shale oil are considered to be production technologies that can effectively utilize shale oil. Thermal upgrading is expected to be a breakthrough technology for effectively utilizing low-maturity shale oil. By heating the formation, viscous, heavy liquid hydrocarbons are converted into light oil, upgrading the shale oil and improving its fluidity. This also converts solid organic matter into oil and gas. Using high-temperature fluids to heat organic-rich shale underground is a major heating method, alongside Shell's ICP technology. Due to its high heating efficiency and controllable energy input per unit time, it is a key area of ​​practical exploration.

[0003] Fluid heating of underground rock formations requires determining the optimal heating well spacing. The production well spacing is crucial to production performance, directly impacting the production plan, production cycle, and input-output ratio. In recent years, pilot trials of high-temperature fluid heating of underground oil shale have been conducted in China, employing a two-injection-one-production and / or four-injection-one-production heating and production method. However, in actual production, sufficient field data is not available to determine the optimal well spacing.

[0004] Therefore, the prior art needs to provide a solution for evaluating the distance between heating wells (for example, the distance between recovery wells) in a scenario of heating underground oil shale. Summary of the Invention

[0005] The purpose of the present invention is to provide a method that can solve the problem of insufficient basis for determining well spacing in in-situ heating oil shale heating and mining schemes.

[0006] In order to solve the above technical problems, an embodiment of the present invention provides a method for evaluating the heating well spacing for in-situ fluid heating of oil shale, comprising: obtaining oil shale samples from the oil shale area to be evaluated and determining basic rock parameters; performing pyrolysis experiments on the oil shale samples to obtain the composition of each pseudo-product and the components of each pseudo-product that change with temperature, based on which, fitting a pre-constructed multi-step total reaction model based on kerogen pyrolysis to obtain the fitted model coefficients and reaction kinetic parameters; setting a well network pattern based on different well spacings for the mining heating area; predicting the formation temperature field formed by the heating conditions based on high-temperature fluid injection in the current formation according to the basic rock parameters, based on which, combining the model coefficients and reaction kinetic parameters, as well as different well network patterns, predicting the production change curves under different well network patterns; establishing a target indicator calculation model for evaluating the advantages and disadvantages of the well network pattern, and obtaining corresponding target indicators from the production change curves under the different well network patterns, thereby selecting the optimal well spacing.

[0007] Preferably, the step of conducting a pyrolysis experiment on the oil shale sample to obtain the composition of each pseudo-product and the component changes of each pseudo-product with temperature includes: obtaining initial data on the composition changes of the main products with temperature based on the pyrolysis experiment carried out; and merging the components with similar properties and the same carbon number in the initial data according to the pseudo-component division results in the multi-step overall reaction model to form multiple pseudo-products and data on the changes of each pseudo-product with temperature.

[0008] Preferably, in performing a pyrolysis experiment on the oil shale sample to obtain the composition of each pseudo-product and the temperature-dependent component of each pseudo-product, based on which, fitting a pre-constructed multi-step overall reaction model based on kerogen pyrolysis to obtain the fitted model coefficients and reaction kinetic parameters comprises: conducting heating pyrolysis experiments at a preset heating rate and under different pressure conditions, thereby recording the composition of each pseudo-product and the temperature-dependent component of each pseudo-product; and establishing the multi-step overall reaction model based on kerogen pyrolysis, wherein the multi-step overall reaction model is:

[0009]

[0010]

[0011]

[0012]

[0013]

[0014]

[0015] Where m represents the total number of pseudo-products, X1, X2…Xi …X m represents the pseudo-products of the 1st, 2nd…i…mth reactions, k1, k2…k i …k m Represents the 1st, 2nd…i…mth reaction formula, Representing a model coefficient matrix; establishing an error function between the experimental measurement value and the theoretical value of the composition of each pseudo-product and the component of each pseudo-product that changes with temperature, thereby solving the error function based on the component content of each pseudo-product that changes with temperature obtained by experimental measurement and the theoretical value of the component content of each fitting that changes with temperature under corresponding conditions to obtain the model coefficients and reaction kinetic parameters, wherein the reaction kinetic parameters include but are not limited to pre-exponential factor and activation energy.

[0016] Preferably, the error function is expressed using the following expression:

[0017] F(E i ,A i ,a i,j )=∑(X exp -X cal ) 2

[0018] Among them, F represents the objective function, E i represents the activation energy parameter of the i-th reaction, a i,j Represents the elements of the model coefficient matrix, A i represents the pre-exponential factor parameter of the i-th reaction, X exp Indicates the theoretical value of component content, X cal An experimentally measured value representing the amount of a component.

[0019] Preferably, the step of predicting the formation temperature field formed by the heating conditions of the current formation based on the injection of high-temperature fluid includes: establishing a formation temperature field prediction model to obtain the distribution characteristics of the formation temperature field under the well pattern heating conditions. In the process of constructing the formation temperature field prediction model, the temperature fields generated by the electric heaters in different horizontal wells are considered and superimposed calculations are performed, including: considering the seepage of high-temperature fluid in the oil shale formation, the high-temperature fluid carries heat to transfer and exchange heat with the rock system in the form of conduction and convection, and its control equation is:

[0020]

[0021] Among them, F e represents the energy change function at different positions in the formation, t represents time, represents porosity, j represents the sequence number of different phase fluids, ρ j represents the density of the j-th phase fluid, S jrepresents the saturation of the j-th phase fluid, u j represents the seepage velocity of the j-th phase fluid, U j represents the internal energy of the j-th phase fluid, H j represents the enthalpy of the j-th phase fluid, T represents the temperature, represents the temperature gradient, ρ s represents the density of kerogen, c s represents the specific heat capacity of kerogen, k represents the thermal conductivity, represents the well injection flow rate, q H represents the fluid energy, U j represents the internal energy of the j-th phase fluid.

[0022] Preferably, the step of predicting the production change curves under different well network modes includes: simulating the pyrolysis process under actual well network heating conditions according to the model coefficients and reaction kinetic parameters; establishing mass conservation equations for different pseudo-product components using the principle of mass conservation; solving the mass conservation equations based on the mass conservation equations for different pseudo-product components, combined with different well spacings, the solved pyrolysis process, and the predicted formation temperature field distribution characteristics, thereby obtaining the production change curves of each hydrocarbon component under given formation heating conditions and given depth conditions under different well network modes.

[0023] Preferably, the mass conservation equations of the different pseudo-product components are expressed using the following expressions:

[0024]

[0025] Among them, F i represents the mass of the ith pseudo-product, t represents the time, represents porosity, j represents the sequence number of different phase fluids, ξ j represents the molar density of the j-phase fluid, ξ j =p j / ZRT, Z represents the gas compressibility coefficient, R represents the constant, T represents the temperature, p j represents the pressure of the j-phase fluid, X ij represents the mole fraction of the i-th pseudo-product component in the j-th phase fluid, u j represents the seepage velocity of the j-phase fluid, K represents the rock permeability, k rj represents the relative permeability of the j-phase fluid, μ j represents the viscosity of the j-phase fluid, represents the pressure gradient of the j-phase fluid, r k represents the reaction rate of the kth chemical reaction in the multi-step overall reaction model, v ij,krepresents the coefficient of the i-th pseudo-product component in the j-th phase fluid in the k-th chemical reaction, Indicates the well injection rate.

[0026] Preferably, the step of selecting the optimal well spacing includes: drawing target indicator curves under different well spacings using the target indicator calculation model according to the production change curves under different well spacings; determining the longest production time corresponding to the maximum target indicator value in each target indicator curve according to the target indicator curves under different well spacings; and calculating the profit value under each well spacing condition according to the longest production time corresponding to the different well spacings, so as to take the well spacing corresponding to the optimal profit value as the optimal well spacing.

[0027] Preferably, the profit value is calculated using the following expression:

[0028]

[0029] Ci=Qi×Po

[0030] Co=(P drl ·N w +P op T0+C dv )

[0031] P drl =P fix +P cph ·H

[0032] N w =N ht +N pd β

[0033] Among them, NPV represents the profit value, Ci represents the annual profit, Co represents the annual expenditure, r represents the interest rate, i represents the benchmark rate of return, N ht Number of heating wells, N pd represents the number of production wells, β represents the drilling cost ratio of production wells to heating wells, P drl represents the single well drilling cost, N w represents the well index, T0 represents the mining time, n represents the sequence number of the mining time, Qi represents the oil production, Po represents the crude oil price, C dv represents fixed investment in equipment, P op represents the operating cost, P fix represents the fixed cost of drilling a single well, P cph It represents the drilling cost per meter and H represents the well depth.

[0034] Preferably, the target indicator calculation model is expressed using the following expression:

[0035]

[0036] Q int =V·ρ r ·FA

[0037] N w =N ht +N pd β

[0038] Among them, E oe Indicates the total calorific value of hydrocarbons produced at time t, E in Indicates the cumulative energy consumed by heating at time t, Q t represents the cumulative oil production at time t, Q int Indicates the oil production potential of the mining area, N w represents the well index, V represents the total volume of organic-rich shale in the mining area, and ρ r Indicates the density of the rock, FA indicates the oil content of shale by weight as determined by the aluminum retort method, N ht Number of heating wells, N pd represents the number of production wells, and β represents the drilling cost ratio of production wells to heating wells.

[0039] Preferably, the well spacing under different well pattern modes is set by the following expression:

[0040]

[0041] Among them, L represents the well spacing, A represents the total area of ​​the mining area, N w Represents the well index.

[0042] On the other hand, an embodiment of the present invention further provides a heating well spacing evaluation system for in-situ fluid heating of oil shale, wherein the heating well spacing evaluation system is used to implement the heating well spacing evaluation method as described above, and the system includes: a basic parameter determination module, which is configured to determine the basic parameters of the rock mass based on the oil shale sample in the in-situ area of ​​the oil shale to be evaluated; a reaction parameter fitting module, which is configured to perform a pyrolysis experiment on the oil shale sample to obtain the composition of each pseudo-product and the component of each pseudo-product that changes with temperature, and based on this, fit a pre-constructed multi-step total reaction model based on kerogen pyrolysis to obtain the fitted model coefficients and reaction dynamics a well network condition setting module, which is configured to set a well network pattern based on different well spacings for the mining heating zone; a production solution module, which is configured to predict the formation temperature field formed by the heating conditions based on the injection of high-temperature fluid in the current formation based on the basic parameters of the rock mass, and based on this, in combination with the model coefficients and reaction kinetic parameters, as well as different well network patterns, predict the production change curves under different well network patterns; a well spacing evaluation module, which is configured to establish a target indicator calculation model for evaluating the quality of the well network pattern, and obtain corresponding target indicators from the production change curves under the different well network patterns, so as to select the optimal well spacing.

[0043] Compared with the prior art, one or more embodiments of the above solutions may have the following advantages or beneficial effects:

[0044] This invention proposes a method and system for evaluating heating well spacing for in-situ fluid heating of oil shale. This method and system include establishing well pattern evaluation indicators, setting well spacing, acquiring basic parameters, predicting the formation temperature field under well pattern heating conditions, and developing a chemical reaction model and calculating the net present value. This method can determine the optimal well spacing for a given production area and basic parameters, addressing the issue of insufficient basis for determining well spacing in in-situ heating oil shale production schemes.

[0045] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0047] Figure 1 Schematic diagram of the steps of the method for evaluating the heating well spacing for in-situ fluid heating of oil shale according to an embodiment of the present application.

[0048] Figure 2 This is a schematic diagram of the production change curve under different well spacing conditions in the heating well spacing evaluation method for in-situ fluid heating of oil shale in an embodiment of the present application.

[0049] Figure 3 This is a schematic diagram of a static energy variation curve under different well spacing conditions in a heating well spacing evaluation method for in-situ fluid heating of oil shale according to an embodiment of the present application.

[0050] 4( a ) and 4 ( b ) are schematic diagrams of a curve showing a change in recovery degree and a curve showing a change in target index under different well spacing conditions in a method for evaluating the heating well spacing for in-situ fluid heating of oil shale according to an embodiment of the present application.

[0051] Figure 5 This is a schematic structural diagram of a heating well spacing evaluation system for in-situ fluid heating of oil shale according to an embodiment of the present application. DETAILED DESCRIPTION

[0052] The following describes the embodiments of the present invention in detail with reference to the accompanying drawings and examples, so that the present invention can fully understand how to apply technical means to solve technical problems and achieve technical effects, and thus implement the invention accordingly. It should be noted that, as long as no conflict exists, the various embodiments of the present invention and the various features of the embodiments can be combined with each other, and the resulting technical solutions are all within the scope of protection of the present invention.

[0053] In addition, the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions. Also, although a logical order is shown in the flowchart, in some cases, the steps shown or described can be performed in a different order than here.

[0054] The terms used herein are intended only to describe specific embodiments and are not intended to limit exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms "a", "an", "an item" used herein are also intended to include the plural. It should also be understood that the terms "comprise" and / or "include" used herein specify the presence of stated features, integers, steps, operations, units and / or components, and do not preclude the presence or addition of one or more other features, integers, steps, operations, units, components and / or combinations thereof.

[0055] In-situ heating of oil shale and thermal upgrading of low-maturity shale oil are considered to be production technologies that can effectively utilize shale oil. Thermal upgrading is expected to be a breakthrough technology for effectively utilizing low-maturity shale oil. By heating the formation, viscous, heavy liquid hydrocarbons are converted into light oil, upgrading the shale oil and improving its fluidity. This also converts solid organic matter into oil and gas. Using high-temperature fluids to heat underground organic-rich shale is a major heating method, alongside Shell's ICP technology. Due to its high heating efficiency and controllable energy input per unit time, it is a major area of ​​practical exploration.

[0056] Fluid heating of underground rock formations requires determining the optimal heating well spacing. The production well spacing is crucial to production performance, directly impacting the production plan, production cycle, and input-output ratio. In recent years, pilot trials of high-temperature fluid heating of underground oil shale have been conducted in China, employing a two-injection-one-production and / or four-injection-one-production heating and production method. However, in actual production, sufficient field data is not available to determine the optimal well spacing.

[0057] Therefore, the prior art needs to provide a scheme for evaluating the distance between heating wells (for example, the distance between heating wells and the distance between heating wells and production wells) in the scenario of heating underground oil shale.

[0058] To address the issues raised in the aforementioned background technology, the present invention proposes a method and system for evaluating heating well spacing for in-situ fluid heating of oil shale. This method and system first establishes a prediction of pyrolysis product production based on pyrolysis experiments. Then, utilizing numerical simulation techniques, they construct a model that comprehensively reflects the formation temperature field and pyrolysis process, thereby determining the optimal heating well spacing. This invention addresses the issue of insufficient basis for determining well spacing in in-situ heating and production schemes for oil shale.

[0059] Figure 1 This is a schematic diagram of the steps of the heating well spacing evaluation method for in-situ fluid heating of oil shale in an embodiment of the present application. Figure 1 , the steps of the heating well spacing evaluation method described in an embodiment of the present invention are described.

[0060] Step S110 measures basic rock mass parameters based on oil shale samples in the in-situ area of ​​the oil shale to be evaluated.

[0061] In step S110, a core sample of the target organic-rich shale layer in the in-situ oil shale area to be evaluated is collected to measure basic rock mass parameters. In the embodiment of the present invention, the basic rock mass parameters include, but are not limited to, kerogen weight percentage, unit molecular weight, kerogen density, rock density, carbon-coke density, rock thermal conductivity, rock thermal conductivity, rock specific heat capacity, and porosity.

[0062] Step S120 conducts an indoor pyrolysis experiment on the oil shale (core) samples collected from the in-situ area of ​​the oil shale to be evaluated to obtain the composition of each pseudo-product and the components of each pseudo-product that change with temperature. Then, according to the (experimental) data of the component content of different pseudo-products that change with temperature, a pre-constructed multi-step overall reaction model based on kerogen pyrolysis is fitted to solve the model coefficients and reaction kinetic parameters.

[0063] In step S120, an indoor pyrolysis experiment is first conducted on the oil shale sample. Specifically, the pyrolysis experiment is conducted at a preset heating rate and under different pressure conditions to record the composition of each pseudo-product and its temperature-dependent composition. In one embodiment, the preset heating rate matches the actual formation heating rate.

[0064] After completing the indoor pyrolysis experiment, the embodiment of the present invention will first obtain the initial data of the composition of the main products changing with temperature based on the pyrolysis experiment conducted, and then merge the components with similar properties and the same carbon number in the current initial data according to the pseudo-component division results in the following multi-step overall reaction model to form multiple pseudo-products and data on the change of each pseudo-product with temperature.

[0065] Specifically, pyrolysis experiments were conducted at different pressures (P1, P2, and P3) using actual formation heating rates. Hydrocarbon components were combined based on similarity in properties and carbon number to form pseudo-components. This yielded data on the compositional content of each redefined pseudo-product, the content of other non-hydrocarbon components, and the temperature-dependent compositional content of each pseudo-product. In this embodiment, the pseudo-products include at least CH4, moisture, light oil, and heavy oil.

[0066] Then, according to the experimentally measured component content data of each fitting object, a pre-constructed multi-step overall reaction model based on kerogen pyrolysis was fitted to solve the model coefficients and reaction kinetic parameters.

[0067] Specifically, a multi-step overall reaction model based on kerogen pyrolysis was first established. This multi-step reaction model for in-situ kerogen pyrolysis describes the primary kerogen cracking and the secondary cracking of each fraction produced by the primary kerogen cracking using a first-order reaction model. Assume that there are m components of the fitted products during the in-situ kerogen pyrolysis process. This multi-step overall reaction model reflects the reaction pattern of the pyrolysis process and is expressed as follows:

[0068]

[0069]

[0070]

[0071]

[0072]

[0073]

[0074] Among them, X1, X2…X i …X m They represent the pseudo-products of the 1st, 2nd…i…mth reactions, k1, k2…k i …k m Represent the 1st, 2nd…i…mth reaction formulas respectively, Represents the model coefficient matrix for the multistep overall reaction model.

[0075] In solving the multi-step overall reaction model, an error function is first established between the experimentally measured values ​​of the composition of each pseudo-product and the temperature-dependent components of each pseudo-product and the corresponding theoretical values. The error function is then solved based on the experimentally measured temperature-dependent component content of each pseudo-product and the theoretical temperature-dependent component content of each fitted product under the corresponding conditions to obtain the model coefficients and reaction kinetic parameters. Kinetic parameters include, but are not limited to, pre-exponential factors and activation energies.

[0076] The error function is expressed as follows:

[0077] F(E i ,A i ,a i,j )=∑(X exp -X cal ) 2 (2)

[0078] In formula (2), F represents the error objective function, E i represents the activation energy parameter of the i-th reaction, a i,j Represents the elements of the model coefficient matrix, A i represents the pre-exponential factor parameter of the i-th reaction, X exp Indicates the theoretical value of component content, X cal An experimentally measured value representing the amount of a component.

[0079] In the embodiment of the present invention, the process of obtaining the model coefficients and reaction kinetic parameters is to solve the experimental values ​​(X exp ) and the theoretical value under corresponding conditions (X cal ). After completing the minimum value fit under the preset constraints, the multi-step reaction equation coefficients and reaction kinetic parameters are obtained. Table 1 shows an example of the reaction kinetic parameter table required after solving the multi-step overall reaction model.

[0080] Table 1

[0081]

[0082] After the multi-step overall reaction model is solved, the process proceeds to step S130.

[0083] Step S130 sets a well pattern based on different well spacings for the current production and heating area to be studied. In step S130, by setting different well spacings (e.g., the spacing between production wells) for the current production and heating area to be studied, a specific well pattern with different well spacing characteristics is formed.

[0084] It should be noted that the given well pattern currently described is the well pattern currently under study. It can be a five-point well pattern with one injection and four production, a five-point well pattern with four injections and one production, a two-injection and one production well pattern, or other reasonable well pattern suitable for in-situ oil shale mining scenarios. The present invention does not specifically limit this. For the same well pattern, the embodiment of the present invention will construct the same well pattern into multiple well patterns to be tested by setting different heating well spacings. Thus, the process proceeds to step S140.

[0085] Furthermore, the well spacing under different well pattern modes is set by the following expression:

[0086]

[0087] Among them, L represents the well spacing, A represents the total area of ​​the mining area, N w Indicates the following well index.

[0088] Step S140 predicts the formation temperature field formed by the heating conditions based on high-temperature fluid injection in the current in-situ formation based on the basic rock mass parameters obtained in step S110, and predicts the production change curve (i.e., the total production change curve of each hydrocarbon component) in the in-situ area of ​​the oil shale to be evaluated based on the predicted formation temperature distribution characteristics, combined with the fitted model coefficients and reaction kinetic parameters, and different (to be tested) well network patterns.

[0089] In step S140, the formation temperature field generated by the heating conditions of the current in-situ formation due to high-temperature fluid injection needs to be predicted. Specifically, a formation temperature field prediction model under the heating conditions of the current well pattern to be studied is first established to obtain the distribution characteristics of the formation temperature field under the well pattern heating conditions.

[0090] In the process of constructing the formation temperature field prediction model, the temperature fields generated by the electric heaters in different horizontal wells are considered and superimposed calculations are performed, including:

[0091] During the in-situ mining of oil shale, the seepage of high-temperature fluid in the oil shale formation is considered. The high-temperature fluid carries heat and transfers and exchanges heat with the rock system in the form of conduction and convection. The temperature control equation at different locations is:

[0092]

[0093] Among them, F e represents the energy change function at different positions in the formation, t represents time, represents porosity, j represents the sequence number of different phase fluids, ρ j represents the density of the j-th phase fluid, S j represents the fluid saturation of the jth phase fluid (i.e., the percentage of the rock pore volume), u j represents the seepage velocity of the j-th phase fluid, U j represents the internal energy of the j-th phase fluid, H j represents the enthalpy of the j-th phase fluid, T represents the temperature, represents the temperature gradient, ρ s represents the density of kerogen, c s represents the specific heat capacity of kerogen, k represents the thermal conductivity, represents the well injection flow rate, q H represents the fluid energy (the energy carried by the outflowing fluid, including internal energy and mechanical energy generated by the flow), U j Represents the internal energy of the j-th phase fluid (including the kinetic energy due to molecular motion and the potential energy due to intermolecular forces).

[0094] Therefore, after completing the construction of the formation temperature field distribution prediction model in step S140, the basic parameters of the rock mass, as well as the target layer thickness, mining area range and basic geological parameters of the oil shale in-situ area to be evaluated can be used to solve the formation temperature field distribution characteristics of the entire oil shale in-situ area to be evaluated under the actual well network heating conditions.

[0095] Next, after obtaining the formation temperature field distribution characteristics, step S140 of the embodiment of the present invention further predicts the production change curve in the in-situ area of ​​the oil shale to be evaluated.

[0096] Specifically, in the first step, the pyrolysis process under actual well pattern heating conditions is simulated based on the solved model coefficients and reaction kinetic parameters.

[0097] In the first step, pyrolysis experiments were conducted on in-situ oil shale samples from the area being evaluated to obtain data on the degree or percentage of pyrolysis of various organic products. Using this experimental data, combined with the fitted model coefficients and reaction kinetic parameters, as well as the formation temperature distribution characteristics, a numerical simulation algorithm was employed to predict the pyrolysis process under actual formation slow heating conditions. The actual formation slow heating conditions refer to the predicted formation temperature distribution characteristics.

[0098] The second step is to use the principle of mass conservation to establish mass conservation equations for different pseudo-product components. The mass conservation equations for different pseudo-product components are expressed as follows:

[0099]

[0100] In formula (5), F i represents the mass of the ith pseudo-product, t represents the time, represents porosity, j represents the sequence number of different phase fluids, ξ j represents the molar density of the j-phase fluid, ξ j =p j / ZRT, Z represents the gas compressibility coefficient, R represents the constant, T represents the temperature, p j represents the pressure of the j-phase fluid, X ij represents the mole fraction of the i-th pseudo-product component in the j-th phase fluid, u j represents the seepage velocity of the j-phase fluid, K represents the rock permeability, k rj represents the relative permeability of the j-phase fluid, μ j represents the viscosity of the j-phase fluid, represents the pressure gradient of the j-phase fluid, r k represents the reaction rate of the kth chemical reaction in the multi-step overall reaction model, v ij,k represents the coefficient of the i-th pseudo-product component in the j-th phase fluid in the k-th chemical reaction, Indicates the well injection rate.

[0101] The third step is to solve the mass conservation equation based on the mass conservation equation of different pseudo-product components, combined with different well spacings, the pyrolysis process solved under the actual well pattern heating conditions, and the predicted formation temperature field distribution characteristics, so as to obtain the (total) production change curve of each hydrocarbon component in the in-situ area of ​​the oil shale to be evaluated under given formation heating conditions and given depth conditions in different (test) well pattern modes, see Figure 2 Among them, the given formation heating condition is the above-predicted formation temperature field distribution characteristics.

[0102] Therefore, after the mass conservation equation is solved and the yield change curve is obtained, the process proceeds to step S150.

[0103] Step S150 establishes a target index calculation model for evaluating the quality of the well pattern, and obtains the target index under the corresponding well spacing conditions based on the production change curves under different well spacing conditions obtained in step S140, thereby optimizing the optimal well spacing.

[0104] In step S140, step 1, according to the production change curves under different well spacings, the preset target indicator calculation model is used to calculate the target indicators under different well spacings, thereby fitting and drawing the target indicator curves under different well spacings, see Figure 4.

[0105] In one embodiment, the target indicator calculation model is expressed using the following expression:

[0106]

[0107] Q int =V·ρ r ·FA (7)

[0108] N w =N ht +N pd β (8)

[0109] In formulas (6)-(8), E oe Indicates the total calorific value of hydrocarbons produced at time t (calculated based on the production change curve), Ein represents the cumulative energy consumed by heating at time t (calculated based on the predicted distribution characteristics of the formation temperature field), Q t represents the cumulative oil production at time t, Q int Indicates the oil production potential of the mining area, N w represents the well index, V represents the total volume of organic-rich shale in the mining area, and ρ r Indicates the density of the rock, FA indicates the oil content of shale by weight as determined by the aluminum retort method, N ht Number of heating wells, N pd represents the number of production wells, and β represents the drilling cost ratio of production wells to heating wells.

[0110] Figure 3 The net energy change curves for different well spacing conditions are shown. The net energy change curves are fitted using net energy data for different well spacing conditions. In this embodiment of the present invention, the net energy data is the difference between the gross calorific value of the produced hydrocarbons and the cumulative energy consumed for heating at the corresponding moment.

[0111] Step 2: Based on the target indicator curves for different well spacings, determine the mined time corresponding to the maximum target indicator value in each target indicator curve, recording this as the maximum mined time. The mined time is calculated by combining the real-time moment corresponding to the maximum target indicator value in each target indicator curve with the start of mining time.

[0112] Next, in step three, based on the longest production time corresponding to different well spacings, the revenue prediction model is used to calculate the revenue value under each well spacing condition, so that the well spacing corresponding to the best revenue value is taken as the optimal well spacing.

[0113] In one embodiment, the revenue prediction model is expressed using the following expression:

[0114]

[0115] Ci=Qi×Po (10)

[0116] Co=(P drl ·N w +P op T0+C dv ) (11)

[0117] P drl =P fix +P cph ·H (12)

[0118] N w =N ht +N pd β (13)

[0119] profit=Q×Po-Co (14)

[0120] In formulas (9) to (13), NPV represents the profit value; Ci represents the annual profit; Co represents the annual expenditure; r represents the interest rate; i represents the benchmark rate of return; N ht Number of heating wells, in units of wells; N pd represents the number of production wells, in units of wells; β represents the drilling cost ratio of production wells to heating wells; P drl Indicates the cost of drilling a single well, in Yuan / well; N w represents the well index; T0 represents the mining time, in months / years; n represents the sequence number of the mining time; Qi represents the oil production, in tons; Po represents the crude oil price, in yuan / ton; C dv represents fixed investment in equipment, in yuan; P op Indicates the operating cost, in yuan / day; P fix represents the fixed cost of drilling a single well; P cph represents the drilling cost per meter; H represents the well depth.

[0121] In addition, the embodiment of the present invention can also calculate the production profit under different well spacing modes according to expression (14). In step 3, the profit values ​​and production profit values ​​under different well spacings can be combined to determine the well spacing corresponding to the best profit after combining the two types of profit as the optimal well spacing.

[0122] In this way, using the above expressions (9) to (13), the benefit value corresponding to each well spacing condition can be calculated, and the well spacing condition corresponding to the maximum benefit value can be taken as the optimal well spacing.

[0123] Example

[0124] Take the mining area of ​​90*90 meters square as an example, the target layer thickness is 18 meters, the oil content is 8%, the well depth is 300 meters, the cost of drilling, completing and cementing a single well is 800,000 yuan, the surface equipment is 10 million yuan, and the operating cost is 2.3 million yuan / year. The production curve, net energy curve, recovery degree curve and target index curve under different well spacing conditions are respectively shown in Figure 2 、 Figure 3 , Figure 4(a) and Figure 4(b). According to the heating well spacing evaluation method described in an embodiment of the present invention, the net present value of the test well pattern based on 30m, 45m, and 90m well spacing conditions is calculated to be -5.01 million yuan, 1.49 million yuan, and -8.45 million yuan, respectively. Of these, 45 meters is the optimal well spacing.

[0125] On the other hand, based on the above-mentioned heating well spacing evaluation method, an embodiment of the present invention further provides a heating well spacing evaluation system for in-situ fluid heating of oil shale. The heating well spacing evaluation system is used to implement the above-mentioned heating well spacing evaluation method.

[0126] Figure 5 This is a schematic diagram of the structure of the heating well spacing evaluation system for in-situ fluid heating of oil shale in an embodiment of the present application. Figure 5 As shown, the heating well spacing evaluation system described in the embodiment of the present invention includes: a basic parameter determination module 510, a reaction parameter fitting module 520, a well network condition setting module 530, a production solution module 540 and a well spacing evaluation module 550.

[0127] Specifically, the basic parameter determination module 510 is implemented according to the method described in step S110 above, and is configured to determine the basic parameters of the rock mass based on the oil shale samples in the in-situ area of ​​the oil shale to be evaluated; the reaction parameter fitting module 520 is implemented according to the method described in step S120 above, and is configured to perform a pyrolysis experiment on the oil shale samples to obtain the composition of each pseudo-product and the components of each pseudo-product that change with temperature, based on which, a pre-constructed multi-step total reaction model based on kerogen pyrolysis is fitted to obtain the fitted model coefficients and reaction kinetic parameters; the well network condition setting module 530 is implemented according to the method described in step S130 above, and is configured to set a well network condition based on different well spacings for the mining heating zone. Well network mode; the production solution module 540 is implemented according to the method described in the above step S140, and is configured to predict the formation temperature field formed by the heating conditions based on high-temperature fluid injection in the current formation according to the basic parameters of the rock mass, and based on this, combined with the permeability at different depths, as well as the model coefficients and reaction kinetic parameters, predict the production change curves of various hydrocarbon components in the in-situ area of ​​the oil shale to be evaluated; the well spacing evaluation module 550 is implemented according to the method described in the above step S150, and is configured to establish a target indicator calculation model for evaluating the advantages and disadvantages of the well network mode, and obtain corresponding target indicators from the production change curves under different well network modes, so as to select the optimal well spacing.

[0128] The present invention discloses a method and system for evaluating heating well spacing for in-situ fluid heating of oil shale. The method and system include establishing well pattern evaluation indicators, setting well spacing, acquiring basic parameters, predicting the formation temperature field under well pattern heating conditions, and developing a chemical reaction model and calculating the net present value. The present invention determines the optimal well spacing for a given production area and basic parameters, addressing the issue of insufficient basis for determining well spacing in in-situ heating oil shale production schemes.

[0129] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by anyone skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

[0130] In the description of the present invention, unless otherwise specified, "plurality" means two or more; terms such as "upper," "lower," "left," "right," "inner," "outer," "front end," "rear end," "head," and "tail" indicate positions or relationships based on those shown in the accompanying drawings. These terms are intended solely to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, terms such as "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0131] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "connected" and "connection" should be understood in a broad sense. For example, they can refer to fixed connection, detachable connection, or integral connection; mechanical connection, electrical connection; direct connection, or indirect connection through an intermediary. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0132] It should be understood that the embodiments disclosed herein are not limited to the specific structures, processing steps, or materials disclosed herein, but should extend to equivalent substitutions of these features understood by those skilled in the relevant art. It should also be understood that the terminology used herein is for the purpose of describing specific embodiments only and is not intended to be limiting.

[0133] References in this specification to "one embodiment" or "an embodiment" mean that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Therefore, appearances of the phrases "one embodiment" or "an embodiment" in various places throughout this specification do not necessarily refer to the same embodiment.

[0134] Although the embodiments disclosed above are for facilitating understanding of the present invention, the contents described are merely embodiments adopted for facilitating understanding of the present invention and are not intended to limit the present invention. Any person skilled in the art of the present invention may make any modifications and changes in the form and details of the implementation without departing from the spirit and scope of the present invention. However, the scope of patent protection of the present invention shall still be subject to the scope defined by the appended claims.

Claims

1. A method for evaluating the heating well spacing for in-situ fluid heating of oil shale, characterized in that: include: Obtain oil shale samples from the oil shale area to be evaluated and determine the basic parameters of the rock mass; A pyrolysis experiment is performed on the oil shale sample to obtain the composition of each pseudo-product and the temperature-dependent component of each pseudo-product. Based on this, a pre-constructed multi-step overall reaction model based on kerogen pyrolysis is fitted to obtain the fitted model coefficients and reaction kinetic parameters; Set up a well pattern based on different well spacing for the mining heating area; Based on the basic rock mass parameters, the formation temperature field formed by the heating conditions of the current formation due to the injection of high-temperature fluid is predicted. Based on this, the production change curves under different well pattern patterns are predicted in combination with the model coefficients and reaction kinetic parameters and different well pattern patterns. A target index calculation model for evaluating the quality of well pattern is established, and corresponding target indexes are obtained from the production change curves under the different well pattern patterns, so as to select the optimal well spacing.

2. The method according to claim 1, characterized in that The step of performing a pyrolysis experiment on the oil shale sample to obtain the composition of each pseudo-product and the temperature-dependent components of each pseudo-product includes: Based on the pyrolysis experiments carried out, initial data on the composition of the main products as a function of temperature were obtained; According to the pseudo-component division results in the multi-step overall reaction model, the components with similar properties and the same carbon number in the initial data are merged to form multiple pseudo-products and temperature-dependent data of each pseudo-product.

3. The method for evaluating the heating well spacing according to claim 1 or 2, wherein: The steps of performing a pyrolysis experiment on the oil shale sample to obtain the composition of each pseudo-product and the temperature-dependent components of each pseudo-product, and fitting a pre-constructed multi-step overall reaction model based on kerogen pyrolysis to obtain fitted model coefficients and reaction kinetic parameters include: Carry out heating pyrolysis experiments at a preset heating rate and under different pressure conditions to record the composition of each pseudo-product and the changes in the composition of each pseudo-product with temperature; The multi-step overall reaction model based on kerogen pyrolysis is established, and the multi-step overall reaction model is: Where m represents the total number of pseudo-products, X1, X2…X i …X m represents the pseudo-products of the 1st, 2nd…i…mth reactions, k1, k2…k i …k m Represents the 1st, 2nd…i…mth reaction formula, represents the model coefficient matrix; An error function is established between the experimental measurement values ​​and theoretical values ​​of the composition of each pseudo-product and the components of each pseudo-product that change with temperature, so as to solve the error function based on the experimentally measured component content of each pseudo-product that changes with temperature and the theoretical value of the component content of each fitting under corresponding conditions that changes with temperature, and obtain the model coefficients and reaction kinetic parameters, wherein the reaction kinetic parameters include but are not limited to the pre-exponential factor and activation energy.

4. The method for evaluating the heating well spacing according to claim 3, wherein: The error function is expressed as follows: F(E i ,A i ,a i,j )=∑(X exp -X cal ) 2 Among them, F represents the objective function, E i represents the activation energy parameter of the i-th reaction, a i,j Represents the elements of the model coefficient matrix, A i represents the pre-exponential factor parameter of the i-th reaction, X exp Indicates the theoretical value of component content, X cal An experimentally measured value representing the amount of a component.

5. The method for evaluating the distance between heater wells according to any one of claims 1 to 4, wherein: The step of predicting the formation temperature field formed by the heating conditions of the current formation due to the injection of high-temperature fluid includes: A formation temperature field prediction model is established to obtain the distribution characteristics of the formation temperature field under the well pattern heating condition. In the process of constructing the formation temperature field prediction model, the temperature fields generated by the electric heaters in different horizontal wells are considered and superimposed calculations are performed, including: Considering the seepage of high-temperature fluid in the oil shale formation, the high-temperature fluid carries heat and transfers and exchanges heat with the rock system in the form of conduction and convection. The governing equation is: Among them, F e represents the energy change function at different positions in the formation, t represents time, represents porosity, j represents the sequence number of different phase fluids, ρ j represents the density of the j-th phase fluid, S j represents the saturation of the j-th phase fluid, u j represents the seepage velocity of the j-th phase fluid, U j represents the internal energy of the j-th phase fluid, H j represents the enthalpy of the j-th phase fluid, T represents the temperature, represents the temperature gradient, ρ s represents the density of kerogen, c s represents the specific heat capacity of kerogen, k represents the thermal conductivity, represents the well injection flow rate, q H represents the fluid energy, U j represents the internal energy of the j-th phase fluid.

6. The method for evaluating the distance between heater wells according to any one of claims 1 to 5, wherein: The steps for predicting production change curves under different well pattern modes include: Based on the model coefficients and reaction kinetic parameters, the pyrolysis process under the actual well pattern heating conditions is simulated; Using the principle of mass conservation, the mass conservation equations for different pseudo-product components are established; Based on the mass conservation equation of the different pseudo-product components, combined with different well spacings, the solved pyrolysis process, and the predicted formation temperature field distribution characteristics, the mass conservation equation is solved to obtain the production change curves of each hydrocarbon component under given formation heating conditions and given depth conditions under different well network modes.

7. The method for evaluating the heating well spacing according to claim 6, wherein: The mass conservation equations of the different pseudo-product components are expressed using the following expressions: Among them, F i represents the mass of the ith pseudo-product, t represents the time, represents porosity, j represents the sequence number of different phase fluids, ξ j represents the molar density of the j-phase fluid, ξ j =p j / ZRT, Z represents the gas compressibility coefficient, R represents the constant, T represents the temperature, p j represents the pressure of the j-phase fluid, X ij represents the mole fraction of the i-th pseudo-product component in the j-th phase fluid, u j represents the seepage velocity of the j-phase fluid, K represents the rock permeability, k rj represents the relative permeability of the j-phase fluid, μ j represents the viscosity of the j-phase fluid, represents the pressure gradient of the j-phase fluid, r k represents the reaction rate of the kth chemical reaction in the multi-step overall reaction model, v ij,k represents the coefficient of the i-th pseudo-product component in the j-th phase fluid in the k-th chemical reaction, Indicates the well injection rate.

8. The method for evaluating the distance between heater wells according to any one of claims 1 to 7, wherein: The steps of optimizing the optimal well spacing include: According to the production change curves under different well spacings, the target indicator calculation model is used to draw the target indicator curves under different well spacings; Determining the longest production time corresponding to the maximum target index value in each target index curve according to the target index curves under different well spacings; According to the longest production time corresponding to different well spacings, the profit value under each well spacing condition is calculated, and the well spacing corresponding to the best profit value is taken as the optimal well spacing.

9. The method for evaluating the heating well spacing according to claim 8, wherein: The profit value is calculated using the following expression: Ci=Qi×Po Co=(P drl ·N w +P op ·T0+C dv ) P drl =P fix +P cph ·H N w =N ht +N pd ·b Among them, NPV represents the profit value, Ci represents the annual profit, Co represents the annual expenditure, r represents the interest rate, i represents the benchmark rate of return, N ht Number of heating wells, N pd represents the number of production wells, β represents the drilling cost ratio of production wells to heating wells, P drl represents the single well drilling cost, N w represents the well index, T0 represents the mining time, n represents the sequence number of the mining time, Qi represents the oil production, Po represents the crude oil price, C dv represents fixed investment in equipment, P op represents the operating cost, P fix represents the fixed cost of drilling a single well, P cph represents the drilling cost per meter, and H represents the well depth.

10. The method for evaluating the distance between heating wells according to claim 8 or 9, wherein: The target indicator calculation model is expressed using the following expression: Q int =V·ρ r ·FA N w =N ht +N pd ·b Among them, E oe Indicates the total calorific value of hydrocarbons produced at time t, E in Indicates the cumulative energy consumed by heating at time t, Q t represents the cumulative oil production at time t, Q int Indicates the oil production potential of the mining area, N w represents the well index, V represents the total volume of organic-rich shale in the mining area, and ρ r Indicates the density of the rock, FA indicates the oil content of the shale by weight as determined by the aluminum retort method, and N ht Number of heating wells, N pd represents the number of production wells, and β represents the drilling cost ratio of production wells to heating wells.

11. The method for evaluating the distance between heater wells according to any one of claims 1 to 10, wherein: The well spacing in different well pattern modes is set by the following expressions: Among them, L represents the well spacing, A represents the total area of ​​the mining area, N w Represents the well index.

12. A heating well spacing evaluation system for in-situ fluid heating of oil shale, characterized in that: The heating well spacing evaluation system is used to implement the heating well spacing evaluation method according to any one of claims 1 to 11, and the system includes: a basic parameter determination module configured to determine basic rock mass parameters based on oil shale samples from an in-situ area of ​​the oil shale to be evaluated; a reaction parameter fitting module configured to perform a pyrolysis experiment on the oil shale sample to obtain the composition of each pseudo-product and the temperature-dependent components of each pseudo-product, and based on this, fit a pre-constructed multi-step overall reaction model based on kerogen pyrolysis to obtain fitted model coefficients and reaction kinetic parameters; a well pattern condition setting module configured to set a well pattern mode based on different well spacings for the mining heating zone; a production solution module configured to predict, based on the basic rock mass parameters, a formation temperature field formed by heating conditions caused by high-temperature fluid injection in the current formation, and based on this, combine the model coefficients and reaction kinetic parameters with different well pattern patterns to predict production change curves under different well pattern patterns; The well spacing evaluation module is configured to establish a target indicator calculation model for evaluating the quality of the well network mode, and obtain corresponding target indicators from the production change curves under the different well network modes, so as to optimize the optimal well spacing.

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