A method and system for calculating fluid parameters in thick, light oil reservoirs.

Abstract

This invention discloses a method and system for calculating fluid parameters in thick, light oil reservoirs, comprising: performing conventional pressure tests and production profile tests on the target reservoir and creating a pressure curve varying with depth; determining, based on the pressure curve, whether the influence of gravity differentiation on fluid properties reaches a preset level; calculating a pressure gradient estimate based on the pressure curve and calculating a first estimated gradient corresponding to the current fluid parameter to be analyzed; selecting a fluid sample from the deepest wellbore and conducting laboratory experiments to obtain the corresponding starting data of the fluid parameters; then, combining the interpretation results of the production profile and the first estimated gradient, using a gradient iteration method to calculate the vertical distribution data of the current fluid parameter to be analyzed. This invention improves the calculation accuracy of the vertical distribution of fluids while reducing the uncertainty risk of fluid prediction.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development technology, and in particular to a method and system for calculating fluid parameters of thick, light oil reservoirs. Background Technology

[0002] Fluid properties within an oil reservoir are fundamental parameters for oil and gas field development research. The properties of oil and gas within formations vary greatly, not only in phase state but also in properties within the same phase. These differences in fluid properties complicate reservoir development, and the accurate identification and evaluation of reservoir fluids significantly impacts the accuracy of parameters such as oil and gas geological reserve estimation, rational development methods, development plans, production forecasts, and benefit evaluation.

[0003] During hydrocarbon generation, migration, and accumulation, the types of deposited organic matter, differential accumulation, separation and migration, gravity (buoyancy) differentiation, and oxidation can all lead to differences in fluid properties, resulting in differentiation phenomena. For heavy oil with an API gravity of less than 20, diffusion and oxidation are the main reasons for fluid differences caused by later changes in hydrocarbon properties. However, for other ordinary or light oil reservoirs, especially light oil reservoirs with an API gravity greater than 30, differentiation during hydrocarbon accumulation is mainly due to gravity (buoyancy). In areas with active groundwater, hydrodynamics also affect hydrocarbon distribution, but the origin of hydrodynamics is still gravity.

[0004] For ordinary light oil reservoirs with a small reservoir thickness, the prediction error of parameters such as development plan and production forecast can be acceptable within a certain range if fluid differentiation is not considered. However, for oil reservoirs with a large thickness (greater than 100 meters), gravity separation is more obvious, and the accurate calculation of fluid properties has a significant impact on the prediction of relevant parameters.

[0005] Currently, there is considerable research on differentiation phenomena in heavy oil and condensate gas reservoirs both domestically and internationally. While many domestic and international publications mention differentiation phenomena in ordinary light oil reservoirs, the evaluation methods are limited, requiring a large number of fluid samples and substantial laboratory experimental data. Unfortunately, this data collection demands significant financial, material, and time resources. For some reservoirs, especially thick reservoirs in the early stages of development, the lack of suitable sample data, excessively large sampling intervals, or mixed sampling results in insufficient reliable sample data to describe the fluid distribution throughout the reservoir. Furthermore, inadequate laboratory experimental data makes it difficult for existing calculation methods to fully account for the effects of gravity differentiation, leading to significant uncertainties in subsequent fluid modeling, development scheme design, and performance prediction.

[0006] To solve the above-mentioned technical problems, it is necessary to establish a new scheme for rapid calculation of fluid parameters applicable to thick, light oil reservoirs. Summary of the Invention

[0007] To address the aforementioned technical problems, this invention provides a method for calculating fluid parameters in thick, light oil reservoirs, comprising: performing conventional pressure tests and production profile tests on the target reservoir and creating a pressure curve varying with depth; determining, based on the pressure curve, whether the influence of gravity differentiation on fluid properties reaches a preset level; calculating a pressure gradient estimate based on the pressure curve, and further calculating a first estimated gradient corresponding to the current fluid parameter to be analyzed; selecting the fluid sample at the deepest well bottom and conducting laboratory experiments to obtain the corresponding fluid parameter starting data; and then, combining the production profile interpretation results and the first estimated gradient, using a gradient iteration method to calculate the vertical distribution data of the current fluid parameter to be analyzed.

[0008] Preferably, the method further includes: fitting the vertical distribution data of the current fluid parameter to be analyzed; calculating the actual value of the fluid parameter to be analyzed at the corresponding depth based on the collected bottom oil sample; comparing the actual value of the fluid parameter to be analyzed with the fitting curve corresponding to the vertical distribution data to determine whether the first estimated gradient needs to be adjusted.

[0009] Preferably, the vertical distribution data of the fluid parameter to be calculated is calculated using the following expression:

[0010]

[0011] Where i represents the sequence number of each vertical interpretation measurement point, n represents the total number of interpretation measurement points, and M PLT(i) M PLT(n) Q represents the fluid parameter values ​​corresponding to the i-th and n-th interpretation measurement points, respectively. PLT(i) Q PLT(n) D represents the fluid flow rate value corresponding to the i-th and n-th interpretation measurement points, respectively. n D n-1 G represents the vertical depth corresponding to the i-th and n-th interpretation measurement points, respectively. est M represents the first estimated gradient. Grad(n-1) This represents the iterative measurement value of the fluid parameter corresponding to the (n-1)th interpretation measurement point.

[0012] Preferably, the fluid parameters to be analyzed include, but are not limited to, one or more of the following: fluid density, API, fluid viscosity, fluid gas-oil ratio, volume factor, and molar content of pseudo-components.

[0013] Preferably, the step of determining whether the influence of gravity differentiation on fluid properties reaches a preset level based on the pressure curve includes: plotting an overpressure curve that varies with depth based on the pressure curve; identifying fluid density change characteristics and fluid composition change characteristics based on the overpressure curve, and determining the influence of gravity differentiation on the fluid properties of the target reservoir.

[0014] Preferably, the step of calculating the pressure gradient estimate based on the pressure curve includes: performing linear regression fitting on the pressure curve to obtain a corresponding expression; and determining the pressure gradient estimate based on the expression corresponding to the pressure curve.

[0015] Preferably, the step of creating a pressure curve that varies with depth includes: acquiring existing pressure data about the target reservoir, verifying the quality and reliability of the existing pressure data, and selecting representative pressure data; and constructing the pressure curve based on the verified pressure data.

[0016] Preferably, the method further includes: conducting indoor experiments on the collected bottom oil samples to obtain measured data of various fluid parameters generated based on the indoor experiments; comparing the measured data of the various fluid parameters with the vertical distribution data of the fluid parameters to be analyzed to verify the calculation results of the vertical variability of fluid properties.

[0017] In addition, the present invention also provides a system for calculating fluid parameters of thick, light oil reservoirs, comprising: a pressure curve plotting module configured to perform conventional pressure tests and production profile tests on the target reservoir and create a pressure curve that varies with depth; a gravity differentiation evaluation module configured to determine, based on the pressure curve, whether the influence of gravity differentiation on fluid properties reaches a preset level; a fluid parameter gradient generation module configured to calculate a pressure gradient estimate based on the pressure curve and further calculate a first estimated gradient corresponding to the current fluid parameter to be analyzed; and a vertical distribution feature generation module configured to select the fluid sample at the deepest bottom of the well and conduct laboratory experiments to obtain the corresponding fluid parameter starting data, and then, combined with the production profile interpretation results and the first estimated gradient, use a gradient iteration method to calculate the vertical distribution data of the current fluid parameter to be analyzed.

[0018] Preferably, the fluid parameters to be analyzed include, but are not limited to, one or more of the following: fluid density, API, fluid viscosity, fluid gas-oil ratio, volume factor, and molar content of pseudo-components.

[0019] Compared with the prior art, one or more embodiments of the above solutions may have the following advantages or beneficial effects:

[0020] This invention discloses a method and system for calculating fluid parameters in thick, light oil reservoirs. When the number of effective oil and gas samples is limited or laboratory analysis data is scarce, this method and system utilizes conventional pressure data and a small amount of sample analysis data, combined with production profile testing (PLT) interpretation results. Starting with analysis of highly reliable bottomhole fluid samples, PLT iterative decomposition transforms the data into changes in fluid density and other fluid parameters, effectively predicting the vertical distribution of fluid components. Thus, this invention provides a rapid scheme for calculating the vertical distribution of fluid parameters in thick, light oil reservoirs under the influence of gravity differentiation, achieving a prediction accuracy of within 5%, effectively reducing development risks. Furthermore, this invention can also be applied to ordinary light oil reservoirs with large reservoir thicknesses, where gravity differentiation has a certain impact on the vertical distribution of fluids. However, when the number of effective oil and gas samples is limited, the reliability of sample data is insufficient, formation pressure test data is scarce, or time is limited and experimental data is insufficient, making it difficult to directly obtain the vertical component distribution of fluids, this invention enables the prediction of fluid property changes with depth. This not only improves the calculation accuracy of the vertical distribution of fluids but also reduces the uncertainty risk of fluid prediction.

[0021] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims and drawings. Attached Figure Description

[0022] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0023] Figure 1 This is a step diagram of a method for calculating fluid parameters in a thick, light oil reservoir according to an embodiment of this application.

[0024] Figure 2 This is a flowchart illustrating the specific process for calculating fluid parameters in a thick, light oil reservoir according to an embodiment of this application, where the fluid parameter to be analyzed is fluid density.

[0025] Figure 3 This is a schematic diagram illustrating the effect of conventional pressure data in the method for calculating fluid parameters of thick, light oil reservoirs according to an embodiment of this application, specifically for the C oilfield example.

[0026] Figure 4 This is a schematic diagram of the pressure curve effect for an example of oilfield C in the method for calculating fluid parameters of thick light oil reservoirs according to an embodiment of this application.

[0027] Figure 5This is a schematic diagram illustrating the interpretation of production profile test results for an example of oilfield C in the method for calculating fluid parameters of thick, light oil reservoirs according to an embodiment of this application.

[0028] Figure 6 This is a schematic diagram showing the comparison between the calculated fluid gas-oil ratio and the measured value of the sample in the method for calculating fluid parameters of thick light oil reservoirs according to an embodiment of this application, specifically for the C oilfield example.

[0029] Figure 7 This is a schematic diagram comparing the API calculated values ​​with the measured values ​​of the sample in the method for calculating fluid parameters of thick light oil reservoirs according to an embodiment of this application, specifically for the C oilfield example.

[0030] Figure 8 This is a schematic diagram showing the comparison between the calculated C1 content and the measured value of the sample in the method for calculating fluid parameters of thick light oil reservoirs according to an embodiment of this application, specifically for the C oilfield example.

[0031] Figure 9 This is a schematic diagram showing the comparison between the calculated C7+ content and the measured value of the sample in the method for calculating fluid parameters of thick light oil reservoirs according to an embodiment of this application, specifically for the C oilfield example.

[0032] Figure 10 This is a schematic diagram showing the comparison between the calculated fluid density value and the measured value of the sample in the method for calculating fluid parameters of thick light oil reservoirs according to an embodiment of this application, specifically for the C oilfield example.

[0033] Figure 11 This is a schematic diagram of a system for calculating fluid parameters in thick, light oil reservoirs, according to an embodiment of this application. Detailed Implementation

[0034] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples, so that the process of how the present invention uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that, as long as there is no conflict, the various embodiments and features in the various embodiments of the present invention can be combined with each other, and the resulting technical solutions are all within the protection scope of the present invention.

[0035] Furthermore, the steps illustrated in the flowcharts 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 flowcharts, in some cases the steps shown or described may be performed in a different order than that shown here.

[0036] Fluid properties within an oil reservoir are fundamental parameters for oil and gas field development research. The properties of oil and gas within formations vary greatly, not only in phase state but also in properties within the same phase. These differences in fluid properties complicate reservoir development, and the accurate identification and evaluation of reservoir fluids significantly impacts the accuracy of parameters such as oil and gas geological reserve estimation, rational development methods, development plans, production forecasts, and benefit evaluation.

[0037] During hydrocarbon generation, migration, and accumulation, the types of deposited organic matter, differential accumulation, separation and migration, gravity (buoyancy) differentiation, and oxidation can all lead to differences in fluid properties, resulting in differentiation phenomena. For heavy oil with an API gravity of less than 20, diffusion and oxidation are the main reasons for fluid differences caused by later changes in hydrocarbon properties. However, for other ordinary or light oil reservoirs, especially light oil reservoirs with an API gravity greater than 30, differentiation during hydrocarbon accumulation is mainly due to gravity (buoyancy). In areas with active groundwater, hydrodynamics also affect hydrocarbon distribution, but the origin of hydrodynamics is still gravity.

[0038] For ordinary light oil reservoirs with a small reservoir thickness, the prediction error of parameters such as development plan and production forecast can be acceptable within a certain range if fluid differentiation is not considered. However, for oil reservoirs with a large thickness (greater than 100 meters), gravity separation is more obvious, and the accurate calculation of fluid properties has a significant impact on the prediction of relevant parameters.

[0039] Currently, there is considerable research on differentiation phenomena in heavy oil and condensate gas reservoirs both domestically and internationally. While many domestic and international publications mention differentiation phenomena in ordinary light oil reservoirs, the evaluation methods are limited, requiring a large number of fluid samples and substantial laboratory experimental data. Unfortunately, this data collection demands significant financial, material, and time resources. For some reservoirs, especially thick reservoirs in the early stages of development, the lack of suitable sample data, excessively large sampling intervals, or mixed sampling results in insufficient reliable sample data to describe the fluid distribution throughout the reservoir. Furthermore, inadequate laboratory experimental data makes it difficult for existing calculation methods to fully account for the effects of gravity differentiation, leading to significant uncertainties in subsequent fluid modeling, development scheme design, and performance prediction.

[0040] To address the aforementioned technical problems, this application proposes a method and system for calculating fluid parameters applicable to thick, light oil reservoirs. This method and system integrates different disciplines to attempt to solve the uncertainty in the vertical distribution of fluid parameters when sufficient laboratory fluid experimental data or fluid sample points are unavailable. The scheme combines pressure testing, bottomhole flow sampling, and production profile testing data. Starting with pressure changes, it analyzes the fluid property changes caused by gravity differentiation in real time. Then, based on the production profile interpretation results and pressure change characteristics, it iteratively decomposes the fluid parameters of highly reliable bottomhole fluid samples and transforms them into corresponding types of fluid parameter change characteristics, thereby achieving the prediction of the vertical distribution characteristics of fluid components.

[0041] In this way, the present invention comprehensively utilizes conventional reservoir monitoring and reservoir engineering data, such as pressure test data, bottom hole flow sample data, production profile test data, and a small amount of indoor experimental data, to calculate and realize the prediction of the changes in crude oil fluid properties with depth in thick light oil reservoirs considering the influence of gravity differentiation. This improves the calculation accuracy of vertical fluid distribution, reduces the uncertainty risk of fluid prediction, and makes the prediction accuracy controllable within 5%.

[0042] Figure 1 This is a flowchart illustrating the steps of a method for calculating fluid parameters in a thick, light oil reservoir, according to an embodiment of this application. Figure 1 As shown in the embodiments of the present invention, the method for calculating fluid parameters of thick, light oil reservoirs (hereinafter referred to as the "fluid parameter calculation method") includes the following steps:

[0043] Step S110 involves performing conventional pressure tests and production profile tests on the target reservoir, and creating a pressure curve that varies with depth. It should be noted that the target reservoir described in this embodiment of the invention is a thick light oil reservoir. In step S110, conventional pressure tests and production profile tests are first performed on the thick light oil reservoir for which vertical distribution characteristics of fluid parameters need to be analyzed. Based on the pressure data obtained from the conventional pressure tests, a (conventional) pressure curve that varies with depth is created. Furthermore, to ensure the smooth implementation of this embodiment of the invention, bottom hole oil samples need to be collected, and corresponding laboratory experiments are conducted on the bottom hole oil samples.

[0044] It should be noted that the conventional pressure tests described in the embodiments of the present invention typically include cable formation pressure tests and drill pipe formation pressure tests. Furthermore, to ensure prediction accuracy, the embodiments of the present invention require at least three bottom-hole oil samples at different depths. Preferably, the present invention requires three bottom-hole oil samples.

[0045] After obtaining the data required for the current fluid parameter calculation method, proceed to step S120. Step S120, based on the conventional pressure curve created in step S110, determines whether the influence of gravity differentiation on the fluid properties of the target reservoir reaches a preset level. If, in step S120, the influence of gravity differentiation reaches the preset level, it indicates that gravity differentiation has affected the predicted changes in the fluid properties of the target thick, light oil reservoir, and the process proceeds to step S130 to calculate the vertical distribution characteristics of the fluid parameters in the target reservoir under gravity differentiation. If the current influence of gravity differentiation does not reach the preset level, it indicates that the current gravity differentiation has not affected the predicted changes in the fluid properties of the target thick light oil reservoir. In step S120, based on the conventional pressure test data, production profile interpretation data (obtained through production profile testing), and bottom hole flow samples collected in step S110, it is further determined whether the influence of gravity differentiation on the fluid properties of the target oil reservoir has reached the preset level.

[0046] When the influence of gravity differentiation on the fluid properties of the target reservoir reaches a preset level, step S130 calculates the pressure gradient estimate based on the pressure curve obtained in step S110, and then converts the currently calculated pressure gradient estimate into the first estimated gradient corresponding to the fluid parameter to be analyzed. In this embodiment of the invention, the fluid parameter to be analyzed may include any one or more of various types of fluid parameters. Specifically, when calculating the vertical distribution characteristic data of a certain fluid parameter (e.g., fluid density), in step S130, the currently calculated pressure gradient estimate needs to be converted into the estimated gradient corresponding to the current type of analysis, denoted as the first estimated gradient (fluid density estimated gradient). When calculating the vertical distribution characteristic data of multiple types of fluid parameters (e.g., fluid density, fluid gas-oil ratio, and C1 content in the fluid), in step S130, the currently calculated pressure gradient estimate needs to be converted into the estimated gradient corresponding to the respective type of analysis, and a corresponding first estimated gradient is obtained for each fluid parameter (e.g., the pressure gradient estimate is converted into the fluid density estimated gradient, the gas-oil ratio estimated gradient, and the C1 content estimated gradient).

[0047] Furthermore, in this embodiment of the invention, the fluid parameters to be analyzed include, but are not limited to, one or more of the following: fluid density, API (active oil content), fluid viscosity, fluid gas-oil ratio, volume factor, and molar content of pseudo-components (e.g., C1 content in the fluid, C7+ content in the fluid). It should be noted that this embodiment of the invention does not specifically limit the number and type of fluid parameters included in the fluid parameters to be analyzed; those skilled in the art can select them according to actual needs.

[0048] After obtaining the estimated gradient values ​​corresponding to the fluid parameters to be analyzed, the process proceeds to step S140. In step S140, the fluid sample from the deepest well bottom is selected and subjected to laboratory experiments to obtain the corresponding starting data of the fluid parameters. Then, combined with the interpretation results of the production profile and the first estimated gradient obtained in step S130, the gradient iteration method is used to calculate the vertical distribution data of the current fluid parameters to be analyzed.

[0049] In step S140, firstly, based on the collected bottom-hole fluid samples, laboratory experiments are conducted on these fluid samples to obtain fluid parameters for the fluid samples (the number and types of fluid parameters based on the laboratory experiments are consistent with the number and types of the fluid parameters to be analyzed). Then, using the fluid parameters based on the laboratory experiments as the starting point for calculation, combined with the interpretation results of the production profile test obtained according to step S110, and using one or more first estimated gradient data obtained in step S130, the gradient iteration method is used to calculate the vertical distribution data corresponding to each type (each item) of the fluid parameter to be analyzed.

[0050] Figure 2 This is a flowchart illustrating the specific process for calculating fluid parameters in a thick, light oil reservoir according to an embodiment of this application, when the fluid parameter to be analyzed is fluid density. The following is a detailed flowchart in conjunction with... Figure 1 and Figure 2 The specific process of the fluid parameter calculation method described in the embodiments of the present invention will be explained.

[0051] In step S110, after conducting conventional pressure tests, production profile tests, and laboratory experiments on the collected bottom-hole fluid samples of the target reservoir, pressure data based on the conventional pressure tests, production profile interpretation results, and fluid parameters based on the laboratory experiments are obtained. Then, based on the existing pressure data of the target reservoir obtained from the aforementioned tests and experiments, the quality and reliability of the existing pressure data are verified, and representative pressure data are selected. Specifically, when evaluating the quality and reliability of the existing pressure data, unreliable data points such as those with poor stability or affected by capillary forces need to be deleted to ensure that the obtained pressure data is representative.

[0052] Next, based on the currently verified (unreliable data points removed) (standard) pressure data (reference)... Figure 3 To construct a conventional pressure curve (refer to...) Figure 4Because the amount of pressure data obtained from conventional pressure tests is relatively small and the consistency of the obtained pressure data is poor, in order to draw a conventional pressure-depth curve based on the verified conventional pressure data, it is necessary to identify nonlinear trends that may indicate the change of fluid density with depth. That is, based on the verified pressure data, the nonlinear trends in the pressure data that indicate the change of fluid density with depth are identified, thereby forming the pressure curve obtained in step S110.

[0053] Further, in step S120, this embodiment of the invention requires plotting an overpressure curve varying with depth based on the conventional pressure curve constructed in step S110. When plotting the overpressure curve, the pressure values ​​of each data point in the formed pressure curve are compared with a preset pressure baseline standard. For data points whose pressure values ​​exceed the pressure baseline standard, a corresponding overpressure curve is plotted. Then, based on the currently plotted overpressure curve, the fluid density variation characteristics and fluid composition variation characteristics are identified, thereby determining the degree of influence of gravity differentiation on the fluid properties of the target reservoir. In this embodiment of the invention, the pressure baseline standard is used to evaluate the pressure limit value corresponding to whether the fluid at a specific well depth is affected by gravity differentiation. When the pressure value at a certain vertical depth point exceeds this limit value, it indicates that the fluid properties at the current location are likely to be negatively affected by gravity differentiation; when the pressure value at a certain vertical depth point does not exceed this limit value, it indicates that the fluid properties at the current location have not yet been negatively affected by gravity differentiation.

[0054] When the influence of the current gravity differentiation on the fluid properties of the target reservoir exceeds the preset level, the process proceeds to step S130.

[0055] Furthermore, in step S130 of this embodiment of the invention, the pressure gradient estimate based on the pressure curve drawn in the current step S110 is first calculated. Specifically, firstly, the pressure curve formed in the current step S110 is subjected to linear regression fitting to obtain the corresponding expression (i.e., the pressure curve expression). Then, based on the expression corresponding to the pressure curve, the current pressure gradient estimate is determined. More specifically, the pressure depth curve is first regressed to determine the relationship, and the intuitive pressure gradient value (pressure gradient estimate) is calculated. When performing regression fitting on the pressure curve, methods such as residual method, R-squared, or T-test can be used to ensure minimum error.

[0056] Next, based on the fluid parameter types included in the fluid parameters to be analyzed, the current pressure gradient estimate is converted into a first estimate gradient for each fluid parameter type, thus proceeding to step S140.

[0057] Furthermore, in step S140 of this embodiment of the invention, firstly, based on the (small amount) of bottom hole fluid samples collected at the current stage, laboratory experiments are conducted on the fluid samples to obtain corresponding fluid parameter measurement data based on the laboratory experiments (bottom hole fluid sample data). Then, through the production profile testing and interpretation described in step S110, production profile interpretation result data is obtained (production profile interpretation data, see reference). Figure 5 This allows us to obtain all the data required for the current fluid parameter calculation scheme.

[0058] In this embodiment of the invention, it is necessary to perform production profile PLT interpretation on the target reservoir. Using the PLT test results, the actual production volume of each layer and the fluid flow rate value and various fluid parameters corresponding to each interpretation measurement point based on PLT decomposition are interpreted, thereby improving the accuracy of subsequent fluid parameter prediction. The PLT interpretation should be as detailed and accurate as possible.

[0059] Next, the fluid parameter measurement data corresponding to the fluid sample at the deepest bottom of the well is used as the starting data. Combined with the production profile interpretation results and one or more first estimation gradients obtained in step S130 above, a gradient iteration method is used to calculate the vertical distribution data corresponding to each fluid parameter to be analyzed. Specifically, in this embodiment of the invention, the vertical distribution data is calculated by taking the vertical depth corresponding to the deepest part of the sample as the starting point and the vertical depth closest to the ground in the well section to be analyzed as the ending point. The well section to be analyzed is decomposed into PLT, and the fluid parameter value of each PLT interpretation point (of the corresponding type) calculated based on the first estimation gradient is calculated. The well section to be analyzed is divided into several unit well sections with the same vertical depth according to the preset PLT interpretation accuracy. The breakpoints of each unit well section form a sequence of PLT interpretation points arranged from bottom to top, where the 0th interpretation point is the starting point and the nth interpretation point is the ending point.

[0060] Furthermore, the vertical distribution data corresponding to each fluid parameter to be calculated is calculated using the following expression:

[0061]

[0062] Where i represents the sequence number of each vertical interpretation measurement point within the well section to be analyzed, n represents the total number of interpretation measurement points, and M represents the total number of measurement points. PLT(i) M PLT(n) Q represents the fluid parameter (measurement) value (of the corresponding type) under PLT decomposition corresponding to the i-th and n-th interpretation measurement points, respectively. PLT(i) Q PLT(n) D represents the fluid flow rate values ​​corresponding to the i-th and n-th interpretation measurement points under PLT decomposition (this parameter is obtained from the product profile interpretation results data). n Dn-1 G represents the vertical depth corresponding to the i-th and n-th interpretation measurement points, respectively. est M represents the first estimated gradient. Grad(n-1) This represents the iterative (measured) value of the fluid parameter (of the corresponding type) under the PLT decomposition corresponding to the (n-1)th interpretation measurement point. Therefore, based on the fluid parameter data calculated according to the first estimation gradient of the corresponding type for each measurement point, and combined with the product profile interpretation results, the fluid parameter values ​​of the corresponding type under the PLT decomposition for each interpretation measurement point can be calculated sequentially from bottom to top, starting from the starting point.

[0063] For example, when the fluid parameter to be analyzed is fluid density, it is necessary to calculate the vertical distribution data of PLT fluid density. In this case, the fluid sample data at the deepest bottom of the well should be selected as the starting point, and the intuitive fluid density gradient should be used as the first gradient estimate of PLT fluid density gradient. The vertical distribution data of PLT fluid density should then be calculated point by point from bottom to top using the following formula:

[0064]

[0065] Where, ρ PLT(i) ρ PLT(n) ρ represents the fluid density (measured) value under PLT decomposition corresponding to the i-th and n-th interpretation measurement points, respectively. Grad(n-1) This represents the iterative measurement value of fluid density under PLT decomposition corresponding to the (n-1)th interpretation measurement point.

[0066] To ensure the accuracy of the calculated vertical distribution data corresponding to each type of fluid parameter to be analyzed, the fluid parameter calculation method described in this embodiment of the invention also detects whether the first estimation gradient required to calculate the vertical distribution data corresponding to each type of fluid parameter to be analyzed needs to be adjusted. Specifically, the vertical distribution data of the current (type) fluid parameter to be analyzed is linearly fitted to form the vertical distribution change curve of the corresponding type. Then, the actual value of the fluid parameter to be analyzed at the corresponding depth is calculated based on the collected bottom oil sample. Finally, the actual value of the currently calculated fluid parameter to be analyzed is compared with the fitted curve (i.e., the vertical distribution change curve) corresponding to the vertical distribution data to determine whether the first estimation gradient required to calculate the current type of fluid parameter to be analyzed needs to be adjusted, thereby matching the calculation accuracy of the first estimation gradient corresponding to the corresponding fluid parameter with the measurement accuracy of the interpretation measurement point corresponding to the PLT decomposition.

[0067] Specifically, when comparing the actual values ​​with the vertical distribution variation curves, the accuracy of adjacent interpretation measurement points obtained based on PLT decomposition is evaluated to see if it meets the accuracy requirements of the actual values. If not, the first estimation gradient is adjusted. Conversely, if it does meet the requirements, the vertical distribution data of the currently obtained fluid parameter to be analyzed is directly used as the final calculation result, thereby forming the vertical distribution law of fluid parameters using the vertical distribution data corresponding to each fluid parameter to be analyzed.

[0068] Finally, in order to verify the accuracy and gradual regularity of the vertical distribution data corresponding to each fluid parameter to be analyzed obtained in step S140, the fluid parameter calculation method of the present invention further includes verifying the vertical distribution law of the fluid parameters formed above.

[0069] Specifically, when verifying the vertical distribution law of fluid parameters, firstly, laboratory experiments are needed on a sufficient number of bottom-hole oil samples collected in subsequent stages to obtain measured data of various fluid parameters generated from the laboratory experiments (for example, measured data of fluid density variation distribution, dissolved gas-oil ratio variation distribution, and volume coefficient variation distribution, respectively). Then, the measured data of the various fluid parameter variation distributions are compared with the vertical distribution data of the fluid parameters to be analyzed obtained in step S140, according to the same type of fluid parameters, to verify the calculation results of the vertical gradual change of fluid properties.

[0070] For example, the following correlation can be satisfied between the variation distribution data of various fluid parameters obtained from indoor experiments:

[0071] ρ i =(ρ soil +R S(i) *ρ sgas ) / FVF i (3)

[0072] Where, ρ i ρ represents the fluid density at the i-th measurement point, obtained from indoor experiments. soil R represents the crude oil density obtained from indoor experiments. S(i) ρ represents the dissolved gas-oil ratio at the i-th measuring point, obtained from indoor experiments. sgas FVF represents the gas density obtained from indoor experiments. iThis represents the volume factor for the i-th measuring point, obtained based on indoor experiments. Thus, by comparing the variation patterns of the vertical distribution data of fluid density obtained in step S140 with the fluid density variation trends of all measuring points obtained from indoor experiments, comparing the variation patterns of the vertical distribution data of the dissolved gas-oil ratio obtained in step S140 with the fluid dissolved gas-oil ratio variation trends of all measuring points obtained from indoor experiments, and comparing the variation patterns of the vertical distribution data of the fluid volume factor obtained in step S140 with the fluid volume factor variation trends of all measuring points obtained from indoor experiments, the verification of the patterns in the vertical distribution data of the fluid parameters to be analyzed is completed.

[0073] The following example uses the rapid calculation of fluid parameters in well C-01, the first exploratory well in an offshore C oilfield. The specific process of the fluid parameter calculation method described in this embodiment of the invention is explained below:

[0074] C oilfield is an ultra-deepwater reservoir with a reservoir thickness of 150-220 meters and obvious fluid gravity differentiation.

[0075] Due to the high cost of ultra-deepwater drilling and various sampling operations, only 3 wells were drilled in the region during the oilfield evaluation phase. One of them was a dry well, and the remaining 2 were distributed in the north and south regions. However, the north and south regions belong to different oil-water systems, and the fluid properties are also quite different.

[0076] Well C-01, the first exploratory well in the oilfield, is located in the southern region. Although routine pressure and production profile tests were conducted, only three bottom-hole oil samples were collected during the testing process, and only preliminary fluid analysis was performed. Figure 3 ( Figure 3 This is a schematic diagram illustrating the effect of conventional pressure data in the method for calculating fluid parameters of thick, light oil reservoirs according to embodiments of this application, specifically for the C oilfield example. Figure 4 ( Figure 4 This is a schematic diagram of the pressure curve effect for an example of oilfield C in the method for calculating fluid parameters of thick, light oil reservoirs according to embodiments of this application. Figure 5 ( Figure 5 (This is a schematic diagram of the production profile test interpretation results for the C oilfield example in the method for calculating fluid parameters of thick light oil reservoirs according to the embodiments of this application) respectively shows the conventional pressure data, pressure curve and production profile test interpretation results of the C oilfield.

[0077] Furthermore, Table 1 shows the measured values ​​of parameters for the three bottom fluid samples collected from well C-01 (bottom fluid sample data).

[0078] Table 1 Bottomhole fluid sample data from Well C-01

[0079]

[0080]

[0081] in, Figure 3 , Figure 4 and Figure 5 The diagrams show the generation effects of conventional pressure data, pressure curves, and production profile test interpretation results for oilfield C.

[0082] Due to the large reservoir thickness, severe gravity differentiation of fluid components, and a lack of sufficient formation fluid samples and detailed laboratory experimental data, we can only rapidly calculate the vertical distribution data of various fluid parameters to be analyzed, including dissolved gas-oil ratio, API content, C1 content, C7+ content, and fluid density, by integrating various production test data. Furthermore, for the current target C oilfield area, a new well, C-05, was drilled in the subsequent stage, obtaining corresponding bottom-hole fluid samples, thus forming a sufficient number of samples and laboratory experimental data. This led to the generation of measured data on the distribution characteristics of dissolved gas-oil ratio, API content, C1 content, C7+ content, and fluid density based on laboratory experiments. Figure 6 ( Figure 6 This is a schematic diagram comparing the calculated fluid gas-oil ratio with the measured value of the sample in the method for calculating fluid parameters of thick light oil reservoirs according to an embodiment of this application, specifically for the C oilfield example. Figure 7 ( Figure 7 This is a schematic diagram comparing the calculated API values ​​with the measured values ​​of the sample in the method for calculating fluid parameters in thick, light oil reservoirs according to an embodiment of this application, specifically for the C oilfield example. Figure 8 ( Figure 8 This is a schematic diagram comparing the calculated C1 content with the measured sample value in the method for calculating fluid parameters of thick, light oil reservoirs according to an embodiment of this application, specifically for the C oilfield example. Figure 9 ( Figure 9 This is a schematic diagram comparing the calculated C7+ content with the measured sample value in the method for calculating fluid parameters of thick, light oil reservoirs according to embodiments of this application, specifically for the C oilfield example. Figure 10 ( Figure 10 This is a schematic diagram showing the comparison between the calculated values ​​of fluid density and the measured values ​​of the sample in the method for calculating fluid parameters of thick light oil reservoirs according to embodiments of this application, specifically for oilfield C. The diagrams illustrate the comparison between the calculated values ​​of the vertical distribution characteristics of the fluid gas-oil ratio, API vertical distribution characteristics, C1 content vertical distribution characteristics, C7+ content vertical distribution characteristics, and fluid density vertical distribution characteristics calculated using the method described in this embodiment of the invention, and the measured data for the corresponding fluid categories.

[0083] Furthermore, Table 2 shows a comparison between the predicted fluid parameters and the measured data from well C-05.

[0084] Table 2 compares the predicted fluid parameters with the measured data from well C-05.

[0085]

[0086]

[0087] The method used in this invention has been well applied in the current C oilfield, providing data support for subsequent fluid modeling, geological reserve estimation, and development index prediction. It was also well validated in the new well C-05 drilled three years later, with a prediction accuracy of less than 5%.

[0088] On the other hand, based on the above-mentioned fluid parameter calculation method, this embodiment of the invention also provides a system for calculating fluid parameters of thick light oil reservoirs (hereinafter referred to as "fluid parameter calculation system"). Figure 11 This is a schematic diagram of a system module for calculating fluid parameters in thick, light oil reservoirs, according to an embodiment of this application. Figure 11 As shown, the fluid parameter calculation system of this embodiment includes: a pressure curve plotting module 1101, a gravity differentiation evaluation module 1102, a fluid parameter gradient generation module 1103, and a vertical distribution feature generation module 1104.

[0089] Specifically, the pressure curve plotting module 1101 is implemented according to the method described in step S110 above, configured to perform conventional pressure tests and production profile tests on the target reservoir, and create a pressure curve that varies with depth; the gravity differentiation evaluation module 1102 is implemented according to the method described in step S120 above, configured to determine whether the influence of gravity differentiation on fluid properties reaches a preset level based on the pressure curve; the fluid parameter gradient generation module 1103 is implemented according to the method described in step S130 above, configured to calculate the pressure gradient estimate based on the pressure curve, and further calculate the first estimated gradient corresponding to the fluid parameter to be analyzed; the vertical distribution feature generation module 1104 is implemented according to the method described in step S140 above, configured to select the fluid sample at the deepest bottom of the well and conduct indoor experiments to obtain the corresponding fluid parameter starting data, and then combine the production profile interpretation results and the first estimated gradient, using a gradient iteration method to calculate the vertical distribution data of the fluid parameter to be analyzed.

[0090] In this embodiment of the invention, the fluid parameters to be analyzed include, but are not limited to, one or more of the following: fluid density, API, fluid viscosity, fluid gas-oil ratio, volume factor, and molar content of pseudo-components.

[0091] This invention discloses a method and system for calculating fluid parameters in thick, light oil reservoirs. When the number of effective oil and gas samples is limited or laboratory analysis data is scarce, this method and system utilizes conventional pressure data and a small amount of sample analysis data, combined with production profile testing (PLT) interpretation results. Starting with analysis of highly reliable bottomhole fluid samples, PLT iterative decomposition transforms the data into changes in fluid density and other fluid parameters, effectively predicting the vertical distribution of fluid components. Thus, this invention provides a rapid scheme for calculating the vertical distribution of fluid parameters in thick, light oil reservoirs under the influence of gravity differentiation, achieving a prediction accuracy of within 5%, effectively reducing development risks. Furthermore, this invention can also be applied to ordinary light oil reservoirs with large reservoir thicknesses, where gravity differentiation has a certain impact on the vertical distribution of fluids. However, when the number of effective oil and gas samples is limited, the reliability of sample data is insufficient, formation pressure test data is scarce, or time is limited and experimental data is insufficient, making it difficult to directly obtain the vertical component distribution of fluids, this invention enables the prediction of fluid property changes with depth. This not only improves the calculation accuracy of the vertical distribution of fluids but also reduces the uncertainty risk of fluid prediction.

[0092] 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 variations or substitutions that can be easily conceived by those 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 determined by the scope of the claims.

[0093] It should be understood that the embodiments disclosed herein are not limited to the specific structures, processing steps, or materials disclosed herein, but should be extended to equivalent substitutions of these features as understood by those skilled in the art. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

[0094] The phrase "an embodiment" or "an embodiment" used in this specification means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Therefore, the phrase "an embodiment" or "an embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment.

[0095] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection of this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A method for calculating fluid parameters in thick, light oil reservoirs, comprising: Conventional pressure tests and production profile tests were conducted on the target reservoir, and pressure curves as a function of depth were created. Based on the pressure curve, determine whether the degree of influence of gravity differentiation on fluid properties reaches the preset level; Calculate the pressure gradient estimate based on the pressure curve, and further calculate the first estimated gradient corresponding to the current fluid parameter to be analyzed. The fluid sample at the deepest well bottom is selected and subjected to laboratory experiments to obtain the corresponding starting data of fluid parameters. Then, combined with the interpretation results of the produced fluid profile and the first estimated gradient, the gradient iteration method is used to calculate the vertical distribution data of the fluid parameters to be analyzed. The vertical distribution data of the fluid parameters to be analyzed is calculated using the following expression: in, i Indicates the serial number of each vertical interpretation measurement point. n This indicates the total number of measurement points to be interpreted. , They represent the first i The, the n Explain the fluid parameter values ​​corresponding to each measurement point. , They represent the first i The, the n Explain the fluid flow rate value corresponding to each measurement point. , They represent the first n The, the n -1 explanation of the vertical depth corresponding to the measuring point This represents the first estimated gradient. Indicates the first n -1 interprets the iterative measurement values ​​of fluid parameters corresponding to the measurement points.

2. The method according to claim 1, characterized in that, The method further includes: Fit the vertical distribution data of the current fluid parameters to be analyzed; Calculate the actual values ​​of the fluid parameters to be analyzed at the corresponding depth based on the collected bottom oil samples; The actual values ​​of the fluid parameters to be analyzed are compared with the fitted curves corresponding to the vertical distribution data to determine whether the first estimated gradient needs to be adjusted.

3. The method according to claim 1 or 2, characterized in that, The parameters of the fluid to be analyzed include, but are not limited to, one or more of the following: fluid density, API, fluid viscosity, fluid gas-oil ratio, volume factor, and molar content of the pseudo-component.

4. The method according to claim 1 or 2, characterized in that, The step of determining whether the influence of gravity differentiation on fluid properties reaches a preset level based on the pressure curve includes: Based on the pressure curve, plot the overpressure curve as a function of depth; Based on the overpressure curve, the characteristics of fluid density and composition changes are identified, and the degree of influence of gravity differentiation on the fluid properties of the target reservoir is determined.

5. The method according to claim 1 or 2, characterized in that, The step of calculating the pressure gradient estimate based on the pressure curve includes: The pressure curve was subjected to linear regression fitting to obtain the corresponding expression; The pressure gradient estimate is determined based on the expression corresponding to the pressure curve.

6. The method according to claim 1 or 2, characterized in that, The steps for creating a pressure profile that varies with depth include: Obtain existing pressure data for the target reservoir, verify the quality and reliability of the existing pressure data, and select representative pressure data. The pressure curve is constructed based on verified pressure data.

7. The method according to claim 1 or 2, characterized in that, The method further includes: Indoor experiments were conducted on the collected bottom oil samples to obtain measured data of various fluid parameters based on the indoor experiments; The measured data of the various fluid parameters are compared with the vertical distribution data of the fluid parameters to be analyzed to verify the calculation results of the vertical gradual change of fluid properties.

8. A system for calculating fluid parameters in thick, light oil reservoirs, comprising: The pressure curve plotting module is configured to perform conventional pressure tests and production profile tests on the target reservoir and create pressure curves that vary with depth. The gravity differentiation evaluation module is configured to determine, based on the pressure curve, whether the degree of influence of gravity differentiation on fluid properties reaches a preset level. The fluid parameter gradient generation module is configured to calculate the pressure gradient estimate based on the pressure curve, and further calculate the first estimated gradient corresponding to the current fluid parameter to be analyzed. The vertical distribution feature generation module is configured to select the fluid sample at the deepest well bottom and conduct laboratory experiments to obtain the corresponding fluid parameter starting data. Then, combining the production profile interpretation results and the first estimated gradient, a gradient iteration method is used to calculate the vertical distribution data of the fluid parameter to be analyzed. The vertical distribution data of the fluid parameter to be analyzed is calculated using the following expression: in, i Indicates the serial number of each vertical interpretation measurement point. n This indicates the total number of measurement points to be interpreted. , They represent the first i The, the n Explain the fluid parameter values ​​corresponding to each measurement point. , They represent the first i The, the n Explain the fluid flow rate value corresponding to each measurement point. , They represent the first n The, the n -1 explanation of the vertical depth corresponding to the measuring point This represents the first estimated gradient. Indicates the first n -1 interprets the iterative measurement values ​​of fluid parameters corresponding to the measurement points.

9. The system according to claim 8, characterized in that, The parameters of the fluid to be analyzed include, but are not limited to, one or more of the following: fluid density, API, fluid viscosity, fluid gas-oil ratio, volume factor, and molar content of the pseudo-component.

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