A method for quantitatively characterizing the predicted deep formation water chloride content

Abstract

The application discloses a method for quantitatively characterizing and predicting deep formation water chloride content, and relates to the technical field of exploration and development of deep-ultra deep tight sandstone gas reservoirs; the method comprises the following steps: recovering burial history and thermal evolution history of the target layer; quantitatively characterizing water-rock reaction intensity; quantitatively characterizing and evaluating evolution process of formation water chloride content; recovering burial history and thermal evolution history of the target layer comprises the following steps: stratifying the formation by using multiple data means; in combination with formation tectonic movement background, recovering denudation thickness and denudation time by using formation trend line method. The application can accurately and rapidly quantitatively characterize and evaluate the evolution process of deep-ultra deep formation water chloride content by analyzing formation burial process, thermal evolution history and formation water conventional geochemical data and the like. The analysis process is simple and easy to realize, and the required data are less, so that the application is a quick method capable of quantitatively analyzing formation water properties in different periods.

Description

Technical Field

[0001] This invention relates to the field of exploration and development technology for deep-ultra-deep tight sandstone gas reservoirs, specifically to a method for quantitatively characterizing and predicting chloride content in deep formation water. Background Technology

[0002] Deep to ultra-deep gas reservoirs are one of the most important oil and gas exploration areas in my country now and in the future. However, as exploration and development progress, most gas wells have begun to exhibit water production characteristics, and the nature of this water production is highly complex, with variations in the salinity and chloride content of formation water from different wells. The chloride content of deep to ultra-deep formation water is significantly higher than that of shallow formation water, and it is a major controlling factor for salinity and a key indicator for determining the type of water produced by gas wells. Therefore, the differences in the water production characteristics of different gas wells greatly increase the difficulty for researchers in determining the type of formation water, thus making gas reservoirs susceptible to water intrusion. Quantitatively characterizing the evolution and causes of chloride content in formation water is of great significance for timely optimization of extraction measures and improvement of oil and gas recovery rates.

[0003] Generally, deep formation water in sedimentary basins mainly includes primary sedimentary water, diagenetic water, and atmospheric precipitation. The chloride content of formation water is primarily controlled by the degree of reaction between pore fluids and rocks during sedimentation and burial (water-rock reaction) and the flow of pore fluids. Water-rock reaction is a process that occurs throughout the evolution of formation water in all regions and is a crucial factor influencing its properties; however, the extent of this reaction is currently primarily described qualitatively. The flow of pore fluids ensures the continuity of the water-rock reaction and is the main controlling factor for its intensity, as well as the fundamental reason for differences in chloride content in formation water across different well areas. Water-rock reaction is an ongoing diagenetic process closely related to the burial depth and temperature of the formation. Differences in chloride content in formation water across different well areas reflect variations in the water-rock reaction process, indicating different sedimentary burial and paleothermal evolution processes. Therefore, the burial process and temperature evolution history of the formation are key to studying the intensity of the water-rock reaction. Quantitative characterization and evaluation of the evolution of chloride content in formation water in different well areas are of great significance for accurately determining the water production type of gas wells, optimizing production measures, and improving oil and gas recovery. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method for quantitatively characterizing and predicting chloride content in deep formation water.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A method for quantitatively characterizing and predicting chloride content in deep formation water includes the following steps:

[0007] S1: Reconstruct the burial history and thermal evolution history of the target layer;

[0008] S2: Quantitative characterization of water-rock reaction intensity;

[0009] S3: Quantitative characterization and differential evaluation of the evolution process of chloride content in formation water.

[0010] Preferably, step S1 includes the following steps:

[0011] S11: Use multiple data methods to divide the strata into layers;

[0012] S12: Based on the background of stratigraphic tectonic movement, the stratigraphic trend line method is used to reconstruct the erosion thickness and erosion time;

[0013] S13: Reconstruct paleotemperature based on the correspondence between geothermal gradient, measured temperature, and vitrinite reflectivity.

[0014] Preferably, in step S11, the layered approach employs well logging lithology, well logging curves, well coring, and seismic exploration methods.

[0015] Preferably, step S2 includes the following steps:

[0016] S21: First, based on the burial history and thermal evolution history data, the burial time and temperature experienced by the target layer are divided into intervals with the temperature gradient as an example;

[0017] S22: Then, each temperature range is further divided into equal-interval, detailed sections;

[0018] S23: Finally, sum up the product of each small temperature range and the time elapsed;

[0019] S24: Using Matlab software, the burial depth and corresponding geological time of the target layer are first digitally read at equal intervals to obtain the functional relationship between depth and time;

[0020] S25: Then continue to extract burial depth and paleotemperature data at equal intervals to obtain the functional relationship between burial depth and paleotemperature;

[0021] S26: Finally, the burial time and paleotemperature data are extracted digitally at equal intervals to obtain the functional relationship between burial time and paleotemperature.

[0022] Preferably, in step S21, the temperature gradient is 10°C.

[0023] Preferably, in step S22, each temperature range is further divided into n smaller ranges at 1°C intervals.

[0024] Preferably, in step S22, n = 10.

[0025] The beneficial effects of this invention are reflected in:

[0026] 1. This invention enables precise and rapid quantitative characterization and evaluation of the evolution of chloride content in deep to ultra-deep formation water by analyzing data such as burial processes, thermal evolution history, and conventional geochemical data of formation water. The analysis process is simple and easy to implement, requiring relatively little data, and is a rapid method for quantitatively analyzing the properties of formation water at different stages. Attached Figure Description

[0027] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0028] Figure 1 This is a flowchart of a method for quantitatively characterizing and predicting chloride content in deep formation water proposed in this invention;

[0029] Figure 2 This is a flowchart illustrating the process of reconstructing the burial history and thermal evolution history of the target layer using a method for quantitatively characterizing and predicting chloride content in deep formation water, as proposed in this invention.

[0030] Figure 3 This is a flowchart illustrating the quantitative characterization of water-rock reaction intensity, a method for quantitatively characterizing and predicting chloride content in deep formation water proposed in this invention. Detailed Implementation

[0031] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are merely illustrative of the technical solution of the present invention and are therefore intended to limit the scope of protection of the present invention.

[0032] It should be noted that, unless otherwise stated, the technical or scientific terms used in this application should have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0033] Example 1:

[0034] A method for quantitatively characterizing and predicting chloride content in deep formation water includes the following steps:

[0035] S1: Reconstruct the burial history and thermal evolution history of the target layer;

[0036] S2: Quantitative characterization of water-rock reaction intensity;

[0037] S3: Quantitative characterization and differential evaluation of the evolution process of chloride content in formation water.

[0038] Step S1 includes the following steps:

[0039] S11: Use multiple data methods to divide the strata into layers;

[0040] S12: Based on the background of stratigraphic tectonic movement, the stratigraphic trend line method is used to reconstruct the erosion thickness and erosion time;

[0041] S13: Reconstruct paleotemperature based on the correspondence between geothermal gradient, measured temperature, and vitrinite reflectivity.

[0042] In step S11, well logging lithology, well logging curves, drilling coring, and seismic exploration methods are used in layers.

[0043] Example 2:

[0044] A method for quantitatively characterizing and predicting chloride content in deep formation water includes the following steps:

[0045] S1: Reconstruct the burial history and thermal evolution history of the target layer;

[0046] S2: Quantitative characterization of water-rock reaction intensity;

[0047] S3: Quantitative characterization and differential evaluation of the evolution process of chloride content in formation water.

[0048] Step S1 includes the following steps:

[0049] S11: Use multiple data methods to divide the strata into layers;

[0050] S12: Based on the background of stratigraphic tectonic movement, the stratigraphic trend line method is used to reconstruct the erosion thickness and erosion time;

[0051] S13: Reconstruct paleotemperature based on the correspondence between geothermal gradient, measured temperature, and vitrinite reflectivity.

[0052] In step S11, well logging lithology, well logging curves, drilling coring, and seismic exploration methods are used in layers.

[0053] Step S2 includes the following steps:

[0054] S21: First, based on the burial history and thermal evolution history data, the burial time and temperature experienced by the target layer are divided into intervals with the temperature gradient as an example;

[0055] S22: Then, each temperature range is further divided into equal-interval, detailed sections;

[0056] S23: Finally, sum up the product of each small temperature range and the time elapsed;

[0057] S24: Using Matlab software, the burial depth and corresponding geological time of the target layer are first digitally read at equal intervals to obtain the functional relationship between depth and time;

[0058] S25: Then continue to extract burial depth and paleotemperature data at equal intervals to obtain the functional relationship between burial depth and paleotemperature;

[0059] S26: Finally, the burial time and paleotemperature data are extracted digitally at equal intervals to obtain the functional relationship between burial time and paleotemperature.

[0060] Example 3:

[0061] A method for quantitatively characterizing and predicting chloride content in deep formation water includes the following steps:

[0062] S1: Reconstruct the burial history and thermal evolution history of the target layer;

[0063] S2: Quantitative characterization of water-rock reaction intensity;

[0064] S3: Quantitative characterization and differential evaluation of the evolution process of chloride content in formation water.

[0065] Step S1 includes the following steps:

[0066] S11: Use multiple data methods to divide the strata into layers;

[0067] S12: Based on the background of stratigraphic tectonic movement, the stratigraphic trend line method is used to reconstruct the erosion thickness and erosion time;

[0068] S13: Reconstruct paleotemperature based on the correspondence between geothermal gradient, measured temperature, and vitrinite reflectivity.

[0069] In step S11, well logging lithology, well logging curves, drilling coring, and seismic exploration methods are used in layers.

[0070] Step S2 includes the following steps:

[0071] S21: First, based on the burial history and thermal evolution history data, the burial time and temperature experienced by the target layer are divided into intervals with the temperature gradient as an example;

[0072] S22: Then, each temperature range is further divided into equal-interval, detailed sections;

[0073] S23: Finally, sum up the product of each small temperature range and the time elapsed;

[0074] S24: Using Matlab software, the burial depth and corresponding geological time of the target layer are first digitally read at equal intervals to obtain the functional relationship between depth and time;

[0075] S25: Then continue to extract burial depth and paleotemperature data at equal intervals to obtain the functional relationship between burial depth and paleotemperature;

[0076] S26: Finally, the burial time and paleotemperature data are extracted digitally at equal intervals to obtain the functional relationship between burial time and paleotemperature.

[0077] In step S21, the temperature gradient is 10°C.

[0078] Example 4:

[0079] A method for quantitatively characterizing and predicting chloride content in deep formation water includes the following steps:

[0080] S1: Reconstruct the burial history and thermal evolution history of the target layer;

[0081] S2: Quantitative characterization of water-rock reaction intensity;

[0082] S3: Quantitative characterization and differential evaluation of the evolution process of chloride content in formation water.

[0083] Step S1 includes the following steps:

[0084] S11: Use multiple data methods to divide the strata into layers;

[0085] S12: Based on the background of stratigraphic tectonic movement, the stratigraphic trend line method is used to reconstruct the erosion thickness and erosion time;

[0086] S13: Reconstruct paleotemperature based on the correspondence between geothermal gradient, measured temperature, and vitrinite reflectivity.

[0087] In step S11, well logging lithology, well logging curves, drilling coring, and seismic exploration methods are used in layers.

[0088] Step S2 includes the following steps:

[0089] S21: First, based on the burial history and thermal evolution history data, the burial time and temperature experienced by the target layer are divided into intervals with the temperature gradient as an example;

[0090] S22: Then, each temperature range is further divided into equal-interval, detailed sections;

[0091] S23: Finally, sum up the product of each small temperature range and the time elapsed;

[0092] S24: Using Matlab software, the burial depth and corresponding geological time of the target layer are first digitally read at equal intervals to obtain the functional relationship between depth and time;

[0093] S25: Then continue to extract burial depth and paleotemperature data at equal intervals to obtain the functional relationship between burial depth and paleotemperature;

[0094] S26: Finally, the burial time and paleotemperature data are extracted digitally at equal intervals to obtain the functional relationship between burial time and paleotemperature.

[0095] In step S21, the temperature gradient is 10°C.

[0096] In step S22, each temperature range is further divided into n smaller ranges at 1°C intervals.

[0097] Example 5:

[0098] A method for quantitatively characterizing and predicting chloride content in deep formation water includes the following steps:

[0099] S1: Reconstruct the burial history and thermal evolution history of the target layer;

[0100] S2: Quantitative characterization of water-rock reaction intensity;

[0101] S3: Quantitative characterization and differential evaluation of the evolution process of chloride content in formation water.

[0102] Step S1 includes the following steps:

[0103] S11: Use multiple data methods to divide the strata into layers;

[0104] S12: Based on the background of stratigraphic tectonic movement, the stratigraphic trend line method is used to reconstruct the erosion thickness and erosion time;

[0105] S13: Reconstruct paleotemperature based on the correspondence between geothermal gradient, measured temperature, and vitrinite reflectivity.

[0106] In step S11, well logging lithology, well logging curves, drilling coring, and seismic exploration methods are used in layers.

[0107] Step S2 includes the following steps:

[0108] S21: First, based on the burial history and thermal evolution history data, the burial time and temperature experienced by the target layer are divided into intervals with the temperature gradient as an example;

[0109] S22: Then, each temperature range is further divided into equal-interval, detailed sections;

[0110] S23: Finally, sum up the product of each small temperature range and the time elapsed;

[0111] S24: Using Matlab software, the burial depth and corresponding geological time of the target layer are first digitally read at equal intervals to obtain the functional relationship between depth and time;

[0112] S25: Then continue to extract burial depth and paleotemperature data at equal intervals to obtain the functional relationship between burial depth and paleotemperature;

[0113] S26: Finally, the burial time and paleotemperature data are extracted digitally at equal intervals to obtain the functional relationship between burial time and paleotemperature.

[0114] In step S21, the temperature gradient is 10°C.

[0115] In step S22, each temperature range is further divided into n smaller ranges at 1°C intervals.

[0116] In step S22, n = 10.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for quantitatively characterizing and predicting chloride content in deep formation water, characterized in that: Includes the following steps: S1: Reconstruct the burial history and thermal evolution history of the target layer; S2: Quantitative characterization of water-rock reaction intensity; S3: Quantitative characterization and differential evaluation of the evolution process of chloride content in formation water; Step S1 includes the following steps: S11: Use multiple data methods to divide the strata into layers; S12: Based on the background of stratigraphic tectonic movement, the stratigraphic trend line method is used to reconstruct the erosion thickness and erosion time; S13: Reconstruct paleothermal temperature based on the correlation between geothermal gradient, measured temperature, and vitrinite reflectivity; Step S2 includes the following steps: S21: First, based on the burial history and thermal evolution history data, the burial time and temperature experienced by the target layer are divided into intervals with the temperature gradient as an example; S22: Then, each temperature range is further divided into equal-interval, detailed sections; S23: Finally, sum up the product of each small temperature range and the time elapsed; S24: Using Matlab software, the burial depth and corresponding geological time of the target layer are first digitally read at equal intervals to obtain the functional relationship between depth and time; S25: Then continue to extract burial depth and paleotemperature data at equal intervals to obtain the functional relationship between burial depth and paleotemperature; S26: Finally, the burial time and paleotemperature data are extracted digitally at equal intervals to obtain the functional relationship between burial time and paleotemperature. In step S21, the temperature gradient is 10°C; In step S22, each temperature range is further divided into n smaller ranges with an interval of 1℃. In step S22, n=10.

2. The method for quantitatively characterizing and predicting chloride content in deep formation water according to claim 1, characterized in that, In step S11, well logging lithology, well logging curves, drilling coring, and seismic exploration methods are used in layers.

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