A wellbore environment correction method, system, device and medium

Abstract

This application discloses a method, system, device, and medium for wellbore environment correction in well logging. The method includes the following steps: obtaining the initial formation density, wellbore collapse depth, clay content and density, short and long source distance detection depths, mud density, rock skeleton density, pore fluid density, and porosity; determining the density response parameters of the long source distance detector based on the long source distance detection depth, wellbore collapse depth, mud density, rock skeleton density, pore fluid density, and porosity; determining the density response parameters of the short source distance detector based on the short source distance detection depth, wellbore collapse depth, mud density, rock skeleton density, pore fluid density, and porosity; determining the pure formation density based on the long source distance detection depth, short source distance detection depth, and the two density response parameters; and determining the corrected formation density based on the initial formation density, clay content, clay density, and pure formation density. This application can be widely applied in the field of drilling measurement technology.

Description

Technical Field

[0001] This application relates to the field of drilling measurement technology, and in particular to a wellbore environment correction method, system, device and storage medium. Background Technology

[0002] Density curves are essential elastic parameters for seismic inversion and rock physics modeling. However, due to environmental factors such as wellbore enlargement, density logging values ​​are often abnormally low in enlarged well sections. To correct for the influence of the wellbore on density logging curves, current technologies primarily measure formation density and calculate formation porosity, using these two parameters to correct the logging curves. However, as the wellbore enlarges or the wellbore changes, the density logging curve also changes, often causing a sharp drop, resulting in relatively low accuracy of the measured formation density values. Therefore, there are still technical problems that need to be solved in related technologies. Summary of the Invention

[0003] The purpose of this application is to at least partially solve one of the technical problems existing in the prior art.

[0004] Therefore, one objective of the embodiments of this application is to provide a logging wellbore environment correction method, system, device and storage medium, which can improve accuracy.

[0005] To achieve the aforementioned technical objectives, the technical solution adopted in this application includes: a wellbore environment correction method, comprising acquiring the initial formation density, wellbore collapse depth, clay content, clay density, short-spacing detection depth, long-spacing detection depth, logging mud density, rock skeleton density, pore fluid density of the uncollapsed portion of the formation within the wellbore, and porosity of the uncollapsed portion of the formation within the wellbore; and determining the long-spacing detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity based on the long-spacing detection depth, the logging mud depth, the rock skeleton density, the pore fluid density, and the porosity. The detector's first density response parameter; the second density response parameter of the short-spacing detector determined based on the short-spacing detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity; the pure formation density with the highest porosity in the interpretation interval determined based on the long-spacing detection depth, the short-spacing detection depth, the first density response parameter, and the second density response parameter; and the corrected target formation density determined based on the initial formation density, the clay content, the clay density, and the pure formation density.

[0006] In addition, the well logging environment correction method according to the above embodiments of the present invention may also have the following additional technical features:

[0007] Furthermore, in this embodiment of the application, the step of determining the corrected target formation density based on the initial formation density, the clay content, the clay density, and the pure formation density specifically includes: determining a first formation density based on the initial formation density, the clay content, the clay density, and the pure formation density; and determining the target formation density based on the initial formation density and the first formation density.

[0008] Further, in this embodiment of the application, the step of determining the first formation density based on the initial formation density, the clay content, the clay density, and the pure formation density specifically includes: inputting the initial formation density, the clay content, the clay density, and the pure formation density into a preset formation density determination formula to determine the first formation density; wherein the formation density determination formula is:

[0009] DEN min =V sh *DEN sh +(1-V sh *ρ b )*DEN

[0010] DEN min V is the density of the first formation. sh DEN is the clay content. sh ρ is the density of clay, DEN is the initial formation density, and ρ is the density of clay. b This represents the density of the pure formation.

[0011] Furthermore, in this embodiment of the application, the step of determining the target formation density based on the initial formation density and the first formation density specifically includes: determining the magnitude relationship between the initial formation density and the first formation density; when the initial formation density is greater than or equal to the first formation density, using the initial formation density as the target formation density; when the initial formation density is less than the first formation density, using the first formation density as the target formation density.

[0012] Furthermore, in this embodiment of the application, the step of determining the first density response parameter of the long-source-distance detector based on the long-source-distance detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity specifically includes: inputting the long-source-distance detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity into a preset first density response parameter calculation formula to determine the first density response parameter of the long-source-distance detector;

[0013] The formula for calculating the first density response parameter includes:

[0014]

[0015] Where ρ L Here is the first density response parameter, ρ1 is the logging mud density, and ρ ma ρ is the density of the rock skeleton. f L is the pore fluid density, L1 is the wellbore collapse depth, L' is the long-distance detection depth, and φ is the porosity.

[0016] Furthermore, in this embodiment of the application, the step of determining the second density response parameter of the short-source distance detector based on the short-source distance detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity specifically includes: inputting the short-source distance detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity into a preset second density response parameter calculation formula to determine the second density response parameter of the short-source distance detector;

[0017] The formula for calculating the second density response parameter includes:

[0018]

[0019] Where ρ s The second density response parameter is ρ1, where ρ is the logging mud density. ma ρ is the density of the rock skeleton. f φ is the pore fluid density, L1 is the wellbore collapse depth, L is the short source distance detection depth, and φ is the porosity.

[0020] Furthermore, in this embodiment of the application, the step of determining the pure formation density with the highest porosity in the interpretation section based on the long source distance detection depth, the short source distance detection depth, the first density response parameter, and the second density response parameter specifically includes: inputting the long source distance detection depth, the short source distance detection depth, the first density response parameter, and the second density response parameter into a preset formation density formula to determine the pure formation density with the highest porosity in the interpretation section;

[0021] The formula for the formation density is:

[0022]

[0023] Where ρ b To explain the density of the pure formation with the highest porosity in the stratigraphic interval, ρ s ρ is the second density response parameter. L Let L' be the first density response parameter, L' be the long source distance detection depth, and L be the short source distance detection depth.

[0024] On the other hand, embodiments of this application also provide a logging wellbore environment correction system, including:

[0025] The acquisition unit is used to acquire the initial formation density, wellbore collapse depth, clay content, clay density, short source distance detection depth, long source distance detection depth, logging mud density, rock skeleton density, pore fluid density of the uncollapsed part of the formation in the well, and porosity of the uncollapsed part of the formation in the well.

[0026] The first processing unit is used to determine the first density response parameter of the long-source-distance detector based on the long-source-distance detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity.

[0027] The second processing unit is used to determine the second density response parameter of the short-source-distance detector based on the short-source-distance detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity.

[0028] The third processing unit is used to determine the density of the pure formation with the highest porosity in the interpretation section based on the long source distance detection depth, the short source distance detection depth, the first density response parameter and the second density response parameter.

[0029] The fourth processing unit is used to determine the corrected target formation density based on the initial formation density, the clay content, the clay density, and the pure formation density.

[0030] On the other hand, this application also provides a logging wellbore environment correction device, comprising:

[0031] At least one processor;

[0032] At least one memory for storing at least one program;

[0033] When the at least one program is executed by the at least one processor, the at least one processor implements a logging wellbore environment correction method as described above.

[0034] In addition, this application also provides a storage medium storing processor-executable instructions, which, when executed by a processor, are used to perform a logging wellbore environment correction method as described above.

[0035] The advantages and beneficial effects of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application:

[0036] This application determines the first density response parameter of a long-spacing detector using long-spacing detection depth, borehole collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity; and determines the second density response parameter of a short-spacing detector using short-spacing detection depth, borehole collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity. Then, using the long-spacing detection depth, short-spacing detection depth, first density response parameter, and second density response parameter, the pure formation density with the highest porosity in the interpretation interval is determined. Finally, the corrected target formation density is determined using the initial formation density, clay content, clay density, and pure formation density. This application fully considers wellbore enlargement or wellbore changes when determining the final target formation density, and incorporates logging parameters such as long-spacing detection depth, borehole collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity into the calculation, thereby improving the accuracy of formation density calculation. Attached Figure Description

[0037] Figure 1 This is a schematic diagram illustrating the steps of a well logging environment correction method in a specific embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram illustrating the steps of determining the corrected target formation density based on the initial formation density, clay content, clay density, and pure formation density in a specific embodiment of the present invention.

[0039] Figure 3 This is a schematic diagram illustrating the steps of determining the target formation density based on the initial formation density and the first formation density in a specific embodiment of the present invention.

[0040] Figure 4 This is a schematic diagram of the steps of the well logging environment correction method in another specific embodiment of the present invention;

[0041] Figure 5 This is a schematic diagram of the steps of the well logging environment correction method in another specific embodiment of the present invention;

[0042] Figure 6 This is a schematic diagram of compensated density logging measurement in a specific embodiment of the present invention;

[0043] Figure 7 This is a schematic diagram of the simulation results of density logging wellbore correction in a specific embodiment of the present invention;

[0044] Figure 8 This is a schematic diagram of the simulation results of density logging wellbore correction in another specific embodiment of the present invention;

[0045] Figure 9This is a schematic diagram of the structure of a logging wellbore environment correction system in a specific embodiment of the present invention;

[0046] Figure 10 This is a schematic diagram of a well logging environment correction device in a specific embodiment of the present invention. Detailed Implementation

[0047] The following detailed description, in conjunction with the accompanying drawings, illustrates the principles and processes of the well logging environment correction method, system, device, and storage medium in the embodiments of the present invention.

[0048] First, the existing correction methods will be explained:

[0049] Density curves are one of the essential elastic parameters for seismic inversion and rock physics modeling. Moreover, due to environmental factors such as wellbore enlargement, density logging in most enlarged well sections will show abnormally low values. Therefore, it is necessary to correct the wellbore logging and calculate the corrected formation density.

[0050] In related technologies, the true density ρ of the formation obtained from well logging is usually calculated using a model porosity φ based on a volumetric model of formation components. b This density value can be used to verify the effectiveness of wellbore correction. Its calculation formula is:

[0051] ρ b =(1-V sh -φ)*ρ ma + V sh *DEN sh +φ*ρ f

[0052] ρ ma The density of the rock skeleton; ρ f V is the pore fluid density in the formation; φ is the porosity of the formation; V sh DEN is the clay content. sh The density is the density of the clay. Then, the formation density from the well logging is calculated using a formula.

[0053] In the aforementioned algorithms, while environmental corrections can be made using the density of the rock skeleton, the density of pore fluids in the formation, the porosity of the formation, the clay content, and the clay density, their accuracy is often relatively low. According to the measurement principle of density logging, density logging records the intensity of gamma rays scattered from the formation, primarily used to measure formation volume density and calculate formation porosity. Wellbore enlargement or irregular wellbore walls have a significant impact on density logging curves, often causing a sharp drop in the density logging curve and resulting in significantly lower measured density values.

[0054] In response to the aforementioned technical deficiencies, referring to Figure 1 , Figure 1 This is a schematic diagram illustrating the steps of a well logging well environment correction method according to this application. Figure 1 The correction method of this application includes, but is not limited to, steps S101-S105.

[0055] S101. Obtain the initial formation density, wellbore collapse depth, clay content, clay density, short-spot distance detection depth, long-spot distance detection depth, logging mud density, rock skeleton density, pore fluid density of the uncollapsed portion of the formation within the well, and porosity of the uncollapsed portion of the formation within the well.

[0056] Understandably, well logging can refer to the well being measured. This well can be offshore or onshore. Initial formation density, wellbore collapse depth, clay content, clay density, short-spacing depth of detection, long-spacing depth of detection, logging mud density, rock skeleton density, pore fluid density of the uncollapsed portion of the formation within the well, and porosity of the uncollapsed portion of the formation within the well can all be measured using existing equipment or sensors. Specifically, short-spacing depth of detection can be measured using a short-spacing detector, and long-spacing depth of detection can be measured using a long-spacing detector.

[0057] In some feasible embodiments of this application, the processor can establish a wired or wireless connection with existing measuring devices or sensors. Through communication between the devices, data measured by the measuring devices or sensors can be transmitted to the processor. The processor can further process data such as initial formation density, wellbore collapse depth, clay content, clay density, short-spacing detection depth, long-spacing detection depth, logging mud density, rock skeleton density, pore fluid density of the uncollapsed portion of the formation within the well, and porosity of the uncollapsed portion of the formation within the well.

[0058] It should be noted that the aforementioned limited connection methods may include connections between mobile devices and host computers, connections between host computers, and wired connections between other known or future-developed devices and host computers; while the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (Ultra Wide Band) connections, and other known or future-developed wireless connection methods.

[0059] S102. Determine the first density response parameter of the long-spot distance detector based on the long-spot distance detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity.

[0060] It is understandable that the first density response parameter can be the density response parameter corresponding to a long source-distance detector.

[0061] In some feasible embodiments of this application, the long-spacing detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity can be stored in a database. The processor can extract the long-spacing detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity from the database and input them into the calculation formula within the storage processor to ultimately determine the first density response parameter of the long-spacing detector.

[0062] S103. Determine the second density response parameters of the short-spot distance detector based on the short-spot distance detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity.

[0063] It is understandable that the second density response parameter can be the density response parameter corresponding to a short source distance detector.

[0064] In some feasible embodiments of this application, the short-spacing detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity can be stored in a database. The processor can extract these parameters from the database and input them into a calculation formula within the storage processor, ultimately determining the second density response parameter for the long-spacing detector.

[0065] It should be noted that the calculation formula in this embodiment can be the same as or different from the formula used to determine the first density response parameter of the long-source-distance detector. The calculation formula in the storage processor can be set differently according to different needs.

[0066] S104. Based on the long source distance detection depth, short source distance detection depth, first density response parameter, and second density response parameter, determine the density of the pure formation with the highest porosity in the interpretation interval.

[0067] It is understandable that the porosity in the interpretation section may vary due to different depths in actual exploration. In this embodiment, the density of the pure formation with the highest porosity in the interpretation section is determined.

[0068] In some feasible embodiments of this application, the processor can extract short-source-distance detection depth, long-source-distance detection depth, first density response parameter and second density response parameter from the database, and input them into the calculation formula in the storage processor, so as to finally determine the pure formation density with the highest porosity in the interpretation section.

[0069] S105. Determine the corrected target formation density based on the initial formation density, clay content, clay density, and pure formation density.

[0070] In some feasible embodiments of this application, the processor can extract the initial formation density, clay content, clay density and pure formation density from the database and input them into the calculation formula in the storage processor, and finally determine the pure formation density with the highest porosity in the interpretation section.

[0071] In summary, this application can determine the first density response parameter of a long-spacing detector using long-spacing detection depth, borehole collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity; and determine the second density response parameter of a short-spacing detector using short-spacing detection depth, borehole collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity. Then, using the long-spacing detection depth, short-spacing detection depth, first density response parameter, and second density response parameter, the pure formation density with the highest porosity in the interpretation interval is determined. Finally, the corrected target formation density is determined using the initial formation density, clay content, clay density, and pure formation density. This application fully considers the expansion of the logging or changes in the wellbore when determining the final target formation density, and incorporates logging parameters such as long-spacing detection depth, borehole collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity into the calculation, which can improve the accuracy of formation density calculation.

[0072] Furthermore, referring to Figure 2 , Figure 2 This is a schematic diagram illustrating the steps in this application for determining the corrected target formation density based on the initial formation density, clay content, clay density, and pure formation density. Figure 2 In this process, the step may include, but is not limited to, steps S201-S202.

[0073] S201. Determine the first formation density based on the initial formation density, clay content, clay density, and pure formation density.

[0074] S202. Determine the target formation density based on the initial formation density and the first formation density.

[0075] Understandably, the first formation density can be the minimum theoretical formation density of the measured well, which may differ from the actual directly measured formation density.

[0076] In some feasible embodiments of this application, the processor can calculate a first formation density based on the initial formation density, clay content, clay density, and pure formation density. After calculating the first formation density, the corrected target formation density is finally determined by comparing the magnitudes of the initial formation density and the first formation density.

[0077] Furthermore, the step of determining the first formation density based on the initial formation density, clay content, clay density, and pure formation density can specifically include:

[0078] The initial formation density, clay content, clay density, and pure formation density are input into a preset formation density determination formula to determine the first formation density; the formation density determination formula is as follows:

[0079] DEN min =V sh *DEN sh +(1-V sh *ρ b )*DEN

[0080] DEN min V is the density of the first formation. sh DEN is the clay content. sh ρ is the density of clay, DEN is the initial formation density, and ρ is the density of clay. b This represents the density of the pure formation.

[0081] In some feasible embodiments of this application, the processor may first be configured with a formation density determination formula. The formula is specifically as follows:

[0082] DEN min =V sh *DEN sh +(1-V sh *ρ b )*DEN

[0083] DEN min V is the density of the first formation. sh DEN is the clay content. sh ρ is the density of clay, DEN is the initial formation density, and ρ is the density of clay. b This refers to the pure formation density. After the formula is configured, the processor receives three data points: initial formation density, clay content, clay density, and pure formation density. The first formation density can be directly calculated using the internally set formula.

[0084] Furthermore, referring to Figure 3 , Figure 3 This is a schematic diagram illustrating the steps in this application for determining the target formation density based on the initial formation density and the first formation density. Figure 3In this process, this step may include, but is not limited to, steps S301-S303.

[0085] S301. Determine the initial formation density and the relationship between the magnitudes of the first formation density;

[0086] S302. When the initial formation density is greater than or equal to the first formation density, the initial formation density shall be used as the target formation density.

[0087] S303. When the initial formation density is less than the first formation density, the first formation density shall be used as the target formation density.

[0088] In some feasible embodiments of this application, the processor can compare the initial formation density with the first formation density. When the initial formation density is greater than or equal to the first formation density, the processor can determine the initial formation density as the corrected target formation density. When the initial formation density is less than the first formation density, the processor can determine the first formation density as the target formation density.

[0089] Furthermore, referring to Figure 4 The step of determining the first density response parameter of the long-source-distance detector based on the long-source-distance detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity specifically includes step S1021.

[0090] S1021. Input the long-spot detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity into the preset first density response parameter calculation formula to determine the first density response parameter of the long-spot detector.

[0091] The formula for calculating the first density response parameter includes:

[0092]

[0093] Where ρ L Here is the first density response parameter, ρ1 is the logging mud density, and ρ ma ρ is the density of the rock skeleton. f L is the pore fluid density, L1 is the wellbore collapse depth, L' is the long-distance detection depth, and φ is the porosity.

[0094] In some feasible embodiments of this application, the processor may be initially configured with a formula for calculating the first density response parameter. The formula is specifically as follows:

[0095]

[0096] Where ρ L Here is the first density response parameter, ρ1 is the logging mud density, and ρ ma ρ is the density of the rock skeleton.f Let L1 be the pore fluid density, L' be the wellbore collapse depth, L' be the long-spacing detection depth, and φ be the porosity. After the formula is configured, the processor receives six data points: long-spacing detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity. Using the internally set formula, it can directly calculate the first density response parameter of the long-spacing detector.

[0097] Furthermore, referring to Figure 5 The step of determining the second density response parameter of the short-source-distance detector based on the short-source-distance detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity may specifically include step S1031.

[0098] S1031. Input the short-source distance detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity into the preset second density response parameter calculation formula to determine the second density response parameter of the short-source distance detector.

[0099] The formula for calculating the second density response parameter includes:

[0100]

[0101] Where ρ s The second density response parameter is ρ1, where ρ is the logging mud density. ma ρ is the density of the rock skeleton. f φ is the pore fluid density, L1 is the wellbore collapse depth, L is the short source distance detection depth, and φ is the porosity.

[0102] In some feasible embodiments of this application, the processor may first be configured with a second density response parameter calculation formula. The formula is specifically as follows:

[0103]

[0104] Where ρ s The second density response parameter is ρ1, where ρ is the logging mud density. ma ρ is the density of the rock skeleton. f Here, L is the pore fluid density, L1 is the wellbore collapse depth, L is the short-spacing detection depth, and φ is the porosity. After the formula is configured, the processor receives six data points: short-spacing detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity. Using the internally set formula, it can directly calculate the second density response parameter of the long-spacing detector.

[0105] Furthermore, the step of determining the density of the pure formation with the highest porosity in the interpretation interval based on the long-source-distance detection depth, the short-source-distance detection depth, the first density response parameter, and the second density response parameter specifically includes:

[0106] The long-source-distance detection depth, short-source-distance detection depth, first density response parameter, and second density response parameter are input into the preset formation density formula to determine the pure formation density with the highest porosity in the interpretation interval.

[0107] The formula for formation density is:

[0108]

[0109] Where ρ b To explain the density ρ of the pure formation with the highest porosity in the stratigraphic interval s ρ is the second density response parameter. L Let L' be the first density response parameter, L' be the long source distance detection depth, and L be the short source distance detection depth.

[0110] In some feasible embodiments of this application, the processor may first be configured with a second density response parameter calculation formula, the formula being as follows:

[0111]

[0112] Where ρ b To explain the density ρ of the pure formation with the highest porosity in the stratigraphic interval s ρ is the second density response parameter. L Here, L' is the first density response parameter, L' is the long-source-distance detection depth, and L is the short-source-distance detection depth. After the formula is configured, the processor receives four data points: the long-source-distance detection depth, the short-source-distance detection depth, the first density response parameter, and the second density response parameter. Using the internally set formula, it can directly calculate the density of the pure formation with the highest porosity in the interpretation section.

[0113] The specific implementation principle of this application is explained below with reference to the accompanying drawings:

[0114] First, refer to Figure 6 A compensated density logging tool consists of two conventional density logging tools with unequal source spacing. The shorter source spacing probe has a shallower detection depth, while the longer source spacing probe has a deeper detection depth. Therefore, the relative contributions of each part to the probe response in the radial direction are also different. The difference in detection depth between the two tools is often used to correct for the influence of mud cake. Figure 6 In this context, L1 represents the wellbore collapse depth; L represents the short-spacing detection depth; and L' represents the long-spacing detection depth.

[0115] In practical engineering applications, some density logging has its own unique characteristics, especially when two density logging curves with long and short source distances are provided. However, due to the unknown calibration chart of the instrument, it is difficult to use traditional calibration methods to correct for the formations that are severely affected by the wellbore. By analyzing the theoretical response of density logging, this paper attempts a method to correct for the impact on the wellbore based on the different detection depths of long and short source distances.

[0116] Specifically, the calculation process in this embodiment includes:

[0117] 1. Construct a theoretical model.

[0118] Since density logging is performed close to the wellbore, the contributions of the enlarged borehole portion and the formation portion to the density logging values ​​can be considered only. The formation portion includes the rock skeleton and the pore fluid portion (φ). The model is as follows: Figure 6 As shown.

[0119] 2. Calculate the corrected target formation density.

[0120] The readings of the long-source-pitch detectors and the short-source-pitch detectors are respectively denoted as ρ. L and ρ s Then there is

[0121] (3-10)

[0122] (3-11)

[0123] In equations (3-10) and (3-11), ρ1 is the density of the mud; ρ ma The density of the rock skeleton; ρ f To study the pore fluid density in the uncollapsed strata within the depth range; φ represents the porosity of the strata.

[0124] Multiply both sides of equation (3-10) by L', and both sides of equation (3-11) by L, then subtract the two equations to obtain...

[0125] (3-12)

[0126] Ignoring the effects of mud intrusion, the density of the formation can be expressed as:

[0127] (3-13)

[0128] From equations (3-12) and (3-13), the formation density can be expressed as:

[0129] (3-14)

[0130] Secondly, the effectiveness of the correction was verified through experiments.

[0131] 1. The impact of wellbore enlargement on density logging in a water-bearing pure sandstone formation is simulated. It is assumed that the wellbore is filled with fresh cement slurry with a density ρ1 of 1.0 g / cm³; the density of the rock skeleton is taken as the density value of sandstone ρma, which is 2.65 g / cm³; the density of the pore fluid ρf is taken as 1.0 g / cm³; the source distance of the long and short source distance detectors is set to 30 cm and 10 cm, respectively; the model porosity φ is randomly generated between 0.42 and 0.76; the drill bit diameter BS is set to 15 cm; wellbore collapse occurs at depths of 7-8 m, 17-20 m, and 26-30 m, see [see details]. Figure 7 .

[0132] 2. The simulation steps include:

[0133] (1) Calculate the true density ρ of the formation using the model porosity φ based on the volumetric model of the formation components. b

[0134] (2) According to Figure 6 The theoretical model proposed in the paper calculates the density response values ​​ρ of detectors with long and short source distances according to equations (3-10) and (3-11). L and ρ s The pure formation density ρ was calculated using (3-14). b .

[0135] (3) The influence of the wellbore is corrected using equation (3-8) to obtain the corrected formation density ρ. C (DENc).

[0136] DEN min =V sh *DEN sh +(1-V sh *ρ b )*DEN

[0137]

[0138] DEN min V is the density of the first formation. sh DEN is the clay content. sh ρ is the density of clay, DEN is the initial formation density, and ρ is the density of clay. b This represents the density of the pure formation.

[0139] 3. Results of theoretical simulation

[0140] The results of theoretical simulations are as follows Figure 7 As shown in the figure. CAL in the figure represents the wellbore diameter curve, reflecting the changes in the wellbore; in the 7-8 m, 17-20 m, and 26-30 m sections where the wellbore enlarges, ρ... L and ρ sAll are significantly reduced, and the short source distance ρ s Longer source distance ρ L The significant decrease is due to the mud density being lower than the formation density; utilizing ρ L and ρ s Formation density curve ρ after wellbore correction C The actual density curve ρb of the formation almost completely overlaps with the actual density curve, which shows that this method is theoretically feasible and can eliminate the impact of wellbore enlargement on density logging.

[0141] In some older wells and newer offshore wells, density logging data is often presented as long- or short-spot density. By combining this with relevant instrument parameters, wellbore calibration can be performed on the density logging data. This application demonstrates the effectiveness of this method in a well in the South China Sea. Figure 8 As shown.

[0142] Depend on Figure 8 It can be seen that in the interval where the wellbore diameter (CAL) increases, both the long and short source distance density curves decrease, and the short source distance density ρ s ρ, the density of sources with longer distances L The reduction is significant; in wellbore-stable sections, the density values ​​for long and short source distances coincide or are close. After wellbore correction, the formation density curve ρ... C There has been a significant improvement.

[0143] In addition, refer to Figure 9 ,and Figure 1Corresponding to the method described above, this application also provides a wellbore environment correction system. This system may include an acquisition unit 1001, a first processing unit 1002, a second processing unit 1003, a third processing unit 1004, and a fourth processing unit 1005. The acquisition unit can be connected to the first processing unit, the first processing unit can be connected to the second processing unit, the second processing unit can be connected to the third processing unit, and the third processing unit can be connected to the fourth processing unit. The acquisition unit 1001 can be used to acquire the initial formation density, wellbore collapse depth, clay content, clay density, short-spacing detection depth, long-spacing detection depth, logging mud density, rock skeleton density, pore fluid density of the uncollapsed portion of the formation within the well, and porosity of the uncollapsed portion of the formation within the well. The first processing unit 1002 can be used to determine the first density response parameter of the long-spacing detector based on the long-spacing detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity. The second processing unit 1003 can be used to determine the second density response parameter of the short-spacing detector based on the short-spacing detection depth, wellbore collapse depth, logging mud density, rock skeleton density, pore fluid density, and porosity. The third processing unit 1004 can be used to determine the pure formation density with the highest porosity in the interpretation interval based on the long-spacing detection depth, short-spacing detection depth, the first density response parameter, and the second density response parameter. The fourth processing unit 1005 can be used to determine the corrected target formation density based on the initial formation density, clay content, clay density, and pure formation density.

[0144] It should be noted that the acquisition unit 1001 can be any integrated circuit module or microprocessor module obtained by integrating a chip with processing functions and its peripheral circuits using existing integration technology. Similarly, the first processing unit 1002 can also be any integrated circuit module or microprocessor module obtained by integrating a chip with processing functions and its peripheral circuits using existing integration technology. Furthermore, the first processing unit 1002 may include one or more memories.

[0145] In some embodiments of this application, the acquisition unit 1001 may be located in the same gateway or a device with a processor as the first processing unit 1002. The acquisition unit 1001 can acquire the initial formation density, wellbore collapse depth, clay content, clay density, short-spacing detection depth, long-spacing detection depth, logging mud density, rock skeleton density, pore fluid density of the uncollapsed portion of the formation within the well, and porosity of the uncollapsed portion of the formation within the well through a chip within its own processor. The first processing unit 1002 can calculate the first density response parameter of the long-spacing detector using an internal algorithm. The second processing unit 1003 can calculate the second density response parameter of the short-spacing detector using an internal algorithm. The acquisition unit 1001 can transmit the acquired data to the processor via a wired or wireless connection with the processor of the first processing unit 1002. The specific device connection method and device configuration between the acquisition unit 1001 and the first processing unit 1002 are not limited.

[0146] It should be noted that the content of the above-described well logging environment correction method embodiments is applicable to the well logging environment correction system embodiments. The specific functions implemented by the well logging environment correction system embodiments are the same as those of the above-described well logging environment correction method embodiments, and the beneficial effects achieved are also the same as those achieved by the above-described well logging environment correction method embodiments.

[0147] and Figure 1 Corresponding to the method, this application also provides a logging wellbore environment correction device, the specific structure of which can be referred to Figure 10 ,include:

[0148] At least one processor 1011;

[0149] At least one memory 1012 is used to store at least one program;

[0150] When the at least one program is executed by the at least one processor, the at least one processor implements the well logging environment correction method.

[0151] It should be noted that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0152] and Figure 1 Corresponding to the method described above, this application also provides a storage medium storing processor-executable instructions, which, when executed by the processor, are used to perform the well logging environment correction method.

[0153] It should be noted that the content of the above-described well logging environment correction method embodiments is applicable to this storage medium embodiment. The specific functions implemented by this storage medium embodiment are the same as those of the above-described well logging environment correction method embodiments, and the beneficial effects achieved are also the same as those achieved by the above-described well logging environment correction method embodiments.

[0154] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this application are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0155] Furthermore, although this application is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding this application. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional technology for an engineer. Therefore, those skilled in the art can implement the application set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of this application, which is determined by the full scope of the appended claims and their equivalents.

[0156] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several programs to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0157] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequential list of executable programs for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, a program execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can retrieve and execute a program from or in conjunction with such a program execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can mean any means that can contain, store, communicate, propagate, or transmit a program for use by or in conjunction with a program execution system, apparatus, or device.

[0158] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0159] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable program execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0160] In the foregoing description of this specification, the references to terms such as "one embodiment," "another embodiment," or "some embodiments," etc., indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0161] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

[0162] The above is a detailed description of the preferred embodiments of this application, but this application is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application, and these equivalent modifications or substitutions are all included within the scope defined by the claims of this application.

Claims

1. A method for correcting wellbore environment during logging, characterized in that, include: The logging data includes initial formation density, wellbore collapse depth, clay content, clay density, short-spot distance detection depth, long-spot distance detection depth, logging mud density, rock skeleton density, pore fluid density of the uncollapsed portion of the formation within the well, and porosity of the uncollapsed portion of the formation within the well. The first density response parameter of the long-source-distance detector is determined based on the long-source-distance detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity. The second density response parameter of the short-spot distance detector is determined based on the short-spot distance detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity. Based on the long source distance detection depth, the short source distance detection depth, the first density response parameter, and the second density response parameter, the density of the pure formation with the highest porosity in the interpretation section is determined. The corrected target formation density is determined based on the initial formation density, the clay content, the clay density, and the pure formation density. The step of determining the corrected target formation density based on the initial formation density, the clay content, the clay density, and the pure formation density specifically includes: The first formation density is determined based on the initial formation density, the clay content, the clay density, and the pure formation density. The target formation density is determined based on the initial formation density and the first formation density; The step of determining the first formation density based on the initial formation density, the clay content, the clay density, and the pure formation density specifically includes: The initial formation density, the clay content, the clay density, and the pure formation density are input into a preset formation density determination formula to determine the first formation density; wherein the formation density determination formula is: DEN min =V sh *DEN sh +(1-V sh *ρ b )*DEN DEN min V is the density of the first formation. sh DEN is the clay content. sh ρ is the density of clay, DEN is the initial formation density, and ρ is the density of clay. b This represents the density of the pure formation. The step of determining the target formation density based on the initial formation density and the first formation density specifically includes: Determine the initial formation density and the relationship between the magnitudes of the first formation density; When the initial formation density is greater than or equal to the first formation density, the initial formation density is used as the target formation density; When the initial formation density is less than the first formation density, the first formation density is used as the target formation density.

2. The well logging environment correction method according to claim 1, characterized in that, The step of determining the first density response parameter of the long-spacing detector based on the long-spacing detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity specifically includes: The long-source-distance detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity are input into a preset first density response parameter calculation formula to determine the first density response parameter of the long-source-distance detector. The formula for calculating the first density response parameter includes: Where ρ L Here is the first density response parameter, ρ1 is the logging mud density, and ρ ma ρ is the density of the rock skeleton. f L is the pore fluid density, L1 is the wellbore collapse depth, L' is the long-distance detection depth, and φ is the porosity.

3. The well logging environment correction method according to claim 1, characterized in that, The step of determining the second density response parameter of the short-spot detector based on the short-spot detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity specifically includes: The short-source distance detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity are input into a preset second density response parameter calculation formula to determine the second density response parameter of the short-source distance detector; The formula for calculating the second density response parameter includes: Where ρ s The second density response parameter is ρ1, where ρ is the logging mud density. ma ρ is the density of the rock skeleton. f φ is the pore fluid density, L1 is the wellbore collapse depth, L is the short source distance detection depth, and φ is the porosity.

4. The well logging environment correction method according to claim 1, characterized in that, The step of determining the density of the pure formation with the highest porosity in the interpretation section based on the long-source-distance detection depth, the short-source-distance detection depth, the first density response parameter, and the second density response parameter specifically includes: The long-source-distance detection depth, the short-source-distance detection depth, the first density response parameter, and the second density response parameter are input into a preset formation density formula to determine the pure formation density with the highest porosity in the interpretation section. The formula for the formation density is: Where ρ b To explain the density of the pure formation with the highest porosity in the stratigraphic interval, ρ s ρ is the second density response parameter. L Let L' be the first density response parameter, L' be the long source distance detection depth, and L be the short source distance detection depth.

5. A logging wellbore environment correction system, characterized in that, include: The acquisition unit is used to acquire the initial formation density, wellbore collapse depth, clay content, clay density, short source distance detection depth, long source distance detection depth, logging mud density, rock skeleton density, pore fluid density of the uncollapsed part of the formation in the well, and porosity of the uncollapsed part of the formation in the well. The first processing unit is used to determine the first density response parameter of the long-source-distance detector based on the long-source-distance detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity. The second processing unit is used to determine the second density response parameter of the short-source-distance detector based on the short-source-distance detection depth, the wellbore collapse depth, the logging mud density, the rock skeleton density, the pore fluid density, and the porosity. The third processing unit is used to determine the density of the pure formation with the highest porosity in the interpretation section based on the long source distance detection depth, the short source distance detection depth, the first density response parameter and the second density response parameter. The fourth processing unit is used to determine the corrected target formation density based on the initial formation density, the clay content, the clay density, and the pure formation density. The step of determining the corrected target formation density based on the initial formation density, the clay content, the clay density, and the pure formation density specifically includes: The first formation density is determined based on the initial formation density, the clay content, the clay density, and the pure formation density. The target formation density is determined based on the initial formation density and the first formation density; The step of determining the first formation density based on the initial formation density, the clay content, the clay density, and the pure formation density specifically includes: The initial formation density, the clay content, the clay density, and the pure formation density are input into a preset formation density determination formula to determine the first formation density; wherein the formation density determination formula is: DEN min =V sh *DEN sh +(1-V sh *ρ b )*DEN DEN min V is the density of the first formation. sh DEN is the clay content. sh ρ is the density of clay, DEN is the initial formation density, and ρ is the density of clay. b This represents the density of the pure formation. The step of determining the target formation density based on the initial formation density and the first formation density specifically includes: Determine the initial formation density and the relationship between the magnitudes of the first formation density; When the initial formation density is greater than or equal to the first formation density, the initial formation density is used as the target formation density; When the initial formation density is less than the first formation density, the first formation density is used as the target formation density.

6. A logging wellbore environment correction device, characterized in that... include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements a logging wellbore environment correction method as described in any one of claims 1-4.

7. A computer-readable storage medium storing processor-executable instructions, characterized in that, The processor-executable instructions, when executed by the processor, are used to perform a logging wellbore environment correction method as described in any one of claims 1-4.

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