Method and apparatus for correcting formation resistivity

Abstract

The application discloses a kind of correction processing method and device of formation resistivity.Therein, the method includes: obtaining the first measurement parameter corresponding to a plurality of formations in target oil well respectively;Based on the first porosity and the first permeability corresponding to a plurality of formations respectively, using corresponding fitting algorithm, the porosity calculation model and the permeability calculation model corresponding to target oil well are obtained respectively;Based on the porosity calculation model, the second porosity corresponding to the formation to be measured in target oil well is determined;And based on the permeability calculation model, the second permeability corresponding to the formation to be measured is determined;Based on the second porosity and the second permeability corresponding to the formation to be measured, the formation measurement resistivity corresponding to the formation to be measured is corrected, and the corrected formation measurement resistivity corresponding to the formation to be measured is obtained.The application solves the technical problems of poor correction effect of the correction processing method of formation resistivity in related art under high salinity mud invasion, low accuracy of formation resistivity measurement.

Description

Technical Field

[0001] This invention relates to the field of petroleum and natural gas geology and exploration and development engineering technology, and more specifically, to a method and apparatus for correcting formation resistivity. Background Technology

[0002] In medium- to high-porosity, high-permeability reservoirs, especially gas-bearing reservoirs, high-salinity drilling fluids can lead to resistivity logging values ​​that are significantly lower than the original formation resistivity. This interferes with reservoir identification and reduces the accuracy of calculating oil and gas saturation. Therefore, correcting resistivity logging data to restore the true formation resistivity has always been a challenge in well logging work and a crucial issue affecting oil and gas reservoir evaluation and the prediction of favorable areas.

[0003] For a long time, numerous correction methods and related calculation models have been proposed for the reconstruction of true formation resistivity. Commonly used methods include the chart method and numerical simulation. The chart method involves creating a corresponding invasion correction chart based on logging instruments. It works well in cases of low-salinity mud invasion, but its correction effect is poor in cases of high-salinity mud invasion. The numerical simulation method is based on the phase flow and diffusion theories in porous media, establishing a dynamic relationship between resistivity logging values ​​and mud invasion depth, and inverting to obtain the true formation resistivity. However, this method makes too many assumptions, simplifying a complex nonlinear problem into a simple linear one, resulting in a significant deviation from actual formation conditions.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a method and apparatus for correcting formation resistivity, which at least solves the technical problem that the correction effect of formation resistivity correction methods in the related art is poor under the condition of high-mineralization mud intrusion and the accuracy of formation resistivity measurement is low.

[0006] According to one aspect of the present invention, a method for correcting formation resistivity is provided, comprising: acquiring first measurement parameters corresponding to multiple formations in a target oil well, wherein the first measurement parameters include at least: first porosity and first permeability; based on the first porosity corresponding to the multiple formations, employing a first fitting algorithm to obtain a porosity calculation model corresponding to the target oil well; based on the first permeability corresponding to the multiple formations, employing a second fitting algorithm to obtain a permeability calculation model corresponding to the target oil well; determining a second porosity corresponding to a formation to be tested in the target oil well based on the porosity calculation model; determining a second permeability corresponding to the formation to be tested based on the permeability calculation model; and correcting the formation resistivity corresponding to the formation to be tested based on the second porosity and the second permeability corresponding to the formation to be tested to obtain a corrected formation resistivity corresponding to the formation to be tested.

[0007] Optionally, the above-mentioned porosity calculation model for the target oil well is obtained by using a first fitting algorithm based on the first porosity corresponding to the above-mentioned multiple formations, including: obtaining the first logging density corresponding to the above-mentioned multiple formations; and obtaining the porosity calculation model by using the first fitting algorithm based on the first porosity and the first logging density corresponding to the above-mentioned multiple formations.

[0008] Optionally, determining the second porosity corresponding to the formation to be tested in the target oil well based on the porosity calculation model includes: obtaining the second logging density corresponding to the formation to be tested; and determining the second porosity corresponding to the formation to be tested based on the second logging density and using the porosity calculation model.

[0009] Optionally, the permeability calculation model for the target oil well is obtained by using a second fitting algorithm based on the first permeability corresponding to the multiple formations, including: obtaining the first total porosity, the first movable fluid porosity, and the first bound fluid porosity corresponding to the multiple formations; and obtaining the permeability calculation model by using the second fitting algorithm based on the first total porosity, the first movable fluid porosity, the first bound fluid porosity, and the first permeability corresponding to the multiple formations.

[0010] Optionally, the permeability calculation model obtained by employing the second fitting algorithm based on the first total porosity, the first movable fluid porosity, the first bound fluid porosity, and the first permeability corresponding to the aforementioned multiple strata includes: obtaining a first fitting coefficient, a second fitting coefficient, and a third fitting coefficient corresponding to the permeability calculation model based on the first total porosity, the first movable fluid porosity, the first bound fluid porosity, and the first permeability corresponding to the aforementioned multiple strata, using the second fitting algorithm; and constructing the permeability calculation model based on the first fitting coefficient, the second fitting coefficient, and the third fitting coefficient.

[0011]

[0012] Wherein, K represents the second permeability of the stratum to be tested; This represents the second total porosity corresponding to the stratum to be tested. This indicates the second movable fluid porosity corresponding to the aforementioned formation. denoted by , the second bound fluid porosity corresponding to the formation to be tested; f represents the first fitting coefficient mentioned above, g represents the second fitting coefficient mentioned above, and h represents the third fitting coefficient mentioned above.

[0013] Optionally, determining the second permeability corresponding to the formation to be tested based on the permeability calculation model includes: obtaining the second total porosity, the second movable fluid porosity, and the second bound fluid porosity corresponding to the formation to be tested; and determining the second permeability corresponding to the formation to be tested based on the second total porosity, the second movable fluid porosity, and the second bound fluid porosity, using the permeability calculation model.

[0014] Optionally, the above-mentioned correction processing of the formation resistivity corresponding to the formation to be tested based on the second porosity and the second permeability of the formation to be tested to obtain the corrected formation resistivity includes: obtaining the mud resistivity, cementation index and saturation index of the formation to be tested; and correcting the formation resistivity based on the formation resistivity, mud resistivity, second porosity, second permeability, cementation index and saturation index of the formation to be tested to obtain the corrected formation resistivity.

[0015] Optionally, the above-mentioned correction processing of the measured resistivity of the formation based on the measured resistivity of the formation, the resistivity of the mud, the second porosity, the second permeability, the cementation index, and the saturation index corresponding to the formation to be tested, to obtain the corrected measured resistivity of the formation, includes: based on the measured resistivity of the formation, the resistivity of the mud, the second porosity, the second permeability, the cementation index, and the saturation index corresponding to the formation to be tested, the measured resistivity of the formation is corrected in the following manner to obtain the corrected measured resistivity of the formation:

[0016]

[0017] Wherein, TRT represents the corrected formation resistivity, RT represents the formation resistivity, m represents the cementation index, n represents the saturation index, and K represents the second permeability. The second porosity is represented by α, which represents the mud intrusion constant factor corresponding to the tested formation. R mf This indicates the resistivity of the aforementioned mud.

[0018] According to another aspect of the present invention, a formation resistivity correction processing apparatus is also provided, comprising: a first acquisition module, configured to acquire first measurement parameters corresponding to multiple formations in a target oil well, wherein the first measurement parameters include at least: first porosity and first permeability; a second acquisition module, configured to obtain a porosity calculation model corresponding to the target oil well based on the first porosity corresponding to the multiple formations and employing a first fitting algorithm; a third acquisition module, configured to obtain a permeability calculation model corresponding to the target oil well based on the first permeability corresponding to the multiple formations and employing a second fitting algorithm; a determination module, configured to determine a second porosity corresponding to a formation to be tested in the target oil well based on the porosity calculation model; and to determine a second permeability corresponding to the formation to be tested based on the permeability calculation model; and a correction module, configured to perform correction processing on the formation resistivity corresponding to the formation to be tested based on the second porosity and the second permeability corresponding to the formation to be tested, to obtain a corrected formation resistivity corresponding to the formation to be tested.

[0019] According to another aspect of the present invention, a non-volatile storage medium is also provided, which stores a plurality of instructions adapted for a processor to load and execute any one of the above-described formation resistivity correction processing methods.

[0020] In this embodiment of the invention, by acquiring first measurement parameters corresponding to multiple formations in the target oil well, wherein the first measurement parameters include at least: first porosity and first permeability; based on the first porosity corresponding to the multiple formations, a first fitting algorithm is used to obtain a porosity calculation model corresponding to the target oil well; based on the first permeability corresponding to the multiple formations, a second fitting algorithm is used to obtain a permeability calculation model corresponding to the target oil well; based on the porosity calculation model, a second porosity corresponding to the formation to be tested in the target oil well is determined; and based on the permeability calculation model, a second permeability corresponding to the formation to be tested is determined. Based on the second porosity and second permeability of the formation to be tested, the formation resistivity of the formation to be tested is corrected to obtain the corrected formation resistivity. This achieves the goal of correcting formation resistivity through parameter fitting, thereby eliminating the influence of drilling fluid conditions with different mineralization on formation resistivity measurement. This improves the accuracy of formation resistivity correction under high-mineralization mud invasion conditions, and solves the technical problem that the formation resistivity correction method in related technologies has poor correction effect and low accuracy of formation resistivity measurement under high-mineralization mud invasion conditions. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0022] Figure 1 This is a flowchart of a method for correcting formation resistivity according to an embodiment of the present invention;

[0023] Figure 2 This is a schematic diagram of the fitting result of an optional porosity calculation model according to an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of the fitting results of an optional cementation index and saturation index according to an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram comparing the results of resistivity correction using a graphical method in an optional embodiment of the present invention with those in the prior art.

[0026] Figure 5 This is a schematic diagram of a formation resistivity correction processing device according to an embodiment of the present invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] According to an embodiment of the present invention, a method embodiment for correcting formation resistivity is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0030] Figure 1 This is a flowchart of a formation resistivity correction method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0031] Step S102: Obtain first measurement parameters corresponding to multiple formations in the target oil well, wherein the first measurement parameters include at least: first porosity and first permeability;

[0032] Step S104: Based on the first porosity corresponding to the above-mentioned multiple formations, a first fitting algorithm is used to obtain the porosity calculation model corresponding to the above-mentioned target oil well.

[0033] Step S106: Based on the first permeability corresponding to the above-mentioned multiple formations, a second fitting algorithm is used to obtain the permeability calculation model corresponding to the above-mentioned target oil well;

[0034] Step S108: Based on the above porosity calculation model, determine the second porosity corresponding to the formation to be tested in the above target oil well; and based on the above permeability calculation model, determine the second permeability corresponding to the formation to be tested.

[0035] Step S110: Based on the second porosity and second permeability of the formation to be tested, the formation resistivity of the formation to be tested is corrected to obtain the corrected formation resistivity of the formation to be tested.

[0036] Through the above steps, formation resistivity can be corrected by parameter fitting, thereby eliminating the influence of drilling fluid conditions with different mineralization on formation resistivity measurement. This achieves the technical effect of improving the accuracy of formation resistivity correction under high mineralization mud invasion conditions, and solves the technical problem that the formation resistivity correction method in related technologies has poor correction effect and low accuracy of formation resistivity measurement under high mineralization mud invasion conditions.

[0037] Optionally, the target oil wells mentioned above are oil wells pre-injected with high-salinity water-based drilling fluid (also known as mud); the aforementioned formations may be, but are not limited to, high-permeability formations. It can be understood that the aforementioned formations correspond to different formation depths in the oil well, and different formation depths correspond to different lithological core samples.

[0038] Optionally, the first fitting algorithm and the second fitting algorithm mentioned above can be the same algorithm or different algorithms. For example, the least squares fitting algorithm can be used to construct the porosity calculation model and permeability calculation model corresponding to the target oil well.

[0039] Optionally, the resistivity to be corrected mentioned in the embodiments of the present invention may include, but is not limited to: microsphere focused resistivity, shallow lateral resistivity, deep lateral resistivity, water-bearing resistivity of rock samples, gas-bearing resistivity of rock samples, resistivity after mud intrusion, etc.

[0040] Optionally, the corrected formation resistivity described above is the high-permeability formation resistivity to eliminate the influence of high-salinity water-based drilling fluid intrusion. The formation to be measured is any one of the formations in the target oil well.

[0041] Optionally, physical property analysis experiments are conducted on the aforementioned multiple formations to obtain the first porosity corresponding to each of the multiple formations. A first fitting algorithm may be used, but is not limited to, to fit the porosity calculation model corresponding to the target oil well based on the first logging density and the first porosity corresponding to each of the multiple formations.

[0042] Specifically, the first logging density corresponding to each of the above-mentioned formations can be obtained based on the density logging data corresponding to the above-mentioned target oil wells, but not limited to this method.

[0043] Optionally, physical property analysis experiments are conducted on the aforementioned multiple formations to obtain the first permeability corresponding to each of the multiple formations. A second fitting algorithm can be used, but is not limited to, to fit the permeability calculation model corresponding to the target oil well based on the first total porosity, first movable fluid porosity, first bound fluid porosity, and first permeability corresponding to each of the multiple formations. Specifically, the first total porosity, first movable fluid porosity, and first bound fluid porosity corresponding to each of the multiple formations can be obtained, but is not limited to, based on nuclear magnetic resonance logging data corresponding to the target oil well.

[0044] In this embodiment of the invention, firstly, based on pre-acquired logging data of the target oil well, logging parameters such as first porosity and first permeability corresponding to multiple formations in the target oil well are obtained; physical property analysis experiments are conducted on the multiple formations to obtain the first porosity and first permeability corresponding to each formation; based on the first porosity and first permeability corresponding to each formation, corresponding fitting algorithms are used to fit and obtain porosity calculation models and permeability calculation models corresponding to the target oil well; the second logging density corresponding to the formation to be tested is input into the porosity calculation model to obtain the second porosity corresponding to the formation to be tested; the second total porosity, second movable fluid porosity, and second bound fluid porosity corresponding to the formation to be tested are input into the permeability calculation model to obtain the second permeability corresponding to the formation to be tested. Based on the obtained second porosity and second permeability, the formation resistivity corresponding to the formation to be tested is corrected to obtain the corrected formation resistivity corresponding to the formation to be tested. This method fully considers the influence of mud concentration on formation resistivity measurements, thereby improving the accuracy of formation resistivity correction. It provides a reliable basis for the accurate evaluation of the electrical properties and saturation of high-permeability formations.

[0045] In an optional embodiment, based on the first porosity corresponding to the plurality of formations, a first fitting algorithm is used to obtain a porosity calculation model corresponding to the target oil well, including:

[0046] Obtain the first logging density corresponding to each of the above-mentioned formations;

[0047] Based on the first porosity and the first logging density corresponding to the above-mentioned multiple strata, the porosity calculation model is obtained by using the first fitting algorithm.

[0048] Optionally, physical property analysis experiments are conducted on the aforementioned multiple formations to obtain the first porosity corresponding to each of the multiple formations. A first fitting algorithm may be used, but is not limited to, to fit the porosity calculation model corresponding to the target oil well based on the first logging density and the first porosity corresponding to each of the multiple formations.

[0049] Optionally, but not limited to, the first logging density corresponding to each of the above-mentioned multiple formations can be obtained based on the density logging data corresponding to the above-mentioned target oil wells.

[0050] Optionally, based on the first porosity and the first logging density corresponding to the aforementioned multiple formations, the first fitting algorithm is used to obtain the fourth and fifth fitting coefficients corresponding to the porosity calculation model; based on the fourth and fifth fitting coefficients, the porosity calculation model in the following form is constructed:

[0051]

[0052] in, The first logging density represents the second porosity corresponding to the formation being tested; ρ represents the first logging density mentioned above; d represents the fourth fitting coefficient mentioned above; and e represents the fifth fitting coefficient mentioned above. The fourth and fifth fitting coefficients can be obtained by fitting porosity experimental data and density logging data from physical property analysis using the least squares method; the first logging density is obtained based on the density logging curve corresponding to the target oil well. Optionally, the first logging density is obtained based on the density logging curve corresponding to the target oil well, and the obtained logging curve is used to indicate the correspondence between any formation in the target oil well and the logging density.

[0053] In an optional embodiment, determining the second porosity corresponding to the formation to be tested in the target oil well based on the porosity calculation model includes:

[0054] Obtain the second logging density corresponding to the above-mentioned formation to be tested;

[0055] Based on the aforementioned second logging density, the aforementioned porosity calculation model is used to determine the aforementioned second porosity corresponding to the aforementioned formation to be tested.

[0056] It is understandable that after obtaining the second logging density corresponding to the above-mentioned formation to be tested, the obtained second logging density is input into the constructed porosity calculation model to calculate the second porosity corresponding to the above-mentioned formation to be tested.

[0057] In an optional embodiment, based on the first permeability corresponding to the plurality of formations, a second fitting algorithm is used to obtain the permeability calculation model corresponding to the target oil well, including:

[0058] Obtain the first total porosity, the first movable fluid porosity, and the first bound fluid porosity corresponding to the above-mentioned multiple strata respectively;

[0059] Based on the first total porosity, the first movable fluid porosity, the first bound fluid porosity, and the first permeability corresponding to the above-mentioned multiple strata, the permeability calculation model is obtained by using the second fitting algorithm.

[0060] Optionally, physical property analysis experiments are conducted on the aforementioned multiple formations to obtain the first permeability corresponding to each of the multiple formations. A second fitting algorithm may be used, but is not limited to, to fit the permeability calculation model corresponding to the aforementioned target oil well based on the first total porosity, first movable fluid porosity, first bound fluid porosity, and first permeability corresponding to each of the aforementioned multiple formations.

[0061] Optionally, but not limited to, based on the nuclear magnetic resonance logging data corresponding to the target oil wells, the first total porosity, the first movable fluid porosity, and the first bound fluid porosity corresponding to the multiple formations can be obtained respectively.

[0062] Optionally, based on the first total porosity, the first movable fluid porosity, the first bound fluid porosity, and the first permeability corresponding to the above-mentioned multiple strata, the second fitting algorithm is used to fit the fitting coefficients (i.e., the first fitting coefficient, the second fitting coefficient, and the third fitting coefficient) corresponding to the permeability calculation model, and the permeability calculation model is determined based on the corresponding fitting coefficients.

[0063] In an optional embodiment, based on the first total porosity, the first movable fluid porosity, the first bound fluid porosity, and the first permeability corresponding to the plurality of formations respectively, the permeability calculation model is obtained by employing the second fitting algorithm, including:

[0064] Based on the first total porosity, the first movable fluid porosity, the first bound fluid porosity, and the first permeability corresponding to the above-mentioned multiple strata, the first fitting coefficient, the second fitting coefficient, and the third fitting coefficient corresponding to the above-mentioned permeability calculation model are obtained by using the above-mentioned second fitting algorithm.

[0065] Based on the first fitting coefficient, the second fitting coefficient, and the third fitting coefficient mentioned above, the above penetration rate calculation model is constructed as follows:

[0066]

[0067] Wherein, K represents the second permeability of the stratum to be tested; This represents the second total porosity corresponding to the stratum to be tested. This indicates the second movable fluid porosity corresponding to the aforementioned formation. denoted by , the second bound fluid porosity corresponding to the formation to be tested; f represents the first fitting coefficient mentioned above, g represents the second fitting coefficient mentioned above, and h represents the third fitting coefficient mentioned above.

[0068] Optionally, but not limited to, the first, second, and third fitting coefficients can be obtained by using regression analysis of permeability experimental data and nuclear magnetic resonance logging data.

[0069] In an optional embodiment, determining the second permeability corresponding to the formation to be tested based on the permeability calculation model includes:

[0070] Obtain the second total porosity, the second movable fluid porosity, and the second bound fluid porosity corresponding to the above-mentioned formation to be tested;

[0071] Based on the aforementioned second total porosity, the aforementioned second movable fluid porosity, and the aforementioned second bound fluid porosity, the aforementioned permeability calculation model is used to determine the aforementioned second permeability corresponding to the aforementioned formation to be tested.

[0072] It is understandable that in the target oil well, the formation permeability is related to the total porosity, movable fluid porosity, and bound fluid porosity. After obtaining the second total porosity, second movable fluid porosity, and second bound fluid porosity corresponding to the formation to be tested, these values ​​are input into the pre-constructed permeability calculation model to calculate the second permeability corresponding to the formation to be tested.

[0073] In an optional embodiment, the above-mentioned correction processing of the formation resistivity corresponding to the formation to be tested based on the second porosity and the second permeability to obtain the corrected formation resistivity corresponding to the formation to be tested includes:

[0074] Obtain the mud resistivity, cementation index, and saturation index corresponding to the above-mentioned strata to be tested;

[0075] Based on the aforementioned formation resistivity, mud resistivity, second porosity, second permeability, cementation index, and saturation index corresponding to the formation to be tested, the formation resistivity is corrected to obtain the corrected formation resistivity.

[0076] Optionally, but not limited to, core electrical experiments can be conducted on the aforementioned strata to obtain the first cementation index and the first saturation index corresponding to each of the aforementioned strata. The core electrical experiments can be conducted according to the procedures specified in the standard "Core Analysis Methods SY / T5385-2007".

[0077] Optionally, based on the aforementioned formation resistivity, mud resistivity, second porosity, second permeability, cementation index, and saturation index corresponding to the formation to be tested, the formation resistivity is corrected in the following manner to obtain the corrected formation resistivity:

[0078]

[0079] Wherein, TRT represents the corrected formation resistivity, RT represents the formation resistivity, m represents the cementation index, n represents the saturation index, and K represents the second permeability. The second porosity is represented by α, which represents the mud intrusion constant factor corresponding to the tested formation. R mf This indicates the resistivity of the aforementioned mud.

[0080] Optionally, the aforementioned mud intrusion constant factor is used to indicate the degree of mud intrusion in the aforementioned formation.

[0081] Optionally, based on the measured resistivity of the first formation, the first mud resistivity, the first porosity, the first permeability, the first cementation index, the first saturation index, and the actual resistivity of the first formation corresponding to the aforementioned multiple formations, the mud intrusion constant factors corresponding to the aforementioned multiple formations are obtained by combining the least squares fitting algorithm in the following manner:

[0082]

[0083] Wherein, TRT represents the actual resistivity of the first formation, RT represents the measured resistivity of the first formation, m represents the first cementation index, n represents the first saturation index, and K represents the first permeability. The first porosity is represented by α, the mud intrusion constant factor is represented by R. mf This represents the resistivity of the first mud slurry mentioned above.

[0084] Based on the above embodiments and optional embodiments, the present invention proposes an optional implementation method, which specifically includes the following steps:

[0085] Step S1: Select target oil wells in the study area with logging data such as density, array lateral, nuclear magnetic resonance, and mud resistivity, and obtain the formation resistivity RT and mud resistivity R corresponding to the formation to be tested. mf .

[0086] Step S2: Select multiple formations with different lithologies from the target oil well and conduct physical property analysis experiments to obtain the first porosity and first permeability corresponding to each formation. Combined with density logging and nuclear magnetic resonance logging data, establish porosity and permeability calculation models using the least squares algorithm, as shown below. The model fitting results are as follows. Figure 2 As shown:

[0087]

[0088] In the formula, The second porosity is the formation to be tested, and DEN is the density logging curve. Any point on the density logging curve corresponds to the logging density of any formation in the target oil well.

[0089]

[0090] In the formula, K is the second permeability corresponding to the stratum to be tested; This represents the second total porosity corresponding to the stratum to be tested. The second movable fluid porosity corresponding to the formation to be tested; This represents the second bound fluid porosity corresponding to the formation to be tested.

[0091] Step S3: Select multiple formations in the target oil well to conduct rock electrical experiments. Using the least squares algorithm, obtain a cementation index m value of 1.968 and a saturation index n value of 1.858. The fitting results for the cementation index and saturation index are as follows: Figure 3 As shown.

[0092] Step S4: Obtain the second logging density corresponding to the formation to be tested, input the second logging density into the porosity calculation model obtained in step S2, and calculate the second porosity corresponding to the formation to be tested.

[0093] Step S5: Obtain the second total porosity, second movable fluid porosity, and second bound fluid porosity corresponding to the formation to be tested. Input the second total porosity, the second movable fluid porosity, and the second bound fluid porosity into the pre-constructed permeability calculation model to calculate the second permeability corresponding to the formation to be tested.

[0094] Step S6: Select multiple formations in the target oil well to conduct resistivity experiments under the condition of high salinity water-based drilling fluid invasion, obtain the formation resistivity corresponding to each formation, and obtain the mud invasion constant factor α as 7.1 by the least squares method.

[0095] Step S7: Based on the measured resistivity of the formation, the resistivity of the mud, the second porosity, the second permeability, the cementation index, and the saturation index corresponding to the formation to be tested, the measured resistivity of the formation is corrected in the following manner to obtain the corrected measured resistivity of the formation:

[0096]

[0097] Wherein, TRT represents the corrected formation resistivity, RT represents the formation resistivity, m represents the cementation index, n represents the saturation index, and K represents the second permeability. The second porosity is represented by α, which represents the mud intrusion constant factor corresponding to the tested formation. R mf This indicates the resistivity of the aforementioned mud.

[0098] Optional, Figure 4 This diagram illustrates the results of resistivity correction performed using a graphical method in the implementation of this invention and in the prior art. Figure 4 As can be seen from the second column, the resistivity correction effect of this application (corresponding to the experimentally corrected resistivity in the figure) is significantly better than the resistivity correction effect of the chart method (corresponding to the chart-corrected resistivity in the figure). That is, in this embodiment of the invention, by combining rock physics experimental techniques with well logging data, a high-permeability formation resistivity correction model based on resistivity experiments is established to solve the problem of the influence of mud invasion on high-permeability formations, and to provide a reliable basis for the accurate evaluation of the electrical properties and saturation of high-permeability formations.

[0099] This embodiment also provides a formation resistivity correction processing device, which is used to implement the above embodiments and preferred embodiments, and will not be repeated as already described. As used below, the terms "module" and "device" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0100] According to an embodiment of the present invention, an apparatus embodiment for implementing the above-described formation resistivity correction processing method is also provided. Figure 5 This is a schematic diagram of a formation resistivity correction processing device according to an embodiment of the present invention, as shown below. Figure 5 As shown, the above-mentioned formation resistivity correction processing device includes: a first acquisition module 500, a second acquisition module 502, a third acquisition module 504, a determination module 506, and a correction module 508, wherein:

[0101] The first acquisition module 500 is used to acquire first measurement parameters corresponding to multiple formations in the target oil well, wherein the first measurement parameters include at least: first porosity and first permeability;

[0102] The second acquisition module 502 is connected to the first acquisition module 500 and is used to obtain the porosity calculation model corresponding to the target oil well based on the first porosity corresponding to the multiple formations and using a first fitting algorithm.

[0103] The third acquisition module 504 is connected to the second acquisition module 502 and is used to obtain the permeability calculation model corresponding to the target oil well based on the first permeability corresponding to the multiple formations and using a second fitting algorithm.

[0104] The aforementioned determining module 506, connected to the aforementioned third acquiring module 504, is used to determine the second porosity corresponding to the formation to be tested in the aforementioned target oil well based on the aforementioned porosity calculation model; and to determine the second permeability corresponding to the formation to be tested based on the aforementioned permeability calculation model.

[0105] The aforementioned correction module 508 is connected to the aforementioned determination module 506 and is used to perform correction processing on the formation resistivity corresponding to the formation to be tested based on the aforementioned second porosity and the aforementioned second permeability, so as to obtain the corrected formation resistivity corresponding to the formation to be tested.

[0106] In this embodiment of the invention, a first acquisition module 500 is configured to acquire first measurement parameters corresponding to multiple formations in the target oil well, wherein the first measurement parameters include at least: first porosity and first permeability; a second acquisition module 502 is connected to the first acquisition module 500 and is configured to obtain a porosity calculation model corresponding to the target oil well based on the first porosity corresponding to the multiple formations and using a first fitting algorithm; a third acquisition module 504 is connected to the second acquisition module 502 and is configured to obtain a permeability calculation model corresponding to the target oil well based on the first permeability corresponding to the multiple formations and using a second fitting algorithm; a determination module 506 is connected to the third acquisition module 504 and is configured to determine the test formation in the target oil well based on the porosity calculation model. The second porosity corresponding to the layer; and the second permeability corresponding to the layer to be tested determined based on the above permeability calculation model; the correction module 508, connected to the determination module 506, is used to correct the formation resistivity corresponding to the layer to be tested based on the second porosity and the second permeability corresponding to the layer to be tested, to obtain the corrected formation resistivity corresponding to the layer to be tested. This achieves the purpose of correcting the formation resistivity by means of parameter fitting, thereby eliminating the influence of drilling fluid conditions with different mineralization on the formation resistivity measurement. This achieves the technical effect of improving the accuracy of formation resistivity correction under high mineralization mud invasion, and solves the technical problem that the formation resistivity correction method in related technologies has poor correction effect and low accuracy of formation resistivity measurement under high mineralization mud invasion.

[0107] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0108] It should be noted that the first acquisition module 500, the second acquisition module 502, the third acquisition module 504, the determination module 506, and the correction module 508 mentioned above correspond to steps S102 to S110 in the embodiments. The instances and application scenarios implemented by the above modules and their corresponding steps are the same, but they are not limited to the content disclosed in the above embodiments. It should be noted that the above modules, as part of the device, can run in a computer terminal.

[0109] It should be noted that the optional or preferred implementation methods of this embodiment can be found in the relevant descriptions in the embodiments, and will not be repeated here.

[0110] The aforementioned formation resistivity correction processing device may further include a processor and a memory. The first acquisition module 500, the second acquisition module 502, the third acquisition module 504, the determination module 506, the correction module 508, etc., are all stored in the memory as program modules, and the processor executes the aforementioned program modules stored in the memory to realize the corresponding functions.

[0111] The processor contains a core that retrieves the corresponding program modules from memory. One or more cores may be configured. Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory includes at least one memory chip.

[0112] According to an embodiment of this application, an embodiment of a non-volatile storage medium is also provided. Optionally, in this embodiment, the non-volatile storage medium includes a stored program, wherein, when the program is running, it controls the device containing the non-volatile storage medium to execute any of the aforementioned formation resistivity correction processing methods.

[0113] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals, and the non-volatile storage medium includes stored programs.

[0114] Optionally, during program execution, the device containing the non-volatile storage medium performs the following functions: acquiring first measurement parameters corresponding to multiple formations in the target oil well, wherein the first measurement parameters include at least: first porosity and first permeability; based on the first porosity corresponding to the multiple formations, using a first fitting algorithm to obtain a porosity calculation model corresponding to the target oil well; based on the first permeability corresponding to the multiple formations, using a second fitting algorithm to obtain a permeability calculation model corresponding to the target oil well; based on the porosity calculation model, determining the second porosity corresponding to the formation to be tested in the target oil well; and based on the permeability calculation model, determining the second permeability corresponding to the formation to be tested; and based on the second porosity and the second permeability corresponding to the formation to be tested, correcting the formation resistivity corresponding to the formation to be tested to obtain the corrected formation resistivity corresponding to the formation to be tested.

[0115] According to an embodiment of this application, an embodiment of a processor is also provided. Optionally, in this embodiment, the processor is used to run a program, wherein the program executes any of the above-described formation resistivity correction processing methods.

[0116] According to an embodiment of this application, an embodiment of a computer program product is also provided, which, when executed on a data processing device, is adapted to execute a program that initializes the correction processing method steps for formation resistivity having any of the above-described steps.

[0117] Optionally, when the aforementioned computer program product is executed on a data processing device, it is suitable to execute an initialization program having the following method steps: acquiring first measurement parameters corresponding to multiple formations in the target oil well, wherein the first measurement parameters include at least: first porosity and first permeability; based on the first porosity corresponding to the multiple formations, using a first fitting algorithm to obtain a porosity calculation model corresponding to the target oil well; based on the first permeability corresponding to the multiple formations, using a second fitting algorithm to obtain a permeability calculation model corresponding to the target oil well; based on the porosity calculation model, determining a second porosity corresponding to the formation to be tested in the target oil well; and based on the permeability calculation model, determining a second permeability corresponding to the formation to be tested; and based on the second porosity and the second permeability corresponding to the formation to be tested, correcting the formation resistivity corresponding to the formation to be tested to obtain the corrected formation resistivity corresponding to the formation to be tested.

[0118] This invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs the following steps: acquiring first measurement parameters corresponding to multiple formations in a target oil well, wherein the first measurement parameters include at least: first porosity and first permeability; based on the first porosity corresponding to the multiple formations, using a first fitting algorithm to obtain a porosity calculation model corresponding to the target oil well; based on the first permeability corresponding to the multiple formations, using a second fitting algorithm to obtain a permeability calculation model corresponding to the target oil well; based on the porosity calculation model, determining a second porosity corresponding to the formation to be measured in the target oil well; and based on the permeability calculation model, determining a second permeability corresponding to the formation to be measured; and based on the second porosity and second permeability corresponding to the formation to be measured, correcting the formation resistivity corresponding to the formation to be measured to obtain a corrected formation resistivity corresponding to the formation to be measured.

[0119] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0120] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0121] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of modules described above can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between modules, and may be electrical or other forms.

[0122] The modules described above as separate components may or may not be physically separate. Similarly, the components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple modules. Some or all of the modules can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0123] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0124] If the aforementioned integrated modules are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable non-volatile storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a non-volatile storage medium and includes several instructions 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 of the various embodiments of this invention. The aforementioned non-volatile storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0125] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for correcting formation resistivity, characterized in that, include: Obtain first measurement parameters corresponding to multiple formations in the target oil well, wherein the first measurement parameters include at least: first porosity and first permeability; Based on the first porosity corresponding to the multiple formations respectively, a first fitting algorithm is used to obtain the porosity calculation model corresponding to the target oil well; Based on the first permeability corresponding to the multiple formations respectively, a second fitting algorithm is used to obtain the permeability calculation model corresponding to the target oil well; Based on the porosity calculation model, the second porosity corresponding to the formation to be tested in the target oil well is determined; and based on the permeability calculation model, the second permeability corresponding to the formation to be tested is determined. Based on the second porosity and second permeability of the stratum to be tested, the formation resistivity of the stratum to be tested is corrected to obtain the corrected formation resistivity of the stratum to be tested. The step of correcting the formation resistivity corresponding to the formation under test based on the second porosity and second permeability to obtain the corrected formation resistivity includes: acquiring the mud resistivity, cementation index, and saturation index of the formation under test; and correcting the formation resistivity based on the formation resistivity, mud resistivity, second porosity, second permeability, cementation index, and saturation index of the formation under test in the following manner to obtain the corrected formation resistivity: ,in, This represents the corrected formation resistivity. The measured resistivity of the formation is represented by , m represents the cementation index, and n represents the saturation index. This indicates the second penetration rate. This indicates the second porosity. This represents the mud intrusion constant factor corresponding to the formation being tested. This indicates the resistivity of the mud.

2. The method according to claim 1, characterized in that, The porosity calculation model for the target oil well is obtained by using a first fitting algorithm based on the first porosity corresponding to the multiple formations, including: Obtain the first logging density corresponding to each of the multiple formations; Based on the first porosity and the first logging density corresponding to the multiple formations respectively, the first fitting algorithm is used to obtain the porosity calculation model.

3. The method according to claim 1, characterized in that, The determination of the second porosity corresponding to the formation to be tested in the target oil well based on the porosity calculation model includes: Obtain the second logging density corresponding to the formation to be tested; Based on the second logging density, the porosity calculation model is used to determine the second porosity corresponding to the formation to be tested.

4. The method according to claim 1, characterized in that, The permeability calculation model for the target oil well is obtained by using a second fitting algorithm based on the first permeability corresponding to the multiple formations, including: Obtain the first total porosity, the first movable fluid porosity, and the first bound fluid porosity corresponding to the multiple formations respectively; Based on the first total porosity, the first movable fluid porosity, the first bound fluid porosity, and the first permeability corresponding to the multiple strata respectively, the second fitting algorithm is used to obtain the permeability calculation model.

5. The method according to claim 4, characterized in that, The permeability calculation model is obtained by using the second fitting algorithm based on the first total porosity, the first movable fluid porosity, the first bound fluid porosity, and the first permeability corresponding to the multiple formations, respectively, including: Based on the first total porosity, the first movable fluid porosity, the first bound fluid porosity, and the first permeability corresponding to the multiple strata respectively, the second fitting algorithm is used to obtain the first fitting coefficient, the second fitting coefficient, and the third fitting coefficient corresponding to the permeability calculation model. Based on the first fitting coefficient, the second fitting coefficient, and the third fitting coefficient, the permeability calculation model is constructed as follows: ； Wherein, K represents the second permeability corresponding to the stratum to be tested; This represents the second total porosity corresponding to the stratum to be tested. This indicates the second movable fluid porosity corresponding to the formation to be tested; The second bound fluid porosity corresponding to the formation to be tested is represented by f; the first fitting coefficient is represented by g; and the third fitting coefficient is represented by h.

6. The method according to claim 5, characterized in that, The determination of the second permeability corresponding to the formation to be tested based on the permeability calculation model includes: Obtain the second total porosity, the second movable fluid porosity, and the second bound fluid porosity corresponding to the formation to be tested; Based on the second total porosity, the second movable fluid porosity, and the second bound fluid porosity, the permeability calculation model is used to determine the second permeability corresponding to the formation to be tested.

7. A formation resistivity correction processing device, characterized in that, include: The first acquisition module is used to acquire first measurement parameters corresponding to multiple formations in the target oil well, wherein the first measurement parameters include at least: first porosity and first permeability; The second acquisition module is used to obtain the porosity calculation model corresponding to the target oil well based on the first porosity corresponding to the multiple formations respectively and by using a first fitting algorithm. The third acquisition module is used to obtain the permeability calculation model corresponding to the target oil well based on the first permeability corresponding to the multiple formations and using a second fitting algorithm. The determination module is used to determine the second porosity corresponding to the formation to be tested in the target oil well based on the porosity calculation model; and to determine the second permeability corresponding to the formation to be tested based on the permeability calculation model. The calibration module is used to perform calibration processing on the formation resistivity corresponding to the formation to be tested based on the second porosity and the second permeability of the formation to be tested, so as to obtain the calibrated formation resistivity corresponding to the formation to be tested. The correction module is further configured to: acquire the mud resistivity, cementation index, and saturation index corresponding to the formation to be tested; and, based on the formation resistivity, mud resistivity, second porosity, second permeability, cementation index, and saturation index corresponding to the formation to be tested, correct the formation resistivity in the following manner to obtain the corrected formation resistivity: ,in, This represents the corrected formation resistivity. The measured resistivity of the formation is represented by , m represents the cementation index, and n represents the saturation index. This indicates the second penetration rate. This indicates the second porosity. This represents the mud intrusion constant factor corresponding to the formation being tested. This indicates the resistivity of the mud.

8. A non-volatile storage medium, characterized in that, The non-volatile storage medium stores multiple instructions, which are adapted to be loaded by a processor and executed by the formation resistivity correction processing method according to any one of claims 1 to 6.

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