Oil-based mud electrical imaging logging-while-drilling device and oil-based mud electrical imaging logging-while-drilling method

Abstract

According to the oil-based mud electrical imaging logging-while-drilling device and method, a button electrode is arranged at the center position of an electrical imaging probe device which is a main component of the logging device, a shielding electrode and a return electrode are sequentially arranged outwards, and instrument constants of oil-based mud resistivity imaging logging-while-drilling can be determined by adopting a numerical simulation method and a physical experiment model method; the conversion between the measured impedance amplitude and phase information and the formation resistivity and the formation dielectric constant is realized; a fusion and splicing strategy of the formation resistivity is formulated, and fusion and splicing calculation of the full-range formation resistivity is achieved through measurement data under the multi-frequency condition; establishing a minimization objective function by adopting a neural network fitting mode, and realizing calculation of the formation resistivity, the formation dielectric constant and the polar plate gap by adopting an inversion or optimization algorithm; according to the method, the neural network algorithm is used for fitting the forward modeling response function, then the stratum resistivity, the gap and the stratum dielectric constant are obtained through the inversion or optimization algorithm, and oil and gas stratum interpretation and evaluation are better served.

Description

Technical Field

[0001] The invention relates to the technical field of geophysical logging, and in particular to an oil-based mud while-drilling electrical imaging logging device and method. Background Art

[0002] The oil exploration and development industry occupies an important position in the process of national economic and energy development. Oil and gas reservoir evaluation can provide strong technical support for oil exploration and development, among which logging technology and interpretation evaluation play an important role. Well logging, also known as geophysical logging, includes open hole wells and logging while drilling. It belongs to the field of applied geophysics and uses electromagnetic, acoustic, nuclear magnetic, radioactive, electrochemical and other measuring instruments to measure formation resistivity, dielectric constant, density, radioactivity and other parameters and their distribution in underground boreholes. It is widely used in the field of oil and gas exploration and development.

[0003] Open hole electrical imaging logging is an electrical logging method, also known as micro-resistivity scanning imaging logging. It uses a densely distributed array of button electrodes on the instrument plate to form a micro-resistivity scanning array. Combined with supporting shielding electrodes, return electrodes, adjustment and acquisition circuits and other components, it can simultaneously measure dozens to hundreds of resistivity curves, and obtain a high-definition resistivity distribution image of the well wall formation after data processing. Electrical imaging logging while drilling uses a single or multiple button electrodes embedded in the drill collar, combined with the rotation of the drill collar itself during drilling, to measure the well wall formation in different directions. After data processing, the resistivity distribution image of the well wall formation is obtained, which can be used for formation fracture and hole identification, thin layer analysis, geological structure interpretation, etc.

[0004] During drilling, the wellbore contains mud, which plays the role of lubrication, transmission, and maintaining stable pressure in the well. The commonly used mud is low-resistivity water-based mud. Water-based mud appeared the earliest and is widely used. There is also a type of mud that is a dispersed system formed by adding appropriate amounts of treatment agents, lime and weighting materials with oil (diesel or mineral oil) as the continuous phase, water or lipophilic solids (organic soil, oxidized asphalt, etc.) as the dispersed phase. The main advantages of oil-based mud are high temperature resistance, strong inhibition and resistance to salt and calcium pollution, good lubricity, and can effectively reduce damage to oil and gas layers. The resistivity value is very high. The electrical imaging logging instrument used while drilling was originally suitable for low-resistivity water-based mud. However, in quite a few cases, water-based mud is difficult to meet the requirements of field operations, such as special environments such as large inclined wells, horizontal wells, shale formations, and deep-sea reservoirs. Oil-based mud has good lubricity, high temperature and high pressure resistance, maintains well wall stability, and improves operating efficiency. It is widely used in these special environments. However, oil-based mud has oil phase as continuous phase and high resistivity, which is usually hundreds or even tens of thousands times that of water-based mud, limiting the use of existing LWD electrical imaging logging instruments suitable for water-based mud.

[0005] At present, in order to develop electrical imaging logging technology suitable for oil-based mud, measures taken include developing conductive oil-based mud, four-end point measurement method, capacitive coupling method, etc. Patent applications with application numbers 202010117447.2, 202110912504.0, and 202310569238.5 disclose a structure and imaging method of drilling electrical imaging logging instrument suitable for water-based mud. Patent application number 201910294886.8 discloses an oil-based mud microresistivity scanning imaging logging method based on a recessed electrode structure, which uses one frequency but does not consider the coupling between formation resistivity and formation dielectric constant. It is suitable for formations with relatively small resistivity and only measures formation resistivity. The measurement data is single, which is not convenient for subsequent formation interpretation and analysis, and increases the difficulty of plate mechanical manufacturing. The article entitled "Four-parameter calculation method of oil-based mud electrical imaging logging in low-resistivity formations based on depressed electrode pairs" in the 8th issue of "Acta Petrolei Sinica" in 2020 published a four-parameter calculation method of oil-based mud microresistivity scanning imaging logging based on depressed electrode pairs. It uses one frequency and calculates four parameters such as mud resistivity, mud dielectric constant, mud cake thickness and formation resistivity through equivalent model, enriching the measurement data. However, this method also does not consider the coupling between formation resistivity and formation dielectric constant. Like the patent application with application number 201910294886.8, it is only applicable to low-resistance formations. The patent application with application number 202011019657.4 is based on the application number 201910294886.8, and identifies and judges well wall cracks and holes. It also does not consider the coupling between formation resistivity and formation dielectric constant, and is only applicable to low-resistance formations. The patent application with application number 201910124532.9 announced a multi-frequency correction method based on micro-resistivity scanning imaging in an oil-based mud environment. This method also takes obtaining formation resistivity as its main purpose and does not fully consider the influence of formation capacitance coupling. The article entitled "Analysis and quantitative inversion of electrical imaging logging response in oil-based drilling fluid environment" in the Journal of China University of Petroleum (Natural Science Edition) in 2018, No. 3, analyzed the response characteristics of oil-based mud micro-resistivity scanning imaging logging, and used the inversion method to study the formation resistivity and the mud cake thickness (interval) between the electrode plate and the well wall. It is necessary to repeatedly search the forward modeling database until the objective function is met. The process is cumbersome and cannot meet the real-time requirements of logging field interpretation. In addition, there is a lack of analysis of the influence of formation dielectric constant and inversion processing methods. The patent application with application number 202211164950.9 discloses a method for determining parameters of oil-based mud electrical imaging logging. This method also mainly focuses on open hole electrical imaging logging and does not specifically involve the structure of oil-based mud while-drilling electrical imaging logging instruments and data processing methods.Through the above analysis, the existing methods have the disadvantages of high development cost, limited applicable formation conditions, inability to effectively separate mud cake / mud signals from formation signals, being affected by formation capacitance coupling, single data, and complicated data processing. In addition, they mainly focus on the open hole environment and lack oil-based mud while-drilling electrical imaging logging methods and devices. Summary of the invention

[0006] In order to overcome the defects of the above-mentioned prior art, the purpose of the present invention is to provide an oil-based mud electrical imaging logging while drilling device and method, which is suitable for the measurement and calculation of the resistivity and dielectric constant of the oil-based mud in the electrical imaging logging while drilling. Based on the electrical imaging probe device, a neural network algorithm is used to fit the forward response function, and then an inversion or optimization algorithm is used to obtain the formation resistivity, gap, and formation dielectric constant. It has the characteristics of quickly and accurately obtaining multiple parameters based on electrical imaging logging while drilling in an oil-based mud environment, which is beneficial to reservoir geological evaluation.

[0007] In order to achieve the above object, the technical solution of the present invention is:

[0008] An oil-based mud while-drilling electrical imaging logging device comprises a logging instrument body 10, an electrical imaging probe device 13 is embedded in the circumference of the logging instrument body 10, the electrical imaging probe device 13 comprises a button electrode 14 located at the center thereof, and outwardly there are a shielding electrode 15 and a return electrode 16 in sequence; an A insulating ring 17 is arranged between the button electrode 14 and the shielding electrode 15, a B insulating ring 18 is arranged between the shielding electrode 15 and the return electrode 16, an insulating belt 19 is arranged between the return electrode 16 and the main body of the logging instrument 10, and a stabilizer 20 is installed on the logging instrument body 10 around the electrical imaging probe device 13.

[0009] The surface area of ​​the return electrode 16 is greater than the surface area of ​​the button electrode 14 .

[0010] The button electrode 14 has a rectangular surface shape, and the shielding electrode 15 , the return electrode 16 , the A insulating ring 17 , the B insulating ring 18 , and the insulating tape 19 all have rectangular ring shapes.

[0011] The number of the electrical imaging probe devices 13 distributed in the circumferential direction of the logging tool body 10 is N, where N≥1, an integer.

[0012] The materials of the A insulating ring 17, the B insulating ring 18 and the insulating tape 19 are all non-metallic materials.

[0013] An oil-based mud electrical imaging logging while drilling method comprises the following steps:

[0014] Step A, at a certain sampling interval, the oil-based mud while-drilling electrical imaging logging device measures the well wall formation 4;

[0015] Step B, the button electrode 14 emits an A current 22 at a certain frequency, the current passes through the mud / mud cake layer 21 into the formation 4, passes through the mud / mud cake layer 21 again and flows back to the return electrode 16; at the same time, the shielding electrode 15 maintains the same potential as the button electrode 14, and emits a B current 23, similarly, the current passes through the mud / mud cake layer 21 into the formation 4, passes through the mud / mud cake layer 21 again and flows back to the return electrode 16, and the B current 23 shields the A current 22 to ensure that the A current 22 can enter the formation 4 more;

[0016] Alternatively, the button electrode 14 and the shielding electrode 15 maintain the same potential, and the outer return electrode 16 emits the A current 22 and the B current 23 at a certain frequency; the A current 22 passes through the mud / mud cake layer 21 into the formation 4, and passes through the mud / mud cake layer 21 again to flow back to the button electrode 14 in the center; at the same time, the B current 23 passes through the mud / mud cake layer 21 into the formation 4, and passes through the mud / mud cake layer 21 again to flow back to the shielding electrode 15;

[0017] Step C, measuring the amplitude A of the current 22 emitted or received by the button electrode 14 i and Phase , and at the same time measure the emission voltage amplitude A of the button electrode 14 u and Phase Or the emission voltage amplitude A of the return electrode 16 u and Phase As the drill bit 6 rotates and drills continuously, a series of current and voltage values ​​can be measured, and the measured impedance amplitude A of the button electrode 14 can be obtained by calculation. z and Phase ,Right now

[0018]

[0019]

[0020] Step D, establish a mathematical model for measuring impedance of the button electrode 14, that is,

[0021]

[0022] Among them, A z , The button electrode 14 measures the impedance amplitude and phase. G represents the geometric response of the electrical imaging probe device 13. When the structural dimensions of the electrical imaging probe device 13 are determined, G remains unchanged. f represents the frequency combination of the transmitting B current 23, which generally includes more than two groups of frequencies. When performing the logging while drilling operation, the number and size of the frequencies in f have been determined. R m is the resistivity of the oil-based mud in the wellbore 7, ε mis the dielectric constant (relative) of the oil-based mud in the wellbore 7, sd is the distance (referred to as the gap) between the button electrode 14 and the formation 4, R t is the resistivity of layer 4, ε f is the dielectric constant (relative) of the formation 4; F represents a nonlinear function describing the measurement process;

[0023] Step E: Use numerical simulation methods to establish a homogeneous formation model without a wellbore and determine the formation resistivity R t and dielectric constant ε f , the homogeneous formation model is measured using the electrical imaging probe device 13 to obtain the measured impedance amplitude A z and Phase , according to the measured impedance amplitude A z , Phase and the determined formation resistivity R t and dielectric constant ε f , the instrument constant K is obtained through calibration;

[0024] Alternatively, a physical model is constructed in a laboratory environment, that is, the container 24 is filled with aqueous solution, the salinity of the aqueous solution is changed, and the resistivity and dielectric constant of the aqueous solution are measured using an impedance grid analyzer to obtain an equivalent formation resistivity R t and dielectric constant ε f The logging instrument body 10 is placed in the aqueous solution, and the electrical imaging probe device 13 of the logging instrument body 10 is used to measure the aqueous solution, and the measured impedance amplitude A is obtained by calculation. z and Phase ; Finally, according to the measured impedance amplitude A z and Phase and the known formation resistivity R t and dielectric constant ε f , the instrument constant K is obtained through calibration;

[0025] Step F, using n frequency values ​​and introducing n+1 resistivity threshold points R arranged from small to large thi (i=1,2,…,n+1), calculate the real part Z of the measured impedance of the button electrode 14 at each frequency ri The corresponding resistivity R ri and the impedance magnitude ξ at the lowest frequency a1 , where the real part of the measured impedance Z ri The corresponding resistivity R ri The following formula is used for calculation:

[0026]

[0027] The impedance ratio is calculated using the following formula:

[0028] ξa =KZ a (5)

[0029] The following strategy is used for fusion processing of formation resistivity, namely:

[0030] ①In the interval [R min ,R th1 ], using the resistivity R corresponding to the highest frequency ri Characterizes the change in formation resistivity, where R min is the minimum value of formation resistivity;

[0031] ②In the interval [R th1 ,R th2 ], using the resistivity R corresponding to the second highest frequency ri Characterize formation resistivity changes;

[0032] ③In the interval [R th2 ,R th3 ], using the resistivity R corresponding to the third highest frequency ri Characterize formation resistivity changes;

[0033] ④ And so on, until in the interval [R th,n+1 ,R max ], using the impedance ratio ξ corresponding to the lowest frequency a The amplitude of represents the change of formation resistivity, where R max is the maximum value of formation resistivity;

[0034] Execute steps ① to ④ in sequence to achieve the fusion processing of the full range of formation resistivity;

[0035] Alternatively, select 1 frequency f in the higher range from the n frequency values s , set a resistivity threshold point R ths , calculate the real part of the measured impedance Z at the selected frequency rs The corresponding resistivity R rs And the equivalent resistivity R eqs , where the real part of the measured impedance Z rs The corresponding resistivity R rs Using formula (5),

[0036]

[0037] Equivalent resistivity R eqs The following formula is used for calculation:

[0038]

[0039] Then the following strategy is used to carry out the fusion processing of formation resistivity, namely:

[0040] ①In the interval [R min ,R ths ], the real part of the measured impedance at the selected frequency corresponds to the resistivity R rs Characterizes the change in formation resistivity, where R min is the minimum value of formation resistivity;

[0041] ②In the interval [R ths ,R max ], using the equivalent resistivity R at the selected frequency eqs Characterizes the change in formation resistivity, where R max is the maximum value of formation resistivity;

[0042] By executing the fusion processing steps ①-② in sequence, the fusion processing of the full range of formation resistivity can also be achieved;

[0043] Step G, establish the forward flow chart of logging response. From left to right, the adopted frequency value gradually increases, and the mud surface is established at each frequency value. The horizontal and vertical coordinates of the mud surface are mud resistivity R m , the dielectric constant of mud ε m , the number of values ​​is m1, m2 respectively, thus obtaining m1×m2 mud points. At each mud point, a three-dimensional coordinate system is established, with the coordinate axes being the gap sd, the formation resistivity R t , formation dielectric constant ε f , the number of values ​​of the three are m3, m4, and m5 respectively. Thus, a three-dimensional grid containing m3×m4×m5 data points is established at each mud point. For each three-dimensional grid, the numerical simulation method of step E is used to carry out batch forward calculation of well logging response to obtain the corresponding three-dimensional impedance amplitude data volume and three-dimensional impedance phase data volume;

[0044] Step H, establish a method for determining mud parameters. During the logging while drilling operation, when the logging instrument body 10 passes through the casing 8, the electrical imaging probe device 13 emits current signals at various frequency points, and simultaneously collects the voltage, current amplitude and phase signals, and calculates the amplitude A of the measured impedance at this time. z and Phase , the mud resistivity and mud dielectric constant are calculated using the measured impedance, that is,

[0045]

[0046] Where, ω is the angular frequency of the emission current, satisfying ω=2πf;

[0047] Alternatively, during the logging while drilling operation, each time a certain distance or time is drilled, the shielding electrode 15 on the electrical imaging probe device 13 no longer emits the shielding B current 23, but acts as a return electrode, that is, the emission A current 22 of the button electrode 14 no longer flows back to the return electrode 16, but flows back to the shielding electrode 15; since the emission A current 22 is no longer shielded and the current loop path is shorter, at this time, the measured impedance of the button electrode 14 comes from the mud, so the mud resistivity and dielectric constant are determined using formulas (7) and (8);

[0048] Step I: After determining the mud resistivity and dielectric constant at each frequency, select the corresponding measured impedance amplitude and phase forward modeling data volume, and the corresponding divided formation resistivity R t , gap sd and formation dielectric constant ε f The data is then transformed into the corresponding formation resistivity R using machine learning algorithms, including single-layer or multi-layer neural networks. t , gap sd and formation dielectric constant ε f As input, the impedance amplitude A is measured z and Phase As output, respectively, or both as output, by setting the number of neurons in the hidden layer, the number of layers, the activation function from the input layer to the hidden layer, from the hidden layer to the output layer, and between the hidden layers, continuous iteration optimization, to obtain the optimal neural network model, from the optimal neural network model to extract the weights, thresholds, and neuron activation functions between the layers, composed of the display fitting function expression h(R t ,sd,ε f ) and g(R t ,sd,ε f ), or k(R t ,sd,ε f ),Right now

[0049] A z =h(R t ,sd,ε f ) (9)

[0050]

[0051] or

[0052]

[0053] Step J, obtaining the measured impedance amplitude A at each frequency z and Phase After fitting the function, in order to obtain the formation resistivity R t , gap sd and formation dielectric constant ε f , construct the minimization objective function C(x):

[0054]

[0055] Among them, the vector x consists of the gap, the formation resistivity R at each frequency t and the formation dielectric constant ε f which are values to be determined; S(x) is a combined form of the fitting functions h, g, or k obtained in step G, and the vector y * consists of the impedance amplitude and phase of the electrical imaging probe device 13 at multiple frequencies in the actual measurement data, which is the actual reference value, and the vector x p is the value of the vector x after the previous iteration in the optimization iteration process, which is the reference value; W d and W p are preset weight matrices used to adjust the influence of each difference part in C(x), and ζ is a preset regularization coefficient; the optimization iteration process of the function C(x) is implemented by using the Gauss-Newton iteration algorithm, the particle swarm optimization algorithm, or a combination of the two; when C(x) < tol (tol is a preset error threshold) or the maximum number of iterations is reached, the vector x at this time is the optimal solution, and the calculation of the formation resistivity R t the gap sd, and the formation dielectric constant ε f is completed;

[0056] Step K: Based on the above steps, calculate the formation resistivity, gap, and formation dielectric constant corresponding to the measured impedance amplitude and phase of the electrical imaging probe device 13 one by one. According to the drilling speed and rotational angular velocity of the logging tool body 10, perform image generation and display processing on the calculation data, and then the formation resistivity image, gap image, and formation dielectric constant image of the wellbore formation can be obtained.

[0057] Compared with the prior art, the advantages of the present invention are as follows:

[0058] (1) The oil-based mud logging-while-drilling electrical imaging logging device of the present invention adopts button electrodes, shield electrodes, return electrodes, and insulation design, can work in an oil-based mud environment, can accurately obtain multiple parameters, provides a dedicated device for logging-while-drilling electrical imaging, and the obtained parameters are used to fit the forward response function by a neural network algorithm, and then the formation resistivity, gap, and formation dielectric constant are obtained by using an inversion or optimization algorithm.

[0059] (2) Step E can determine the instrument constants of the oil-based mud logging-while-drilling resistivity imaging logging by using numerical simulation methods and physical experiment model methods, and realize the conversion between the measured impedance amplitude and phase information and the formation resistivity and formation dielectric constant.

[0060] (3) Step F formulates a fusion and splicing strategy for formation resistivity, and uses the measurement data under multi-frequency conditions to realize the fusion and splicing calculation of the full range of formation resistivity.

[0061] (4) Steps G and H formulated the forward modeling database calculation strategy for oil-based mud electrical imaging logging while drilling and two methods for determining mud resistivity and mud dielectric constant applicable to oil-based mud electrical imaging logging while drilling, laying the foundation for the subsequent inversion optimization calculation of formation resistivity, formation dielectric constant and plate gap.

[0062] (5) In steps I and J, a neural network fitting method is used to establish a response function for measuring impedance amplitude and phase, and a minimization objective function is established. An inversion or optimization algorithm is used to calculate formation resistivity, formation dielectric constant, and plate gap.

[0063] In summary, the present invention has formulated a forward data packet calculation strategy for oil-based mud electrical imaging logging while drilling, and has specifically proposed a measurement and calculation method for the resistivity and dielectric constant of oil-based mud suitable for electrical imaging logging while drilling. It is proposed to use a neural network algorithm to fit the forward response function, and then use an inversion or optimization algorithm to obtain the formation resistivity, gap, and formation dielectric constant, which can better serve the interpretation and evaluation of oil and gas exploration and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is an overall schematic diagram of the implementation of the oil-based mud while drilling electrical imaging logging work of the present invention.

[0065] Figure 2 Schematic diagram of the well logging instrument body 10 and the electrical imaging probe device 13 in the present invention, wherein Figure 2 (a) is a schematic diagram of the logging tool body 10; Figure 2 (b) is a schematic diagram of a circular electrical imaging probe device 13, Figure 2 (c) is a schematic diagram of a circular electrical imaging probe device 13, Figure 2 (d) is a schematic diagram of the distribution of the electrical imaging probe device 13 in the circumferential direction of the logging instrument body 10.

[0066] Figure 3 Schematic diagram of the working principle of oil-based mud electrical imaging logging while drilling, where Figure 3 (a) is the current emitted by the button electrode 14; Figure 3 (b) in FIG. 1 is the emission current of the return electrode 16 .

[0067] Figure 4 It is a homogeneous stratum model for numerical simulation.

[0068] Figure 5 is the laboratory mean formation model.

[0069] Figure 6is the forward modeling flow chart of well logging response, where Figure 6 (a) is the forward modeling flow chart of well logging response. Figure 6 (b) in the figure is a three-dimensional coordinate system.

[0070] Figure 7 is a schematic diagram of the neural network for obtaining the measured impedance amplitude and phase fitting function, where Figure 7 (a) is a schematic diagram of impedance amplitude fitting. Figure 7 (b) is a schematic diagram of impedance phase fitting. Figure 7 (c) Schematic diagram of simultaneous fitting of impedance amplitude and phase.

[0071] Figure 8 is the result of the fusion processing method to characterize the formation resistivity change, where Figure 8 (a) is the result of measuring impedance splicing. Figure 8 (b) is the resistivity splicing result calculated from the real part of impedance; Figure 8 (c) is the equivalent resistivity splicing result; Figure 8 (d) is the splicing result of low-frequency impedance ratio; Figure 8 (e) in the figure is the splicing result of high-frequency impedance.

[0072] Fig. 9 The mud parameters are calculated by measuring inside the casing. Fig. 9 (a) is a schematic diagram of mud resistivity. Fig. 9 (b) is a schematic diagram of the dielectric constant results.

[0073] Fig.10 This is a schematic diagram of the results of calculating the mud resistivity and dielectric constant by changing the current emission mode. Fig.10 (a) is a schematic diagram of mud resistivity. Fig.10 (b) is a schematic diagram of the dielectric constant results.

[0074] Fig.11 The calculation result curves of formation resistivity, gap, high and low frequency dielectric constants in layered formations, where Fig.11 (a) is the calculation result of fixed gap. Fig.11 (b) in the figure is the calculation result of the variable gap.

[0075] Fig.12 It is the imaging result of formation resistivity, gap, high and low dielectric constants in inclined formations. DETAILED DESCRIPTION

[0076] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0077] Combined with the above Figure 1 The overall schematic diagram of the implementation of the work in the present invention proposes an oil-based mud while drilling electrical imaging logging method and a logging device thereof, wherein the logging device proposed by the present invention includes a logging instrument body 10. Figure 2 As shown in (a), an electric imaging probe device 13 is embedded in the circumference of the logging tool body 10, which is characterized in that: Figure 2 As shown in (b), the electrical imaging probe device 13 includes a button electrode 14 located at the center thereof, and outwardly there are a shielding electrode 15 and a return electrode 16. An A insulating ring 17 is provided between the button electrode 14 and the shielding electrode 15, an B insulating ring 18 is provided between the shielding electrode 15 and the return electrode 16, and an insulating belt 19 is provided between the return electrode 16 and the main body of the logging instrument 10. A stabilizer 20 is installed on the logging instrument main body 10 around the electrical imaging probe device 13, so that the logging instrument main body 10 is as close to the wellbore axis as possible to ensure the measurement signal quality of the probe device 13.

[0078] The surface area of ​​the return electrode 16 is larger than that of the button electrode 14 to ensure that the contact mud impedance of the return electrode 16 is sufficiently small during the signal acquisition.

[0079] like Figure 2 As shown in (c), the surface shape of the button electrode 14 is rectangular, and the surface shapes of the shielding electrode 15, the return electrode 16, the A insulating ring 17, the B insulating ring 18, and the insulating belt 19 are all rectangular rings. In fact, the surface shapes of these electrodes and insulating rings / belts can be a combination of any shapes.

[0080] The number of the electrical imaging probe devices 13 distributed in the circumferential direction of the logging tool body 10 is N (N≥1, an integer). Figure 2 As shown in (d), N can be 1, 2 (180° symmetrical distribution), 3 (120° equally spaced distribution), 4 (90° equally spaced distribution), etc. In fact, the best N value can be selected according to the actual situation based on the drilling speed of the drill bit 6 and the rotation speed of the logging tool body 10. The number of stabilizers 20 is generally set to 3.

[0081] The materials of the A insulating ring 17 , the B insulating ring 18 and the insulating tape 19 are all non-metallic materials, such as wear-resistant ceramics, rubber, etc. The area and embedding depth of the insulating tape 19 are large enough to ensure good insulation between each electrode and the main body of the logging instrument 10 .

[0082] The present invention provides an oil-based mud electrical imaging logging while drilling method, comprising the following steps:

[0083] Step A, driven by the drilling of the drill bit 6, the oil-based mud electrical imaging logging device rotates and drills continuously. The diameter of the main body 10 of the electrical imaging logging device is slightly larger than the diameter of the drill pipe 5. This can reduce the impact of the mud in the well on the measurement signal and better detect the formation information. At a certain sampling interval, the oil-based mud electrical imaging logging device measures the well wall formation 4.

[0084] The entire oil-based mud while drilling electrical imaging logging device is as follows Figure 1 As shown, a derrick 2 and a drilling operation platform 3 are installed at appropriate positions on the ground (sea surface) 1. The derrick 2 mainly supports, lifts and lowers equipment, provides operating space, etc. The drilling operation platform 3 mainly performs drilling, maintenance, safety protection, etc. In addition, the ground is also equipped with mud pools and their accessories (not shown). By running the drilling operation platform 3, in the ground 4, the drill bit 6 is powered by the rotation of the drill pipe 5 or the downhole motor (not shown) to continuously drill through the formation 4. By controlling the drilling direction of the drill bit 6, a wellbore 7 is formed in the formation 4, and its trajectory can be vertical, inclined, horizontal, etc. or a combination of them. Mud is filled in the wellbore 7, and the mud here is oil-based mud. Casing 8 may be installed at the wellbore port or any position, which mainly plays a role in maintaining the stability of the wellbore. Due to the limitation of the drilling depth, a joint 9 is also installed on the drill pipe 5 to play a role in connection, sealing, and anti-wear. At a certain position at the rear end of the drill bit 6, a measurement while drilling or logging while drilling tool or a logging instrument body 10 is installed, which can provide information support for the drilling state of the drill bit 6 mainly by measuring the original information of the fluid and formation in the well, or transmitting and receiving acoustic waves, electromagnetic and other signals. Here, the logging instrument body 10 is a logging instrument for electrical imaging while drilling. In addition, on the ground 1, there is also a microcomputer control system 11, which transmits information with the drilling operation platform 3 and the logging instrument body 10 through a wired or wireless method 12, and has functions such as information storage, display, and processing.

[0085] Step B, the specific use process of oil-based mud electrical imaging logging while drilling is as follows Figure 3 Due to the different curvature radii between the logging instrument body 10 and the wellbore 7, the presence of the stabilizer 20, the irregularity of the wellbore 10, and other factors, there is mud / mud cake 21 between the probe device 13 and the formation 4. Figure 3 As shown in (a) in the figure, the button electrode 14 emits an A current 22 at a certain frequency, which passes through the mud / mud cake layer 21 into the formation 4, and then passes through the mud / mud cake layer 21 again to flow back to the return electrode 16. At the same time, the shielding electrode 15 maintains the same potential as the button electrode 14 and emits a B current 23, which also passes through the mud / mud cake layer 21 into the formation 4, and then passes through the mud / mud cake layer 21 again to flow back to the return electrode 16. The B current 23 shields the A current 22 to ensure that the A current 22 can enter the formation 4 more.

[0086] Alternatively, Figure 3 As shown in (b), the button electrode 14 and the shielding electrode 15 maintain the same potential, and the outer return electrode 16 emits A current 22 and B current 23 at a certain frequency. The A current 22 passes through the mud / mud cake layer 21 into the formation 4, and then passes through the mud / mud cake layer 21 again to flow back to the button electrode 14 in the center; at the same time, the B current 23 passes through the mud / mud cake layer 21 into the formation 4, and then passes through the mud / mud cake layer 21 again to flow back to the shielding electrode 15. Since the resistivity of the mud / mud cake layer 21 is very high, the frequency range of the A current 22 is generally several megahertz to several hundred megahertz, and the frequency number is n, n≥2.

[0087] Step C, measuring the amplitude A of the current 22 emitted or received by the button electrode 14 i and Phase At the same time, the emission voltage amplitude A of the button electrode 14 is measured u and Phase Or the emission voltage amplitude A of the return electrode 16 u and Phase As the drill bit 6 continuously rotates and drills, a series of current and voltage values ​​can be measured, and the measured impedance amplitude A of the button electrode 14 can be obtained by calculation. z and Phase Right now

[0088]

[0089]

[0090] Step D, according to Figure 3 In the measurement process shown, the measured impedance of the button electrode 14 is the comprehensive contribution of the instrument structure, wellbore, mud / mud cake, and formation. Therefore, a mathematical model for the measured impedance of the button electrode 14 is established, namely:

[0091]

[0092] Among them, A z , The button electrode 14 measures the impedance amplitude and phase. G represents the geometric response of the electrical imaging probe device 13. When the structural dimensions of the electrical imaging probe device 13 are determined, G remains unchanged. f represents the frequency combination of the transmitting B current 23, which generally includes more than two groups of frequencies. When performing the logging while drilling operation, the number and size of the frequencies in f have been determined. R m is the resistivity of the oil-based mud in the wellbore 7, ε m is the dielectric constant (relative) of the oil-based mud in the wellbore 7, sd is the distance (referred to as the gap) between the button electrode 14 and the formation 4, R t is the resistivity of layer 4, εf is the dielectric constant (relative) of the formation 4; F represents a nonlinear function describing the measurement process, which cannot be obtained directly. m , ε m ,sd,R t , ε f is an unknown parameter. In order to explain the characteristics of stratum changes, R t It is a parameter that must be obtained, that is, to obtain the formation resistivity image. In order to provide more accurate and rich geological information in the oil-based mud environment, sd, ε f It is also a parameter that needs to be obtained.

[0093] Step F, such as Figure 4 As shown in the figure, a numerical simulation method is used to establish a homogeneous formation model without a wellbore and determine the formation resistivity R t and dielectric constant ε f , the homogeneous formation model is measured using the electrical imaging probe device 13 to obtain the measured impedance amplitude A z and Phase According to the measured impedance amplitude A z , Phase and the determined formation resistivity R t and dielectric constant ε f , the instrument constant K is obtained through calibration.

[0094] Alternatively, in a laboratory setting, a physical model can be constructed, e.g. Figure 5 As shown, a container 24 of suitable size, such as a PVC cylinder, is used, which is filled with aqueous solution. By gradually adding NaCl salt from distilled water, the mineralization of the aqueous solution is changed, thereby changing the resistivity and dielectric constant of the aqueous solution. At the same time, the resistivity and dielectric constant of the aqueous solution are measured using an impedance grid analyzer to be used to calculate the equivalent formation resistivity R t and dielectric constant ε f The logging instrument body 10 is placed in the aqueous solution, and the electrical imaging probe device 13 of the logging instrument body 10 is used to measure the aqueous solution. The measured impedance amplitude A is obtained by calculation. z and Phase Finally, according to the measured impedance amplitude A z and Phase and the known formation resistivity R t and dielectric constant ε f , the instrument constant K is obtained through calibration. Using the instrument constant K, the measured impedance data can be converted into resistivity and dielectric constant.

[0095] Step F, in order to describe the formation resistivity R t , adopting n frequency values ​​and introducing n+1 resistivity threshold points R arranged from small to large thi(i=1, 2, ..., n+1) Calculate the real part Z of the measured impedance of the button electrode 14 at each frequency ri The corresponding resistivity R ri and the impedance magnitude ξ at the lowest frequency a1 , where the real part of the measured impedance Z ri The corresponding resistivity R ri The following formula is used for calculation:

[0096]

[0097] The impedance ratio is calculated using the following formula:

[0098] ξ a =KZ a 5)

[0099] The following strategy is used for fusion processing of formation resistivity, namely:

[0100] ①In the interval [R min ,R th1 ], using the resistivity R corresponding to the highest frequency ri Characterizes the change in formation resistivity, where R min It is the minimum value of formation resistivity and can be set to values ​​such as 0.2Ωm.

[0101] ②In the interval [R th1 ,R th2 ], using the resistivity R corresponding to the second highest frequency ri Characterize formation resistivity changes;

[0102] ③In the interval [R th2 ,R th3 ], using the resistivity R corresponding to the third highest frequency ri Characterize formation resistivity changes;

[0103] ④ And so on, until in the interval [R th,n+1 ,R max ], using the impedance ratio ξ corresponding to the lowest frequency a The amplitude of represents the change of formation resistivity, where R max It is the maximum value of the formation resistivity and can be set to a value such as 20000Ωm.

[0104] By executing steps ① to ④ in sequence, the fusion processing of the full range of formation resistivity can be realized.

[0105] Alternatively, to describe the formation resistivity R t , select a frequency f in the higher range from n frequency values s , set a resistivity threshold point R ths, calculate the real part of the measured impedance Z at the selected frequency rs The corresponding resistivity R rs And the equivalent resistivity R eqs , where the real part of the measured impedance Z rs The corresponding resistivity R rs The same calculation method as formula (4) is used, that is,

[0106]

[0107] Equivalent resistivity R eqs The following formula is used for calculation:

[0108]

[0109] Then the following strategy is used to carry out the fusion processing of formation resistivity, namely:

[0110] ①In the interval [R min ,R ths ], the real part of the measured impedance at the selected frequency corresponds to the resistivity R rs Characterizes the change in formation resistivity, where R min It is the minimum value of formation resistivity and can be set to values ​​such as 0.2Ωm.

[0111] ②In the interval [R ths ,R max ], using the equivalent resistivity R at the selected frequency eqs Characterizes the change in formation resistivity, where R max It is the maximum value of the formation resistivity and can be set to a value such as 20000Ωm.

[0112] By executing steps ①-② in sequence, the fusion processing of the full range of formation resistivity can also be achieved.

[0113] In order to better characterize the changes in formation resistivity, and also to obtain the gap and formation dielectric constant, so as to better interpret the geological phenomena, the following steps are taken.

[0114] Step G, establish Figure 6 (a) shows the forward modeling flow chart of the well logging response. From left to right, the frequency values ​​used gradually increase (the figure shows 3 frequency values. In actual operation, the number of frequencies used is n, satisfying n ≥ 2). A mud surface is established at each frequency value. The horizontal and vertical coordinates of the mud surface are the mud resistivity R m , the dielectric constant of mud ε m , the number of values ​​is m1 and m2 respectively, thus obtaining m1×m2 mud points. At each mud point, establish Figure 6 (b) shows the three-dimensional coordinate system, where the coordinate axes are the gap sd, the formation resistivity R t, formation dielectric constant ε f , the number of values ​​of the three are m3, m4, and m5 respectively. In this way, a three-dimensional grid containing m3×m4×m5 data points is established at each mud point. For each three-dimensional grid, the forward calculation of well logging response is carried out in batches using the numerical simulation method described above, and the corresponding impedance amplitude data volume (three-dimensional) and impedance phase data volume (three-dimensional) can be obtained. It should be noted that the above parameters can be divided into linear equal intervals or logarithmic equal intervals, and finally hundreds of thousands to tens of millions of forward calculation values ​​can be obtained. The specific number is related to the value range and division interval of each parameter.

[0115] Step H: In order to calculate the formation resistivity, gap, and formation dielectric constant based on the above-mentioned logging response data body when processing actual logging data, it is first necessary to establish a method for determining mud parameters at multiple frequencies. To achieve this goal, during the logging while drilling operation, when the logging instrument body 10 passes through the casing 8, the electrical imaging probe device 13 emits current signals at various frequency points, and simultaneously collects the voltage, current amplitude and phase signals, and calculates the amplitude A of the measured impedance at this time. z and Phase Since the casing is made of metal, its resistivity is much lower than that of mud, which isolates the current signal from entering the formation. The measured impedance mainly comes from the contribution of mud. At this time, the measured impedance can be used to calculate the mud resistivity and mud dielectric constant, that is,

[0116]

[0117] Wherein, ω is the angular frequency of the emission current, satisfying ω=2πf.

[0118] Alternatively, during the logging while drilling operation, each time a certain distance or time is drilled, the shielding electrode 15 on the electrical imaging probe device 13 no longer emits the shielding B current 23, but acts as a return electrode, that is, the emission A current 22 of the button electrode 14 no longer flows back to the return electrode 16, but flows back to the shielding electrode 15. Since the emission A current 22 is no longer shielded and the current loop is shorter, at this time, the measurement impedance of the button electrode 14 mainly comes from the mud, so the mud resistivity and dielectric constant can be determined using formulas (7) and (8).

[0119] Step I: After determining the mud resistivity and dielectric constant at each frequency, Figure 6 In the , select the corresponding measured impedance amplitude and phase forward modeling data volume, and the corresponding divided formation resistivity R t , gap sd and formation dielectric constant ε f Data. Figure 7As shown in the figure, a machine learning algorithm, such as a single-layer or multi-layer neural network, is used to convert the formation resistivity R corresponding to the forward modeling data volume into t , gap sd and formation dielectric constant ε f As input, the impedance amplitude A is measured z and Phase As output [ Figure 7 (a) Figure 7 (b)] or both as output [ Figure 7 (c) in the figure, by setting the number of neurons in the hidden layer, the number of layers, the activation functions from the input layer to the hidden layer, from the hidden layer to the output layer, and between the hidden layers, the optimal neural network model can be obtained through continuous iterative optimization. The weights and thresholds of the connections between the layers are extracted from the optimal neural network model, and the neuron activation function is combined to form the display fitting function expression h(R t ,sd,ε f ) and g(R t ,sd,ε f )[ Figure 7 (a) Figure 7 (b)], or k(R t ,sd,ε f )[ Figure 7 (c)], i.e.

[0120] A z =h(R t ,sd,ε f ) (9)

[0121]

[0122] or

[0123]

[0124] Step J, obtaining the measured impedance amplitude A at each frequency z and Phase After fitting the function, in order to obtain the formation resistivity R t , gap sd and formation dielectric constant ε f , construct the minimization objective function C(x):

[0125]

[0126] The vector x is composed of the gap, the formation resistivity R at each frequency t and the formation dielectric constant ε f S(x) is the combination of the fitting functions h, g or k obtained in step H. The vector y *It consists of the impedance amplitude and phase of the electrical imaging probe device 13 at multiple frequencies in the actual measurement data, which is the actual reference value, vector x p is the value of vector x after the previous iteration during the optimization iteration process, which is the reference value. W d 、W p is a preset weight matrix used to adjust the influence of each difference part in C(x). ζ is a preset regularization coefficient. The optimization iteration process of function C(x) can be implemented by using the Gauss-Newton iteration algorithm, the particle swarm optimization algorithm, or a combination of the two. When C(x) < tol (tol is a preset error threshold) or the maximum number of iterations is reached, the vector x at this time is the optimal solution, and the calculation of the gap sd, formation resistivity R t and formation dielectric constant ε f is completed.

[0127] Step L: Based on the above steps, calculate the formation resistivity, gap, and formation dielectric constant corresponding to the measured impedance amplitude and phase of the electrical imaging probe device 13 one by one. According to the drilling speed and rotational angular velocity of the logging tool body 10, perform image generation and display processing on the calculated data, and then the formation resistivity image, gap image, and formation dielectric constant image of the wellbore formation can be obtained.

[0128] To illustrate and verify the effects and benefits of the content of the present invention, the following several embodiments are studied.

[0129] Embodiment 1

[0130] To illustrate the technical content of the invention, the working process shown in (a) in Figure 3 is adopted. The formation resistivity gradually increases from 0.2 Ωm to 20000 Ωm, and the frequencies are 0.1 MHz, 1 MHz, 10 MHz, and 100 MHz respectively. Combining with the instrument constant, the measured impedance rate is calculated. The resistivity is calculated from the real part of the impedance, the equivalent resistivity, the splicing results of the real part of the multi-frequency impedance and the low-frequency impedance rate, and the splicing results of the real part of the high-frequency impedance and the equivalent resistivity are shown in (a)-(e) in Figure 8 respectively. It can be found that Figure 8 in (a), as the formation resistivity increases, the change amplitude of the measured impedance rate at the 4 frequencies is very small. For example, the result at 0.1 MHz can only characterize the change of the formation resistivity above 1000 Ωm, indicating that it is no longer possible to characterize the change of the formation resistivity only by the amplitude of voltage and current like the low-frequency water-based mud electrical imaging logging. The phase change of voltage and current needs to be considered. Figure 8In (b), after considering the phase change, the real part resistivity of the impedance at the four frequencies shows good sensitivity in different formation resistivity ranges, especially the result of 100MHz can well characterize the change of formation resistivity below 10Ωm. It should be noted that when the formation resistivity increases, the real part resistivity of the impedance reverses, that is, the change trend is non-monotonic and can no longer characterize the change of formation resistivity. Figure 8 In (c), contrary to the change in the resistivity of the real part of the impedance, the equivalent resistivity at the four frequencies can well characterize the change in the resistivity of the formation in the high-resistance area, especially the result of 100 MHz can increase monotonically in the area above 10 Ωm. Figure 8 (d) in the figure shows the fusion processing result using the real part resistivity of impedance at 1MHz, 10MHz, 100MHz and the impedance ratio at 0.1MHz. Figure 8 (e) shows the fusion processing results of the real resistivity and equivalent resistivity of the impedance at 100 MHz. It can be found that although it cannot be completely quantitative, both fusion processing methods can characterize the monotonically increasing change of the formation resistivity from small to large, verifying the effectiveness of the multi-frequency fusion processing proposed in this patent.

[0131] Example 2

[0132] To illustrate the technical content of the invention, when the logging instrument body 10 passes through the metal casing, the electric imaging probe device 13 is used to measure the resistivity and dielectric constant of the mud in the well. The results are as follows: Fig. 9 As shown. The B current 23 emitted by the button electrode 14 is affected by the high conductivity of the metal casing. After passing through the high-resistance mud / mud cake, it flows directly along the metal casing and no longer enters the formation. At this time, the measured impedance has no formation contribution, and compared with the mud / mud cake, the contribution of the metal casing is very low and can be ignored. Therefore, Fig. 9 In (a), the calculated mud resistivity and the actual mud resistivity form a straight line of 'y=x', and the calculated mud dielectric constant and the actual mud dielectric constant form a straight line of 'y=kx+b', indicating that the measurement method inside the casing can well characterize the changes in mud parameters.

[0133] Example 3

[0134] In order to illustrate the technical content of the present invention, the resistivity and dielectric constant of the mud are measured by changing the current emission mode. The results are as follows: Fig.10 As shown. When the logging instrument body 10 moves a certain distance or time in the well, the current emission mode is changed, that is, the emission B current 23 of the button electrode 14 no longer flows back to the return electrode 16, but flows back to the electrode 15 which is closer. At this time, there is no shielding effect of shielding the A current 22. At this time, the radial detection depth of the B current 23 is shallower, and there is almost no contribution from the formation in the measured impedance. As shown in Fig.10 As shown in (a), at this time, the calculated mud resistivity and the actual mud resistivity also present a straight line of 'y=x', and the calculated mud dielectric constant and the actual mud dielectric constant also present a straight line of 'y=kx+b', indicating that changing the current emission method at intervals of a certain distance or time can well characterize the changes in mud parameters.

[0135] Example 4

[0136] In order to illustrate the technical content of the present invention, a layered formation test model is established, in which the formation resistivity is set to change interactively according to low and high values, the gap between the instrument and the formation is a fixed value, and at low and high frequencies, an instrument containing two electrical imaging probe devices 13 is used to perform rotary drilling and scan the well wall formation. The mud resistivity and dielectric constant are determined by the casing measurement method, and then the measurement response fitting function is determined by the neural network, and finally the formation parameters are calculated by the Gauss-Newton inversion algorithm. Fig.11 (a) in the figure gives the calculation results. From the 1st to the 4th track, they are the formation resistivity, gap, formation low-frequency dielectric constant, and formation high-frequency dielectric constant. The two curves in each track correspond to the measurement results of the two probes. It can be found that the formation resistivity curve and the formation dielectric constant curve at two frequencies can reflect the changing characteristics of the layered formation, and the two gap curves are almost overlapped and remain unchanged.

[0137] In order to further illustrate the technical advantages of the present invention, in the above test model, the gap between the instrument and the formation is changed and the high and low values ​​change with the depth, and the formation resistivity range is expanded. The calculation is performed using the same method as above. Fig.11 (b) in the figure gives the calculation results. The meaning of each curve is the same as Fig.11 (a) is consistent. It can be found that even if the gap changes and the contrast between adjacent layers increases, the formation resistivity curve and the formation dielectric constant curve can also reflect the formation change characteristics. At the same time, the gap curve can also reflect the change characteristics of the distance between the instrument and the well wall formation, which well verifies the effectiveness of the technical content of the present invention.

[0138] Example 5

[0139] In order to illustrate the technical content of the present invention, a tilt test model of a layered formation is established. In this formation model, the logging instrument body 10 rotates and drills at a 60° tilt angle. During the drilling process, two low and high measurement frequencies are still used, and two electrical imaging probes rotate to scan the well wall formation. The mud resistivity and dielectric constant are determined by changing the current emission mode, and then the measurement response fitting function is determined by using a neural network. Finally, the formation parameters are calculated using the Gauss-Newton inversion algorithm. According to the drilling speed and the rotation angular velocity, the data of the two probes are arranged into an image pixel matrix according to the longitudinal depth and circumferential angle, and finally the formation imaging is performed. Fig.12 The imaging results are given. From the 1st to the 4th track, they are formation resistivity imaging, gap imaging, formation low-frequency dielectric constant imaging, and formation high-frequency dielectric constant imaging. Bright colors represent high values, and dark colors represent low values. It can be found that the imaging results can well reflect the changes in formation resistivity and formation dielectric constant. Since the drilling direction is inclined by 60°, the formation interface in the image also shows an inclined feature, which is more in line with the on-site status of logging while drilling, reflecting the advantages of the technical content of the present invention.

[0140] In summary, the present invention provides a method and device for electrical imaging logging while drilling for oil-based mud. First, a electrical imaging probe device for drilling while drilling suitable for oil-based mud environment is proposed, and its working principle and measurement impedance calculation method are described in detail. Then, a method of fusing the real part of the measured impedance and the equivalent impedance is used to characterize the change in formation resistivity. Secondly, a method for establishing a forward data package for electrical imaging logging while drilling for oil-based mud, as well as a method for measuring and calculating oil-based mud parameters are proposed. Finally, a neural network algorithm is used to establish a logging response fitting function, and an inversion or optimization algorithm is used to realize the calculation and imaging of formation resistivity, gap, and formation dielectric constant. The technical content of this invention can provide support for interpretation and evaluation services for oil and gas exploration and development.

[0141] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the protection scope of the present invention.

Claims

1. An oil-based mud electric imaging logging device while drilling, comprising a logging instrument body (10), an electric imaging probe device (13) is embedded on the circumference of the logging instrument body (10), characterized in that: The electrical imaging probe device (13) comprises a button electrode (14) located at the center thereof, and outwardly arranged in sequence are a shielding electrode (15) and a return electrode (16); an A insulating ring (17) is arranged between the button electrode (14) and the shielding electrode (15); an B insulating ring (18) is arranged between the shielding electrode (15) and the return electrode (16); an insulating belt (19) is arranged between the return electrode (16) and the body of the well logging instrument (10); and a stabilizer (20) is installed on the well logging instrument body (10) around the electrical imaging probe device (13).

2. The oil-based mud while drilling electrical imaging logging device according to claim 1, characterized in that: An oil-based mud while-drilling electrical imaging logging device, wherein the surface area of ​​the return electrode (16) is greater than the surface area of ​​the button electrode (14).

3. The oil-based mud while drilling electrical imaging logging device according to claim 1, characterized in that: The surface shape of the button electrode (14) is rectangular, and the surface shapes of the shielding electrode (15), the return electrode (16), the A insulating ring (17), the B insulating ring (18), and the insulating tape (19) are all rectangular rings.

4. The oil-based mud while drilling electrical imaging logging device according to claim 1, characterized in that: The number of the electrical imaging probe devices (13) distributed in the circumferential direction of the well logging instrument body (10) is N, where N≥1, an integer.

5. The oil-based mud electrical imaging logging while drilling device according to claim 1, characterized in that: The materials of the A insulating ring (17), the B insulating ring (18) and the insulating tape (19) are all non-metallic materials.

6. An oil-based mud electrical imaging logging while drilling method based on the logging device according to any one of claims 1 to 5, characterized in that: The following steps are involved: Step A, measuring the well wall formation (4) with an oil-based mud while-drilling electrical imaging logging device at a certain sampling interval; Step B, the button electrode (14) emits an A current (22) at a certain frequency, the current passes through the mud / mud cake layer (21) into the formation (4), passes through the mud / mud cake layer (21) again and flows back to the return electrode (16); at the same time, the shielding electrode (15) maintains the same potential as the button electrode (14) and emits a B current (23), similarly, the current passes through the mud / mud cake layer (21) into the formation (4), passes through the mud / mud cake layer (21) again and flows back to the return electrode (16), the B current (23) plays a shielding role on the A current (22), so as to ensure that the A current (22) can enter the formation (4) more; Step C, measuring the amplitude A of the current A (22) emitted or received by the button electrode (14) i and Phase At the same time, the emission voltage amplitude A of the button electrode (14) is measured u and Phase Or the emission voltage amplitude A of the return electrode (16) u and Phase As the drill bit (6) continuously rotates and drills, a series of current and voltage values ​​can be measured, and the measured impedance amplitude A of the button electrode (14) can be obtained by calculation. z and Phase Right now Step D, establishing a mathematical model for measuring impedance of the button electrode (14), namely Among them, A z , is the impedance amplitude and phase measured by the button electrode 14, G represents the geometric response of the electrical imaging probe device (13), when the structural dimensions of the electrical imaging probe device (13) are determined, G remains unchanged; f represents the frequency combination of the emission B current (23), generally including (2) or more groups of frequencies, when performing the logging while drilling operation, the number and size of the frequencies in f have been determined, R m is the resistivity of the oil-based mud in the wellbore (7), ε m is the dielectric constant of the oil-based mud in the wellbore (7), sd is the distance between the button electrode (14) and the formation (4), R t is the resistivity of the formation (4), ε f is the dielectric constant of the formation (4); F represents a nonlinear function describing the measurement process; Step E: Use numerical simulation methods to establish a homogeneous formation model without a wellbore and determine the formation resistivity R t and dielectric constant ε f , the homogeneous formation model is measured using an electrical imaging probe device (13) to obtain a measured impedance amplitude A z and Phase According to the measured impedance amplitude A z , Phase and the determined formation resistivity R t and dielectric constant ε f , the instrument constant K is obtained through calibration; Step F, using n frequency values ​​and introducing n+1 resistivity threshold points R arranged from small to large thi (i=1,2,…,n+1), calculate the real part Z of the measured impedance of the button electrode 14() at each frequency ri The corresponding resistivity R ri and the impedance magnitude ξ at the lowest frequency a1 , where the real part of the measured impedance Z ri The corresponding resistivity R ri The following formula is used for calculation: The impedance ratio is calculated using the following formula: x a =KZ a (5) The following strategy is used for fusion processing of formation resistivity, namely: ①In the interval [R min ,R th1 ], using the resistivity R corresponding to the highest frequency ri Characterizes the change in formation resistivity, where R min is the minimum value of formation resistivity; ②In the interval [R th1 ,R th2 ], using the resistivity R corresponding to the second highest frequency ri Characterize formation resistivity changes; ③In the interval [R th2 ,R th3 ], using the resistivity R corresponding to the third highest frequency ri Characterize formation resistivity changes; ④ And so on, until in the interval [R th,n+1 ,R max ], using the impedance ratio ξ corresponding to the lowest frequency a The amplitude of represents the change of formation resistivity, where R max is the maximum value of formation resistivity; By executing the fusion processing steps ①-④ in sequence, the fusion processing of the full range of formation resistivity can be achieved; Step G, establish the forward flow chart of logging response. From left to right, the adopted frequency value gradually increases, and the mud surface is established at each frequency value. The horizontal and vertical coordinates of the mud surface are mud resistivity R m , the dielectric constant of mud ε m , the number of values ​​is m1, m2 respectively, thus obtaining m1×m2 mud points. At each mud point, a three-dimensional coordinate system is established, with the coordinate axes being the gap sd, the formation resistivity R t , formation dielectric constant ε f , the number of values ​​of the three are m3, m4, and m5 respectively. Thus, a three-dimensional grid containing m3×m4×m5 data points is established at each mud point. For each three-dimensional grid, the numerical simulation method of step E is used to carry out batch forward calculation of well logging response to obtain the corresponding three-dimensional impedance amplitude data volume and three-dimensional impedance phase data volume; Step H, establishing a method for determining mud parameters, during the logging while drilling operation, when the logging instrument body (10) passes through the casing (8), the electrical imaging probe device (13) emits current signals at various frequency points, and simultaneously collects voltage, current amplitude and phase signals, and calculates the amplitude A of the measured impedance at this time. z and Phase The measured impedance is used to calculate the mud resistivity and mud dielectric constant, namely Where, ω is the angular frequency of the emission current, satisfying ω=2πf; Step I: After determining the mud resistivity and dielectric constant at each frequency, select the corresponding measured impedance amplitude and phase forward modeling data volume, and the corresponding divided formation resistivity R t , gap sd and formation dielectric constant ε f The data is then transformed into the corresponding formation resistivity R using machine learning algorithms, including single-layer or multi-layer neural networks. t , gap sd and formation dielectric constant ε f As input, the impedance amplitude A is measured z and Phase As output, respectively, or both as output, by setting the number of neurons in the hidden layer, the number of layers, the activation function from the input layer to the hidden layer, from the hidden layer to the output layer, and between the hidden layers, continuous iteration optimization, to obtain the optimal neural network model, from the optimal neural network model to extract the weights, thresholds, and neuron activation functions between the layers, composed of the display fitting function expression h(R t ,sd,ε f ) and g(R t ,sd,ε f ), or k(R t ,sd,ε f ),Right now A z =h(R t ,sd,e f ) (9) or Step J, obtaining the measured impedance amplitude A at each frequency z and Phase After fitting the function, in order to obtain the formation resistivity R t , gap sd and formation dielectric constant ε f , construct the minimization objective function C(x): Among them, the vector x consists of the gap, the formation resistivity R at each frequency t and the formation dielectric constant ε f and is the value to be determined; S(x) is a combined form of the fitting functions h, g or k obtained in step G, and the vector y * consists of the impedance amplitude and phase of the electrical imaging probe device 13 at multiple frequencies in the actual measurement data and is the actual reference value. The vector x p is the value of the vector x after the previous iteration in the optimization iteration process and is the reference value; W d , W p are preset weight matrices used to adjust the influence of each difference part in C(x), and ζ is a preset regularization coefficient; the optimization iteration process of the function C(x) is implemented by using the Gauss-Newton iteration algorithm, the particle swarm optimization algorithm or a combination of the two; when C(x) < tol, where tol is a preset error threshold, or when C(x) reaches the maximum number of iterations, the vector x at this time is the optimal solution, and the calculation of the formation resistivity R t , the gap sd and the formation dielectric constant ε f is completed. Step K, based on the above steps, the formation resistivity, gap and formation dielectric constant corresponding to the measured impedance amplitude and phase of the electrical imaging probe device (13) are calculated one by one, and according to the drilling speed and rotational angular velocity of the logging instrument body (10), the calculated data is imaged and displayed, so that the formation resistivity image, gap image and formation dielectric constant image of the well wall formation can be obtained.

7. The oil-based mud electrical imaging logging while drilling method according to claim 6, characterized in that: The alternative scheme of step B is that the button electrode (14) and the shielding electrode (15) are kept at the same potential, and the outer return electrode (16) emits A current (22) and B current (23) at a certain frequency; the A current (22) passes through the mud / mud cake layer (21) into the formation (4), passes through the mud / mud cake layer (21) again and flows back to the central button electrode (14); at the same time, the B current (23) passes through the mud / mud cake layer (21) into the formation (4), passes through the mud / mud cake layer (21) again and flows back to the shielding electrode (15).

8. The oil-based mud electrical imaging logging while drilling method according to claim 6, characterized in that: An alternative to step E is to build a physical model in a laboratory environment, that is, the container (24) is filled with aqueous solution, the salinity of the aqueous solution is changed, and the resistivity and dielectric constant of the aqueous solution are measured using an impedance grid analyzer to obtain an equivalent formation resistivity R t and dielectric constant ε f The logging instrument body (10) is placed in the aqueous solution, and the aqueous solution is measured using the electrical imaging probe device (13) of the logging instrument body (10), and the measured impedance amplitude A is obtained by calculation. z and Phase Finally, according to the measured impedance amplitude A z and Phase and the known formation resistivity R t and dielectric constant ε f , the instrument constant K is obtained through calibration.

9. The oil-based mud electrical imaging logging while drilling method according to claim 6, characterized in that: An alternative to step F is to select a frequency f in a higher range from the n frequency values. s , set a resistivity threshold point R ths , calculate the real part of the measured impedance Z at the selected frequency rs The corresponding resistivity R rs And the equivalent resistivity R eqs , where the real part of the measured impedance Z rs The corresponding resistivity R rs Using formula (5), Equivalent resistivity R eqs The following formula is used for calculation: Then the following strategy is used to carry out the fusion processing of formation resistivity, namely: ①In the interval [R min ,R ths ], the real part of the measured impedance at the selected frequency corresponds to the resistivity R rs Characterizes the change in formation resistivity, where R min is the minimum value of formation resistivity; ②In the interval [R ths ,R max ], using the equivalent resistivity R at the selected frequency eqs Characterizes the change in formation resistivity, where R max is the maximum value of formation resistivity; By executing steps ①-② in sequence, the fusion processing of the full range of formation resistivity can also be achieved.

10. The oil-based mud electrical imaging logging while drilling method according to claim 6, characterized in that: The alternative scheme of step H is that during the logging while drilling operation, each time a certain distance or time is drilled, the shielding electrode (15) on the electrical imaging probe device (13) no longer emits the shielding B current (23), but acts as a return electrode, that is, the emission A current (22) of the button electrode (14) no longer flows back to the return electrode (16), but flows back to the shielding electrode (15); since the emission A current (22) is no longer shielded and the current loop path is shorter, at this time, the measurement impedance of the button electrode (14) comes from the mud, so the mud resistivity and dielectric constant are determined using formulas (7) and (8).

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