Formation water mineralization degree measuring device and method

Abstract

The invention discloses a formation water salinity measuring device and method, and the device comprises a downhole instrument which is internally provided with a data collection module and a control module; the data acquisition module comprises pumping equipment, a temperature sensor, an insulating pipeline, and a transmitting coil and a receiving coil which are used for sleeving the insulating pipeline; the pumping equipment is used for pumping the stratum water into the insulating pipeline; the temperature sensor is used for detecting the temperature of formation water and sending a collected temperature detection signal to the control module; and the control module is used for generating a first sine wave signal for driving the transmitting coil, processing a second sine wave signal in the receiving coil to obtain an effective frequency signal, and fitting according to the effective frequency signal and the temperature detection signal to obtain formation water mineralization degree data. The device is simple in structure and low in construction cost, the effect of indirectly fitting the mineralization degree of the formation water can be achieved, and the mineralization degree data of the formation water can be efficiently and accurately obtained.

Description

Technical Field

[0001] The present application relates to the field of well logging technology, and in particular to a formation water salinity measurement device and method. Background Art

[0002] The mineralization of formation water refers to the concentration of dissolved salts in groundwater. In formation water sampling, the mineralization of the sample is a very critical indicator, which plays an important role in fluid identification and fluid sampling timing. Measuring the mineralization of formation water is a very difficult task. The existing methods of measuring the mineralization of formation water are very complicated and time-consuming. There is an urgent need for an efficient and accurate method of measuring the mineralization of formation water. Summary of the invention

[0003] In view of the above problems, the present application is proposed to provide a formation water mineralization measurement device and method that overcomes the above problems or at least partially solves the above problems.

[0004] According to one aspect of the present application, there is provided a formation water salinity measurement device, comprising: a downhole instrument, wherein a data acquisition module and a control module are provided in the downhole instrument; The data acquisition module includes: a pumping device, a temperature sensor, an insulating pipeline, and a transmitting coil and a receiving coil for sheathing the insulating pipeline; Pumping equipment, used to pump formation water into the insulated pipeline; The temperature sensor is used to detect the temperature of the formation water and send the collected temperature detection signal to the control module; The control module is used to generate a first sinusoidal wave signal for driving the transmitting coil, process the second sinusoidal wave signal in the receiving coil to obtain an effective frequency signal, and obtain formation water salinity data by fitting the effective frequency signal and the temperature detection signal.

[0005] Optionally, the control module includes: a first signal processing circuit connected to the transmitting coil and a second signal processing circuit connected to the receiving coil; a first signal processing circuit, used for generating an initial sinusoidal wave signal, adjusting the amplitude of the initial sinusoidal wave signal, and amplifying the initial sinusoidal wave signal after the amplitude adjustment, thereby outputting a first sinusoidal wave signal for driving the transmitting coil; The second signal processing circuit is used to amplify the second sinusoidal wave signal in the receiving coil, convert the amplified second sinusoidal wave signal into an effective value DC signal, and convert the effective value DC signal into an effective frequency signal.

[0006] Optionally, the control module is further configured to: Using a counter to convert the effective frequency signal into a frequency engineering value, and to convert the temperature detection signal into temperature data; Based on a preset first fitting algorithm, conductivity data is calculated according to the frequency engineering value; Based on the preset second fitting algorithm, the formation water salinity data is fitted according to the conductivity data and the temperature data.

[0007] Optionally, the control module is further configured to: According to the conductivity data and the temperature data, multiple groups of target benchmark data are selected from multiple preset groups of benchmark data; wherein each group of benchmark data includes: benchmark conductivity data, benchmark temperature data and benchmark mineralization data; Constructing a set of equations for solving weight values ​​according to a plurality of reference conductivity data and a plurality of reference temperature data included in the plurality of sets of target reference data; A plurality of weight values ​​are obtained by solving the equation group, and the formation water mineralization data are calculated based on the plurality of weight values ​​and a plurality of benchmark mineralization data included in the plurality of sets of target benchmark data.

[0008] Optionally, the control module is further configured to: For each set of reference data in the preset multiple sets of reference data, the data distance is calculated according to the reference conductivity data, the reference temperature data, the conductivity data, and the temperature data in the set of reference data; According to the data distance corresponding to each group of benchmark data, multiple groups of target benchmark data are screened out.

[0009] Optionally, the device further comprises a ground system; The downhole instrument also includes: a teletransmission short section, which is used to receive the formation water mineralization data sent by the control module, and encode the formation water mineralization data and send it to the surface system; The ground system is used to decode the received coded data and visualize the decoded formation water salinity data.

[0010] Optionally, the ground system is further configured to: A first fitting algorithm and a second fitting algorithm are obtained by fitting, and the first fitting algorithm and the second fitting algorithm are sent to a control module; and a plurality of preset groups of reference data are sent to the control module.

[0011] Optionally, the ground system is further used to: adopt a least squares method to fit the mapping relationship between the frequency engineering value and the conductivity data to obtain a first fitting algorithm.

[0012] Optionally, the device further comprises: a probe, and when the downhole instrument reaches the target layer of the formation, the probe extends outwardly toward the well wall so that the downhole instrument is closely attached to the well wall.

[0013] According to another aspect of the present application, a method for measuring formation water salinity is provided, comprising: Pump the formation water into the insulated pipeline; Detect the temperature of formation water and obtain a temperature detection signal; generating a first sinusoidal wave signal for driving the transmitting coil, and processing the second sinusoidal wave signal in the receiving coil to obtain an effective frequency signal; According to the effective frequency signal and temperature detection signal, the formation water salinity data is fitted.

[0014] Optionally, generating a first sinusoidal wave signal for driving a transmitting coil further comprises: Generate an initial sine wave signal, adjust the amplitude of the initial sine wave signal, and amplify the initial sine wave signal after the amplitude adjustment, so as to output a first sine wave signal for driving the transmitting coil; Processing the second sinusoidal wave signal in the receiving coil to obtain an effective frequency signal further includes: The second sinusoidal wave signal in the receiving coil is amplified, the amplified second sinusoidal wave signal is converted into an effective value DC signal, and the effective value DC signal is converted into an effective frequency signal.

[0015] Optionally, fitting to obtain formation water salinity data according to the effective frequency signal and the temperature detection signal further includes: Using a counter to convert the effective frequency signal into a frequency engineering value, and to convert the temperature detection signal into temperature data; Based on a preset first fitting algorithm, conductivity data is calculated according to the frequency engineering value; Based on the preset second fitting algorithm, the formation water salinity data is fitted according to the conductivity data and the temperature data.

[0016] Optionally, based on a preset second fitting algorithm, fitting the formation water salinity data according to the conductivity data and the temperature data further includes: According to the conductivity data and the temperature data, multiple groups of target benchmark data are selected from multiple preset groups of benchmark data; wherein each group of benchmark data includes: benchmark conductivity data, benchmark temperature data and benchmark mineralization data; Constructing a set of equations for solving weight values ​​according to a plurality of reference conductivity data and a plurality of reference temperature data included in the plurality of sets of target reference data; A plurality of weight values ​​are obtained by solving the equation group, and the formation water mineralization data are calculated based on the plurality of weight values ​​and a plurality of benchmark mineralization data included in the plurality of sets of target benchmark data.

[0017] Optionally, screening multiple groups of target reference data from multiple groups of preset reference data according to the conductivity data and the temperature data further includes: For each set of reference data in the preset multiple sets of reference data, the data distance is calculated according to the reference conductivity data, the reference temperature data, the conductivity data, and the temperature data in the set of reference data; According to the data distance corresponding to each group of benchmark data, multiple groups of target benchmark data are screened out.

[0018] Optionally, the method further comprises: Encode the formation water salinity data and transmit them; The encoded data is decoded, and the decoded formation water salinity data is visualized.

[0019] Optionally, the method further comprises: A first fitting algorithm and a second fitting algorithm are obtained by fitting, the first fitting algorithm and the second fitting algorithm are stored, and a plurality of groups of reference data are stored.

[0020] Optionally, fitting to obtain a first fitting algorithm further includes: The least square method is used to fit the mapping relationship between the frequency engineering value and the conductivity data to obtain the first fitting algorithm.

[0021] Optionally, the method further comprises: a probe, when the downhole instrument reaches the target layer of the formation, controlling the probe to extend outward toward the well wall so that the downhole instrument is closely attached to the well wall.

[0022] According to the formation water mineralization measurement device and method provided in the embodiment of the present application, the device includes: a downhole instrument, in which a data acquisition module and a control module are arranged; the data acquisition module includes: a pumping device, a temperature sensor, an insulating pipeline, and a transmitting coil and a receiving coil for being sheathed on the insulating pipeline; the pumping device is used to pump the formation water into the insulating pipeline; the temperature sensor is used to detect the temperature of the formation water and send the collected temperature detection signal to the control module; the control module is used to generate a first sinusoidal wave signal for driving the transmitting coil, process the second sinusoidal wave signal in the receiving coil to obtain an effective frequency signal, and obtain the formation water mineralization data by fitting the effective frequency signal and the temperature detection signal. The device of the present application has a simple structure and low construction cost. All measurements and calculations are completed in the downhole instrument. The conductivity of the formation water is obtained based on a pair of coils, the temperature of the formation water is obtained through a temperature sensor, and the mineralization is obtained by fitting the conductivity and temperature of the formation water. This can achieve the effect of indirectly fitting the mineralization of the formation water, simplify the measurement of the mineralization of the formation water, and can efficiently and accurately obtain the mineralization data of the formation water.

[0023] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings: Figure 1 A schematic diagram of the structure of a formation water mineralization measurement device provided in one embodiment of the present application is shown; Figure 2 A schematic diagram of the structure of a formation water mineralization measurement device provided by another embodiment of the present application is shown; Figure 3 A schematic diagram of the structure of a control module provided in an embodiment of the present application is shown; Figure 4 A flow chart of a formation water mineralization measurement method provided in another embodiment of the present application is shown. DETAILED DESCRIPTION

[0025] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0026] The formation water mainly contains Na + , K + , Cl - , Ca2 + Plasma, in which Na + , Cl - It is the main ion component and the ion with the strongest conductivity in formation water. Formation water is equivalent to an aqueous solution containing a certain concentration of NaCl. This approximation method can achieve sufficiently accurate engineering results to a certain extent. The formation water mineralization measurement device and method of the embodiment of the present application are implemented based on the above theory.

[0027] Figure 1 FIG. 1 is a schematic diagram showing the structure of a formation water mineralization measurement device provided in an embodiment of the present application. Figure 1As shown, the device comprises: a downhole instrument 1, in which a data acquisition module 10 and a control module 11 are arranged. The downhole instrument 1 is lowered to a specified depth in the well to measure the mineralization of formation water.

[0028] The data acquisition module 10 includes: a pumping device 101 , a temperature sensor 102 , a transmitting coil 103 , a receiving coil 104 and an insulating pipeline 105 , wherein the transmitting coil 103 and the receiving coil 104 are sheathed on the insulating pipeline 105 .

[0029] A pumping device 101 is used to pump formation water into an insulating pipeline 105; The temperature sensor 102 is used to detect the temperature of the formation water and send the collected temperature detection signal to the control module 11; The control module 11 is used to generate a first sinusoidal wave signal for driving the transmitting coil 103, convert the second sinusoidal wave signal in the receiving coil 104 into an effective frequency signal, and obtain formation water salinity data by fitting the effective frequency signal and the temperature detection signal.

[0030] In an optional manner, the material of the insulating pipeline 105 is insulating ceramic.

[0031] In another optional manner, the data acquisition module 10 includes: a fluid pipeline, the insulating pipeline 105 is a partial pipeline on the fluid pipeline, that is, the insulating pipeline 105 is a section of the complete fluid pipeline, the formation water is pumped into the fluid pipeline, flows through the insulating pipeline 105, and the insulating pipeline 105 and the fluid pipeline where it is located are pre-buried inside the downhole instrument 1, which can reduce the cost of hardware equipment. Further optionally, the temperature sensor 102 is set at a position close to the insulating pipeline 105 inside the fluid pipeline, and the formation water pumped into the fluid pipeline first passes through the temperature sensor 102 and then passes through the insulating pipeline 105.

[0032] Specifically, the insulating pipeline 105 is covered with two magnetic rings, on which coils are wound, forming a transmitting coil 103 and a receiving coil 104 respectively.

[0033] When a sinusoidal wave signal is sent to the transmitting coil 103 , a sinusoidal wave signal with the same frequency will be generated in the receiving coil 104 . The effective frequency signal corresponding to the sinusoidal wave signal in the receiving coil 104 is related to the conductivity of the formation water in the insulating pipeline 105 .

[0034] The control module 11 stores a fitting algorithm, and the mineralization data of the formation water can be obtained by fitting the fitting algorithm, the effective frequency signal and the temperature detection signal.

[0035] According to the formation water mineralization measuring device of the embodiment of the present application, the structure of the device is simple and the construction cost is low. The measurement and calculation are all completed in the downhole instrument. The electrical conductivity of the formation water is obtained based on a pair of coils, and the temperature of the formation water is obtained through a temperature sensor. The mineralization is obtained by fitting the electrical conductivity and temperature of the formation water. The effect of indirectly fitting the mineralization of the formation water can be achieved, the formation water mineralization measurement work can be simplified, and the mineralization data of the formation water can be obtained efficiently and accurately.

[0036] Figure 2 FIG. 2 shows a schematic diagram of a formation water mineralization measurement device provided in another embodiment of the present application. Figure 2 As shown, the device includes: a downhole instrument 1, a ground system 2 and a probe 4. The downhole instrument 1 and the ground system 2 are connected via a connecting component 3, and the connecting component 3 is a cable or a drill pipe. The ground system 2 supplies power to the downhole instrument 1 via the connecting component 3, and completes up and down communication via the connecting component 3.

[0037] The function of the probe 4 is: when the downhole instrument 1 reaches the target layer of the formation 5, the probe 4 extends outward toward the well wall to make the downhole instrument 1 close to the well wall, thereby ensuring the stability of the downhole instrument 1 during the measurement process.

[0038] The downhole instrument 1 specifically includes: a telemetry sub 12, a data acquisition module 10, a control module 11 and other instrument strings 13. The various parts of the downhole instrument 1 cooperate with each other to complete the measurement of formation water salinity.

[0039] The data acquisition module 10 and the control module 11 may be arranged in the same short section, which is called a cable formation tester.

[0040] The data acquisition module 10 includes: a pumping device 101 , a temperature sensor 102 , an insulating pipeline 105 , and a transmitting coil 103 and a receiving coil 104 for sheathing the insulating pipeline 105 .

[0041] The pumping device 101 is used to pump the formation water into the insulating pipeline 105; the temperature sensor 102 is used to detect the temperature of the formation water and send the collected temperature detection signal to the control module 11; the control module 11 is used to generate a first sinusoidal wave signal for driving the transmitting coil 103, process the second sinusoidal wave signal in the receiving coil 104 to obtain an effective frequency signal, and obtain the formation water mineralization data by fitting the effective frequency signal and the temperature detection signal.

[0042] The teletransmission sub 12 is responsible for encoding and decoding the communication data of the ground system 2, and transmitting the electric energy transmitted by the connecting component 3 to various components in the downhole instrument 1. Specifically, it is used to receive the formation water mineralization data sent by the control module 11, and encode the formation water mineralization data and send it to the ground system 2.

[0043] Correspondingly, the ground system 2 is used to decode the received coded data and visualize the decoded formation water mineralization data, thereby realizing real-time display of the formation water mineralization data.

[0044] The other instrument string 13 includes other instruments working in coordination.

[0045] When the downhole instrument 1 reaches the specified depth, the pumping device 101 starts to work and pumps the formation water into the insulating pipeline 105. The temperature sensor 102 detects the temperature of the formation water and sends the collected temperature detection signal to the control module 11. The control module 11, on the one hand, generates a first sinusoidal wave signal for driving the transmitting coil 103, and converts the second sinusoidal wave signal in the receiving coil 104 into an effective frequency signal. On the other hand, the formation water salinity data is obtained by fitting the effective frequency signal and the temperature detection signal.

[0046] The function and structure of the control module 11 are described in detail below with reference to the accompanying drawings. Figure 3 A schematic diagram of the structure of a control module provided in an embodiment of the present application is shown.

[0047] The control module 11 includes: a first signal processing circuit 111 connected to the transmitting coil 103 and a second signal processing circuit 112 connected to the receiving coil 104 .

[0048] The first signal processing circuit 111 is used to generate an initial sinusoidal wave signal, adjust the amplitude of the initial sinusoidal wave signal, and amplify the initial sinusoidal wave signal after the amplitude adjustment, so as to output a first sinusoidal wave signal for driving the transmitting coil 103 .

[0049] Specifically, the first signal processing circuit 111 includes: a sine wave generator, a waveform amplitude adjustment circuit, and a power amplifier circuit. The sine wave generator generates an initial sine wave signal, the waveform amplitude adjustment circuit adjusts the amplitude of the initial sine wave signal, and then the power amplifier circuit amplifies the signal output by the waveform amplitude adjustment circuit, and the power amplifier circuit outputs a first sine wave signal for driving the transmitting coil 103. For example, the sine wave generator generates an initial sine wave signal of 20kHz, the waveform amplitude adjustment circuit adjusts the waveform to a peak value of 1V, and the power amplifier circuit then amplifies the current to drive the transmitting coil 103.

[0050] The second signal processing circuit 112 is used to amplify the second sinusoidal wave signal in the receiving coil 104, convert the amplified second sinusoidal wave signal into an effective value DC signal, and convert the effective value DC signal into an effective frequency signal.

[0051] Specifically, the second signal processing circuit 112 includes: an amplifier circuit 1121, an effective value conversion circuit 1122, and a voltage-frequency conversion circuit 1123. The amplifier circuit 1121 amplifies the second sinusoidal wave signal, the effective value conversion circuit 1122 converts the sinusoidal wave signal output by the amplifier circuit 1121 into an effective value DC signal, and the voltage-frequency conversion circuit 1123 converts the effective value DC signal output by the effective value conversion circuit 1122 into an effective frequency signal, wherein the larger the effective value DC signal is, the larger the frequency value obtained by conversion is, and the two are proportional.

[0052] The control module 11 is also used to: use a counter to convert the effective frequency signal into a frequency engineering value, and convert the temperature detection signal into temperature data; based on a preset first fitting algorithm, calculate the conductivity data according to the frequency engineering value; based on a preset second fitting algorithm, fit the formation water mineralization data according to the conductivity data and the temperature data.

[0053] In an optional manner, the calculation function of the control module 11 is implemented by the main control module 113, which is the core part of the control module 11 and is implemented by a single-chip minimum system. All related calculations are completed in the main control module 113. The functions of the main control module 113 include: using a counter to convert an effective frequency signal into a frequency engineering value, and converting a temperature voltage signal into temperature data; based on a preset first fitting algorithm, conductivity data is calculated according to the frequency engineering value; based on a preset second fitting algorithm, formation water salinity data is fitted according to the conductivity data and the temperature data. Among them, the temperature voltage signal is obtained by converting the temperature detection signal by the temperature sensor conditioning circuit 114, and the temperature sensor conditioning circuit 114 is connected to the temperature sensor 102.

[0054] The main control module 113 specifically uses the built-in counter to obtain the frequency engineering value corresponding to the effective frequency signal. It should be noted that the frequency engineering value is not the frequency itself, but an engineering value that is strictly proportional to the real frequency. Because what is concerned is the relationship between the fluid conductivity and the frequency engineering value, and the real frequency value is not concerned, the real frequency value is not calculated.

[0055] In addition, the control module 11 also includes other conventional functional modules, including a communication level conversion circuit 115 and a power supply circuit 116. The communication level conversion circuit 115 is responsible for converting the UART level of the single-chip microcomputer into a bus level, and the various parts inside the device communicate with each other through the bus. For example, the cable formation tester communicates with the teletransmission short section 12, and the teletransmission short section 12 encodes the formation water salinity data and uploads it to the ground system 2. The power supply circuit 116 is used to convert the 5V voltage into a 3.3V voltage to supply power to the main control module 113.

[0056] The control module 11 is further used to: select multiple groups of target benchmark data from multiple preset groups of benchmark data according to the conductivity data and the temperature data; wherein each group of benchmark data includes: benchmark conductivity data, benchmark temperature data and benchmark mineralization data; construct a group of equations for solving weight values ​​according to the multiple benchmark conductivity data and the multiple benchmark temperature data included in the multiple groups of target benchmark data; solve the group of equations to obtain multiple weight values, and calculate the formation water mineralization data according to the multiple weight values ​​and the multiple benchmark mineralization data included in the multiple groups of target benchmark data.

[0057] In an optional manner, a specific method for screening multiple sets of target benchmark data is: for each set of benchmark data in the preset multiple sets of benchmark data, the data distance is calculated according to the benchmark conductivity data, benchmark temperature data, conductivity data, and temperature data in the set of benchmark data; and multiple sets of target benchmark data are screened out according to the data distances corresponding to each set of benchmark data.

[0058] The preset first fitting algorithm and the second fitting algorithm and the preset multiple sets of reference data in the control module 11 are all issued by the ground system 2. The ground system 2 is specifically used for: fitting the first fitting algorithm and the second fitting algorithm, and issuing the first fitting algorithm and the second fitting algorithm to the control module 11; and sending the preset multiple sets of reference data to the control module 11.

[0059] In an optional manner, the ground system 2 is further used to: adopt a least squares method to fit the mapping relationship between the frequency engineering value and the conductivity data to obtain a first fitting algorithm.

[0060] The data fitting method of the embodiment of the present application is illustrated below through a specific data example. Under a laboratory environment, 7 NaCl aqueous solutions of different concentrations are extracted and flowed into an insulating ceramic tube, and the conductivity data and frequency engineering values ​​are measured. Table 1 shows the conductivity data and frequency engineering values ​​of the 7 NaCl aqueous solutions. The values ​​in Table 1 are called sample values.

[0061] Table 1

[0062] The algorithm formula for characterizing the mapping relationship between the frequency engineering value and the conductivity data is constructed as follows: a cubic equation with the frequency engineering value as the independent variable and the conductivity data as the dependent variable, as shown in formula (1): (1); In formula (1), y represents the conductivity data, the unit is S / m; x represents the frequency engineering value, without unit; A, B, C, and D are calibration coefficients, all of which are floating point numbers, the unit is S / m.

[0063] Substitute the data in Table 1 into formula (1) and obtain the fitting results of calibration coefficients A, B, C, and D through least squares fitting. The fitting results of calibration coefficients need to meet the following limiting conditions: the cumulative sum of the differences between the sample values ​​of conductivity data and the calculated values ​​of conductivity data is the smallest. The calculated value of conductivity is the conductivity value calculated by substituting the sample values ​​of frequency engineering values ​​and the fitting results of calibration coefficients into the above algorithm formula (1). The limiting condition is expressed as follows: (2); Among them, least squares fitting is a common solution method, and numerical computing libraries such as Matlab and Python's scikit have callable functions.

[0064] Formula (3) is an example of the calculation result obtained by substituting the data example in Table 1 into formula (1) and using the least squares method according to the limiting conditions of formula (2), which is the first fitting algorithm.

[0065] y = (5E-10) x 3 -(2E-06) x 2 +0.0094 x -2.1304 (3); The ground system 2 obtains the above-mentioned algorithm (i.e., the first fitting algorithm) for calculating the conductivity data according to the frequency engineering value by fitting the sample data, and sends the first fitting algorithm to the control module 11. After the control module 11 obtains the measured frequency engineering value, it can fit the corresponding conductivity data.

[0066] In the method of the present application, it is necessary to obtain multiple sets of benchmark data in advance, specifically based on the NaCl aqueous solution, to obtain multiple sets of corresponding benchmark conductivity data, benchmark temperature data and benchmark mineralization data. The multiple sets of benchmark data are stored in the control module 11, so that the control module 11 fits the formation water mineralization data according to the multiple sets of benchmark data.

[0067] It should be noted that the relationship between the conductivity and mineralization of NaCl aqueous solution is an inherent property of the substance and can be measured by experimental methods. When the solution temperature is greater than 100°C, the water will boil and the NaCl aqueous solution cannot be measured at normal temperature and pressure. Considering that when the mineralization remains unchanged, the conductivity and temperature of the NaCl aqueous solution are in direct proportion, and the effect of pressure on conductivity is small enough to be ignored, the corresponding data of the conductivity, mineralization and temperature of the NaCl aqueous solution at over 100°C can be approximated by a linear relationship.

[0068] Specifically, an algorithm formula characterizing the mapping relationship between temperature data and conductivity data is constructed, as shown in formula (4): (4); In formula (4), E and F are coefficients, the unit of E is S / (m℃), the unit of F is S / m; n is the temperature data, the unit is ℃; m is the conductivity data, the unit is S / m.

[0069] Taking the mineralization degree of 1g / L as an example, the conductivity data of the NaCl aqueous solution with a mineralization degree of 1g / L at 20℃~80℃ is substituted into formula (4), and the fitting results of E and F are obtained by the least square fitting method. Then, the fitting results of E and F and the temperature to be estimated (for example, each temperature in the range of 100℃ to 200℃) are substituted into formula (4), and the conductivity data at the temperature to be estimated can be obtained. The calculation method for other mineralization degrees is the same and will not be repeated here.

[0070] Table 2 shows the conductivity data of NaCl aqueous solution at different mineralization degrees and different temperatures, wherein the relevant data at 20°C-80°C are actually measured, and the conductivity data at 100°C-200°C are obtained by fitting according to the above method. Each group of data in Table 2 is determined as each group of benchmark data, and the ground system 2 sends each group of benchmark data to the control module 11.

[0071] Table 2

[0072] The ground system 2 sends all the fitting results of formula (1) and the four calibration coefficients A, B, C, and D to the control module 11, that is, the first fitting algorithm is stored in the control module 11. After the control module 11 obtains the measured frequency engineering value, it substitutes the frequency engineering value and the fitting results of the four calibration coefficients A, B, C, and D into formula (1), and the conductivity data of the formation water can be calculated. The control module 11 also obtains the temperature data of the formation water. The measurement temperature range is within 20°C~200°C, the conductivity is within 0~130S / m, and the formation water mineralization measurement in other ranges is not considered. All data points within the measurement range will be included in the data in Table 2.

[0073] The data obtained by the control module 11 is called real data and is represented by C t represents the conductivity data, T calculated by the control module 11 according to the first fitting algorithm and the frequency engineering value. t represents the temperature data obtained by the control module 11 by converting the temperature detection signal, M t It represents the mineralization data obtained by fitting the control module 11. The control module 11 specifically calculates the formation water mineralization data through the second fitting algorithm. The second fitting algorithm is specifically implemented based on the KNN algorithm. The specific process of the algorithm is as follows: The first step is to obtain each set of benchmark data. In this example, each set of temperature data, conductivity data, and salinity data corresponding to Table 2 is defined as a set of benchmark data. C represents benchmark conductivity data, T represents benchmark temperature data, and M represents benchmark salinity data. There are 250 sets of benchmark data in Table 2. The second step is to define the real data (C t , T t , M t ) and any set of benchmark data (C, T, M), data distance The calculation method of is shown in formula (5); (5); The third step is to calculate the data distance between the real data and each set of benchmark data according to the definition of data distance above, and obtain multiple data distances. In this example, 250 data distances are calculated, and then sorted in ascending order of data distance. The fourth step is to filter the three sets of benchmark data corresponding to the data distances ranked in the top three into multiple sets of target benchmark data, expressed as: (C i , T i , M i )、i=1,2,3,C i represents the reference conductivity data in the i-th group of target reference data, T i represents the reference temperature data in the i-th group of target reference data, M i represents the benchmark mineralization data in the i-th group of target benchmark data, that is, k in the KNN algorithm is 3; In the fifth step, according to the three-dimensional three-point linear interpolation algorithm, first set the dimensionless weights u and v, and then construct a set of two-variable linear equations (6) for solving the weights. The specific equations (6) are as follows: C t = (1-uv)C 1 +uC 2 +vC 3 T t = (1-uv)T1 +uT 2 +vT 3 The sixth step is to solve equation group (6) to obtain the values ​​of weights u and v. Then, the three benchmark mineralization data contained in the three sets of target benchmark data and the values ​​of weights u and v are substituted into formula (7) to calculate the true value of formation water mineralization M. t , that is, the formation water mineralization data obtained by fitting by the control module 11. So far, fitting the formation water mineralization data has been achieved; M t = (1-uv)M 1 +uM 2 +vM 3 (7).

[0074] The ground system 2 fits the above-mentioned algorithm for calculating the mineralization data based on the conductivity data and the temperature data (i.e., the second fitting algorithm), and sends the second fitting algorithm to the control module 11. After the control module 11 obtains the measured conductivity data and temperature data, the corresponding formation water mineralization data can be fitted.

[0075] To sum up, the formation water mineralization measuring device provided in this embodiment has a simple structure and low construction cost, and the measurement method is simpler. By measuring the real-time conductivity of the formation water, the corresponding relationship between the mineralization of the NaCl aqueous solution and the conductivity is used as the basis, and the mineralization data of the formation water is calculated in real time by relying on the weighted KNN method. The measurement and calculation are all completed in the downhole instrument. The conductivity measurement and the weighted KNN calculation are completed in the control module of the downhole instrument. The measurement results are uploaded to the ground system through the bus for display, which can achieve the effect of indirectly fitting the formation water mineralization, simplify the formation water mineralization measurement work, efficiently and accurately obtain the formation water mineralization data, and realize the real-time display of the formation water mineralization data.

[0076] Figure 4 FIG. 2 is a flow chart showing a formation water mineralization measurement method provided by another embodiment of the present application. The method is applied to the formation water mineralization measurement device described in the above embodiment, such as Figure 4 As shown, the method comprises the following steps: Step S401, pumping formation water into an insulating pipeline; Step S402, detecting the temperature of formation water to obtain a temperature detection signal; Step S403, generating a first sinusoidal wave signal for driving the transmitting coil, and processing the second sinusoidal wave signal in the receiving coil to obtain an effective frequency signal; Step S404: fitting the formation water salinity data according to the effective frequency signal and the temperature detection signal.

[0077] In an optional manner, generating a first sinusoidal wave signal for driving the transmitting coil further includes: Generate an initial sine wave signal, adjust the amplitude of the initial sine wave signal, and amplify the initial sine wave signal after the amplitude adjustment, so as to output a first sine wave signal for driving the transmitting coil; Processing the second sinusoidal wave signal in the receiving coil to obtain an effective frequency signal further includes: The second sinusoidal wave signal in the receiving coil is amplified, the amplified second sinusoidal wave signal is converted into an effective value DC signal, and the effective value DC signal is converted into an effective frequency signal.

[0078] In an optional manner, fitting to obtain formation water salinity data according to the effective frequency signal and the temperature detection signal further includes: Using a counter to convert the effective frequency signal into a frequency engineering value, and to convert the temperature detection signal into temperature data; Based on a preset first fitting algorithm, conductivity data is calculated according to the frequency engineering value; Based on the preset second fitting algorithm, the formation water salinity data is fitted according to the conductivity data and the temperature data.

[0079] In an optional manner, based on a preset second fitting algorithm, the formation water salinity data is fitted according to the conductivity data and the temperature data, further comprising: According to the conductivity data and the temperature data, multiple groups of target benchmark data are selected from multiple preset groups of benchmark data; wherein each group of benchmark data includes: benchmark conductivity data, benchmark temperature data and benchmark mineralization data; Constructing a set of equations for solving weight values ​​according to a plurality of reference conductivity data and a plurality of reference temperature data included in the plurality of sets of target reference data; A plurality of weight values ​​are obtained by solving the equation group, and the formation water mineralization data are calculated based on the plurality of weight values ​​and a plurality of benchmark mineralization data included in the plurality of sets of target benchmark data.

[0080] In an optional manner, screening multiple groups of target reference data from multiple groups of preset reference data according to the conductivity data and the temperature data further includes: For each set of reference data in the preset multiple sets of reference data, the data distance is calculated according to the reference conductivity data, the reference temperature data, the conductivity data, and the temperature data in the set of reference data; According to the data distance corresponding to each group of benchmark data, multiple groups of target benchmark data are screened out.

[0081] In an optional manner, the method further comprises: Encode the formation water salinity data and transmit them; The encoded data is decoded, and the decoded formation water salinity data is visualized.

[0082] In an optional manner, the method further comprises: A first fitting algorithm and a second fitting algorithm are obtained by fitting, the first fitting algorithm and the second fitting algorithm are stored, and a plurality of groups of reference data are stored.

[0083] In an optional manner, fitting to obtain a first fitting algorithm further includes: The least square method is used to fit the mapping relationship between the frequency engineering value and the conductivity data to obtain the first fitting algorithm.

[0084] In an optional manner, the method further comprises: a probe, when the downhole instrument reaches a target layer of the formation, controlling the probe to extend outward toward the well wall so that the downhole instrument is closely attached to the well wall.

[0085] To summarize, according to the formation water mineralization measurement method provided in this embodiment, by measuring the real-time electrical conductivity of the formation water, based on the correspondence between the mineralization and electrical conductivity of the NaCl aqueous solution, the mineralization data of the formation water is calculated in real time by the weighted KNN method, and all the measurement and calculation are completed in the downhole instrument, which can achieve the effect of indirectly fitting the formation water mineralization, simplify the formation water mineralization measurement work, efficiently and accurately obtain the formation water mineralization data, and realize the real-time display of the formation water mineralization data.

[0086] The algorithm or display provided here are not inherently related to any specific computer, virtual system or other equipment. Various general systems can also be used together with the teaching based on this. According to the above description, it is obvious to construct the structure required for this type of system. In addition, the present application embodiment is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present application described here, and the above description of specific languages ​​is to disclose the best mode of implementation of the present application.

[0087] In the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0088] Similarly, it should be understood that in order to streamline the present application and aid in understanding one or more of the various inventive aspects, in the above description of the exemplary embodiments of the present application, the various features of the embodiments of the present application are sometimes grouped together into a single embodiment, figure, or description thereof. However, the disclosed method should not be interpreted as reflecting the following intention: the claimed application requires more features than the features explicitly recited in each claim. More specifically, as reflected in the claims, the inventive aspects lie in less than all the features of the single embodiment disclosed above. Therefore, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, with each claim itself serving as a separate embodiment of the present application.

[0089] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and further may be divided into a plurality of submodules or subunits or subcomponents. All features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device so disclosed may be combined in any combination, except that at least some of such features and / or processes or units are mutually exclusive. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature that provides the same, equivalent or similar purpose.

[0090] In addition, those skilled in the art will appreciate that, although some embodiments herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present application and form different embodiments. For example, in the claims, any one of the claimed embodiments may be used in any combination.

[0091] The various component embodiments of the present application may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or a digital signal processor (DSP) may be used in practice to implement some or all functions of some or all components according to the embodiments of the present application. The present application may also be implemented as a device or apparatus program (e.g., a computer program and a computer program product) for executing part or all of the methods described herein. Such a program implementing the present application may be stored on a computer-readable medium, or may be in the form of one or more signals. Such a signal may be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0092] It should be noted that the above embodiments illustrate the present application rather than limit the present application, and that those skilled in the art may design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be constructed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of multiple such elements. The present application may be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In a unit claim that lists several devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be understood as limitations on the order of execution.

Claims

1. A formation water mineralization measurement device, characterized in that: The device comprises: a downhole instrument, wherein a data acquisition module and a control module are arranged in the downhole instrument; The data acquisition module includes: a pumping device, a temperature sensor, an insulating pipeline, and a transmitting coil and a receiving coil for sheathing the insulating pipeline; The pumping equipment is used to pump formation water into the insulating pipeline; The temperature sensor is used to detect the temperature of the formation water and send the collected temperature detection signal to the control module; The control module is used to generate a first sinusoidal wave signal for driving the transmitting coil, process the second sinusoidal wave signal in the receiving coil to obtain an effective frequency signal, and obtain formation water salinity data by fitting the effective frequency signal and the temperature detection signal.

2. The formation water mineralization measuring device according to claim 1, characterized in that: The control module includes: a first signal processing circuit connected to the transmitting coil and a second signal processing circuit connected to the receiving coil; The first signal processing circuit is used to generate an initial sinusoidal wave signal, adjust the amplitude of the initial sinusoidal wave signal, and amplify the initial sinusoidal wave signal after the amplitude adjustment, so as to output a first sinusoidal wave signal for driving the transmitting coil; The second signal processing circuit is used to amplify the second sinusoidal wave signal in the receiving coil, convert the amplified second sinusoidal wave signal into an effective value DC signal, and convert the effective value DC signal into an effective frequency signal.

3. The formation water mineralization measuring device according to claim 1 or 2, characterized in that: The control module is further configured to: Using a counter to convert the effective frequency signal into a frequency engineering value, and to convert the temperature detection signal into temperature data; Based on a preset first fitting algorithm, conductivity data is calculated according to the frequency engineering value; Based on a preset second fitting algorithm, formation water salinity data is fitted according to the conductivity data and the temperature data.

4. The formation water mineralization measuring device according to claim 3, characterized in that: The control module is further configured to: According to the conductivity data and the temperature data, multiple groups of target benchmark data are selected from multiple preset groups of benchmark data; wherein each group of benchmark data includes: benchmark conductivity data, benchmark temperature data and benchmark mineralization data; Constructing a set of equations for solving weight values ​​according to a plurality of reference conductivity data and a plurality of reference temperature data included in the plurality of sets of target reference data; The equation group is solved to obtain a plurality of weight values, and the formation water mineralization data is calculated based on the plurality of weight values ​​and a plurality of reference mineralization data included in the plurality of sets of target reference data.

5. The formation water mineralization measuring device according to claim 4, characterized in that: The control module is further configured to: For each set of reference data in the preset multiple sets of reference data, calculating the data distance according to the reference conductivity data, reference temperature data in the set of reference data and the conductivity data and the temperature data; According to the data distance corresponding to each group of benchmark data, multiple groups of target benchmark data are screened out.

6. The formation water mineralization measuring device according to claim 1, characterized in that: The device also includes a ground system; The downhole instrument further comprises: a teletransmission sub, which is used to receive the formation water salinity data sent by the control module, and encode the formation water salinity data and send it to the surface system; The ground system is used to decode the received coded data and visualize the decoded formation water mineralization data.

7. The formation water mineralization measuring device according to claim 6, characterized in that: The ground system is further used for: A first fitting algorithm and a second fitting algorithm are obtained by fitting, and the first fitting algorithm and the second fitting algorithm are sent to the control module; and a plurality of preset groups of reference data are sent to the control module.

8. The formation water mineralization measuring device according to claim 7, characterized in that: The ground system is further used to: adopt the least square method to fit the mapping relationship between the frequency engineering value and the conductivity data to obtain the first fitting algorithm.

9. The formation water mineralization measuring device according to claim 1, characterized in that: The device further comprises: a probe, and when the downhole instrument reaches the target layer of the formation, the probe extends outwardly toward the well wall so that the downhole instrument is closely attached to the well wall.

10. A method for measuring formation water mineralization, characterized in that: The method is applied to the formation water mineralization measuring device according to any one of claims 1 to 9, and the method comprises: Pump the formation water into the insulated pipeline; Detect the temperature of formation water and obtain a temperature detection signal; generating a first sinusoidal wave signal for driving the transmitting coil, and processing the second sinusoidal wave signal in the receiving coil to obtain an effective frequency signal; According to the effective frequency signal and the temperature detection signal, formation water salinity data is obtained by fitting.

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