An online detection method based on quantum dot tracers for oil fields

Abstract

The invention discloses an online detection method based on a quantum dot tracer for oil fields, which relates to the technical field of oil field tracer detection, and comprises the following steps: S1, adding a quantum dot tracer to the construction fluid injected into each section of the formation for tracing; S2, using an online detection device to detect the quantum dot signal in the return fluid, and collecting the fluid properties of the return fluid; S3, establishing a spectrum conversion model, converting the quantum dot signal into spectral data illumination, judging the type of the quantum dot tracer, and thus determining which section of the formation the return fluid comes from; S4, establishing an illumination conversion model, converting the spectral illumination into quantum dot signal intensity, and using a quantum dot return volume calculation model to calculate the return volume of the quantum dot, thereby determining the return volume of the fracturing fluid in each section of the formation. The invention can present the tracer results in real time and quickly, which is helpful for implementing decision-making and quickly responding to formation changes, reducing the test cycle, and reducing the overall construction interpretation cost of the tracer quantum dots.

Description

Technical Field

[0001] The invention relates to the technical field of oilfield tracer detection, in particular to an online detection method based on a quantum dot tracer for oilfields. Background Art

[0002] With the development of oilfield tracing, from chemical tracers, isotope tracers, trace element tracers to the current quantum tracers. No matter which tracer is used, the whole process from on-site sampling, sample classification and transportation, sample processing, and sample instrument analysis is time-consuming and labor-intensive. Generally, it takes more than two months to obtain a tracer report. Due to the tight construction schedule on site, the construction on site often begins before the tracer report of the reference well is obtained, resulting in the reference well tracer report having no guiding significance for the later well group construction design. The main reason for the long time required for the tracer report to be issued is that direct sample testing cannot be carried out on site. The samples need to be stored in batches and then sent to the laboratory for testing with professional instruments. Subjective factors such as sample batches, sample delivery intervals, and sample delivery personnel cannot be determined and controlled, which often leads to delays in the issuance of tracer reports and loss of timeliness.

[0003] Different tracers correspond to different instrument tests. Currently, the more common tracer instruments for measuring quantum dot fluorescent substances are: spectrophotometer, flow cytometer; chemical tracers are: GCMS, MS, etc.; trace element tracers are: ICP-MS, etc. These instruments are expensive, large in size, heavy in weight, and the samples tested need to be specially processed. Therefore, they cannot be configured at will on site, and the samples can only be sent back to the laboratory for testing, which prolongs the detection time of on-site tracer samples. Summary of the invention

[0004] The purpose of the present invention is to provide an online detection method based on quantum dot tracers for oil fields, and the purpose is to monitor the distribution and state of quantum dots in real time.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] An online detection method based on a quantum dot tracer for oil fields comprises the following steps:

[0007] S1. Add a quantum dot tracer to the construction fluid injected into each formation for tracing and number the quantum dot tracers;

[0008] S2. Detecting quantum dot signals in the return fluid using online detection equipment and collecting fluid properties of the return fluid;

[0009] S3. Establish a spectrum conversion model to convert quantum dot signals into spectral data illumination, determine the type of quantum dot tracer, and thus determine which stratum the return fluid comes from;

[0010] S4. Establish an illumination conversion model to convert the spectral illumination into quantum dot signal intensity, and use the quantum dot return flow calculation model to calculate the return flow of the quantum dots, thereby determining the return flow of the fracturing fluid in each section of the formation.

[0011] Preferably, in S1, the content of quantum dot tracer in the construction fluid injected into each formation section is the same.

[0012] Preferably, the content of the quantum dot tracer in the construction fluid is 0.6-1 mg / L.

[0013] Preferably, in S2, the fluid properties include temperature, pH value and turbidity of the fluid.

[0014] Preferably, in S3, the calculation expression of the spectrum conversion model is:

[0015] ;

[0016] In the formula, is the illumination; is the correction parameter factor; is the wavelength of the incident light; is the angle between the incident light and the micro-spectrometer; is the distance from the built-in light source to the micro-spectral sensor; is the dispersion coefficient; is the characteristic wavelength.

[0017] Preferably, in S4, the calculation expression of the illumination conversion model is:

[0018] ;

[0019] ;

[0020] The calculation expression of the quantum dot return flow calculation model is:

[0021] ;

[0022] ;

[0023] ;

[0024] ;

[0025] In the formula, The quantum dot signal strength detected by the detection device in real time; is the corrected quantum dot signal intensity; for The quantum dot light intensity signal after calibration with the standard curve; Mark the segment number of the stratum for the quantum dots, such as segment 1, segment 2, etc.; is the temperature of the fluid during testing; is the pH value of the fluid during testing; is the turbidity of the fluid during testing; is the comprehensive factor affecting the signal intensity of quantum dots; is the number of parameters that affect the quantum dot light intensity signal; is the fluid temperature of the quantum dots when establishing the standard curve; is the pH value of the fluid in which the quantum dots are located when the standard curve is established.

[0026] Preferably, the detection device includes a controller, on which a micro-spectral sensor, a pH sensor, a temperature sensor, a turbidity sensor and a display screen are provided. The pH sensor, the temperature sensor and the turbidity sensor are mainly used to collect the temperature, pH value and turbidity information of the fluid in which the quantum dots pass in real time.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] (1) The detection device of the present invention has the advantages of real-time data collection and timely output of results, which not only saves the cost of on-site construction work in oil and gas fields, but also saves manpower and material resources, and helps to reduce construction risks.

[0029] (2) The present invention can collect data in real time and present tracing results in real time, thus achieving faster formation tracing detection, facilitating decision-making and rapid response to formation changes, and reducing labor costs, testing cycles, and the overall construction interpretation cost of tracing quantum dots. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a schematic diagram of a flow chart of an embodiment of the present invention;

[0031] Figure 2 This is a schematic diagram of the principle of a micro-spectrometer;

[0032] Figure 3 It is a schematic diagram of the spectral illumination of the present invention;

[0033] Figure 4 This is a graph showing the relationship between the quantum dot signal intensity and illumination of the present invention;

[0034] Figure 5 It is a schematic diagram of a liquid production cross section of an embodiment of the present invention;

[0035] Figure 6 Schematic diagram of the structure of the microfluidic channel of the present invention. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0037] See also Figure 1 , an online detection method based on quantum dot tracers for oil fields, comprising the following steps:

[0038] S1. According to the construction plan, the quantum dot tracer is injected into each section of the horizontal well along with the construction fluid. A quantum dot tracer is added to the construction fluid injected into each section of the formation for tracing, and the quantum dot tracers are numbered. In this embodiment, the quantum dot tracers selected for the four construction well sections are numbered as follows: QD-1, QD-2, QD-3, and QD-4, and the characteristic peaks are 377nm, 475nm, 515nm, and 750nm, respectively. The amount of quantum dot tracer added to each section of the formation is fixed, and the proportion of quantum dot tracer in the construction fluid is 1 mg / L.

[0039] S2. After the on-site construction is completed, the return fluid quantum dot signal is detected by online detection equipment, and the return fluid fluid properties are collected;

[0040] like Figure 6 As shown, the online detection device includes a controller, and the controller is respectively connected with a micro-spectral sensor, a pH value sensor, a temperature sensor, a turbidity sensor and a display screen. The online detection device also includes a mobile power supply to provide power for the entire device, and the mobile power supply is a lithium battery. The display screen is an LED display screen.

[0041] The controller can be a microcomputer, a PLC controller, a single-chip microcomputer, a digital signal processor, or an embedded processor. The controller is mainly responsible for receiving data transmitted by the sensor, performing internal function calculations, and displaying the calculation results on the display screen. It can monitor and test the entire production process of the oil and gas well in real time according to the actual situation on site.

[0042] The micro-spectral sensor contains a light source and a filter, etc., to achieve absorption, scattering and refraction of light.

[0043] The pH sensor is used to collect the pH value of the fluid in which the quantum dots pass, the temperature sensor is used to collect the temperature value of the fluid in which the quantum dots pass, and the turbidity sensor is used to collect the turbidity of the fluid in which the quantum dots pass. The pH value, temperature value and turbidity are input into the controller for calculation and processing.

[0044] When the turbidity sensor is in use, the light source emits light, and when the light passes through the liquid sample containing suspended particles, it will produce a scattering phenomenon on the surface of the particles, part of the light is scattered by the suspended matter, and part of the light passes through the liquid. The turbidity sensor measures the intensity of the scattered light and converts it into an electrical signal, and after processing, outputs the turbidity value.

[0045] The calculation formula of the turbidity value is:

[0046] ;

[0047] Where, is a constant; is the intensity of scattered light waves; is the number of particles per unit solution; is the particle volume.

[0048] S3. The quantum dot signal is converted into spectral data illumination through a spectral conversion model to determine the type of quantum dot tracer, thereby determining which stratum the return fluid comes from;

[0049] The spectrum conversion model is:

[0050] ;

[0051] In the formula, is the illumination; is the correction parameter factor; is the wavelength of the incident light; is the angle between the incident light and the micro-spectrometer; is the distance from the built-in light source to the micro-spectral sensor; is the dispersion coefficient; is the characteristic wavelength.

[0052] like Figure 3 As shown, the calculation results can be directly displayed on the LED display screen, where the characteristic wavelength of quantum dots and specific illumination data can be directly read out. The characteristic wave of quantum dots can be directly read out on the spectral image to determine the type of quantum dots. Since each section of construction is marked with only one type of quantum dot, knowing the type of quantum dot can deduce which section the return fluid comes from.

[0053] S4. The spectral illumination is converted into quantum dot signal intensity through the illumination conversion model, and the quantum dot return flow calculation model is used to calculate the quantum dot return flow. Since the quantum dot injection volume of each section is the same, the return flow ratio of each quantum dot represents the return flow ratio of each section of the construction liquid volume. After calculation, the calculation results will be directly transmitted to the LED display, as shown in the following table. The liquid production profile is as follows: Figure 5As shown in the figure, the amount of backflow in each section of the construction well at each moment is reflected, and the difference in liquid production between each section, the comparison of the cumulative liquid production of each section, and the total liquid production of each section can be intuitively obtained.

[0054] Table 1 Statistics of liquid production of each short return

[0055]

[0056] The quantum dot type and quantum dot content can be converted by the following two functions;

[0057] The calculation expression of the illumination conversion model is:

[0058] ;

[0059] ;

[0060] The illumination of different concentrations of the same type of quantum dots and spectral data is a linear formula. By establishing standard curves of various quantum dot concentrations and illumination, the concentration content of the quantum dots can be calculated from the illumination data.

[0061] The calculation expression of the quantum dot return flow calculation model is:

[0062] ;

[0063] ;

[0064] ;

[0065] ;

[0066] In the formula, The quantum dot signal strength detected by the detection device in real time; is the corrected quantum dot signal intensity (is the detected quantum dot signal intensity The actual quantum dot intensity corrected by the comprehensive factor of factors that affect the quantum dot signal); for After the standard curve ( ) The calibrated quantum dot light intensity signal; The number of segments marking the formation for the quantum dots; is the temperature of the fluid during testing; is the pH value of the fluid during testing; is the turbidity of the fluid during testing; is the comprehensive factor affecting the signal intensity of quantum dots; is the number of parameters that affect the quantum dot light intensity signal; is the fluid temperature of the quantum dots when establishing the standard curve; is the pH value of the fluid where the quantum dots are located when the standard curve is established; the correction function is the intensity function of the influence of the construction conditions before construction, such as temperature, well temperature, and formation residence time, on the quantum dot signal. The correction function is:

[0067] ;

[0068] In the formula, is the temperature at the bottom of the quantum dot well; is the residence time of quantum dots at the bottom of the well.

[0069] The present invention utilizes the unique optical properties of quantum dots and realizes high-precision capture measurement and high-resolution detection of formation tracer quantum dots through a computational model. Various sensors are based on the characteristics of quantum dots and fluids, and can capture tiny changes in quantum dots and fluids, thereby calculating changes in the formation online, providing more reliable data for more accurate tracing results. The controller can use the above calculation formula to change the operating parameters at any time according to the on-site well conditions, such as well temperature, formation diffusion coefficient, and quantum dot expected bottom hole residence time, through various sensors, so that online detection tests are more flexible and can adapt to different types of oil and gas well tests. Traditional oil and gas well tests usually take days or weeks to obtain sufficient data, while the present invention can directly collect data in real time, present tracing results in real time, and achieve faster formation tracing detection, which is helpful for decision-making and rapid response to formation changes, and reduces labor costs, reduces testing cycles, and reduces the overall construction interpretation cost of tracing quantum dots.

Claims

1. An online detection method based on quantum dot tracers for oil fields, characterized in that: The following steps are involved: S1. Add a quantum dot tracer to the construction fluid injected into each formation for tracing and number the quantum dot tracers; S2. Detecting quantum dot signals in the return fluid using online detection equipment and collecting fluid properties of the return fluid; S3. Establish a spectrum conversion model to convert quantum dot signals into spectral data illumination, determine the type of quantum dot tracer, and thus determine which stratum the return fluid comes from; The calculation expression of the spectrum conversion model is: Where, h(λ) is the illumination; φ is the transmittance correction parameter factor; λ0 is the wavelength of the incident light; c is the angle between the incident light and the micro-spectrometer; L is the distance from the built-in light source to the micro-spectrometer; b is the scatter coefficient; λ is the characteristic wavelength; S4. Establish an illumination conversion model to convert the spectral illumination into quantum dot signal intensity, and use the quantum dot return flow calculation model to calculate the return flow of the quantum dots, thereby determining the return flow of the fracturing fluid in each section of the formation.

2. The online detection method based on quantum dot tracers for oil fields according to claim 1, characterized in that: In S1, the content of quantum dot tracer in the construction fluid injected into each formation section is the same.

3. The online detection method based on quantum dot tracers for oil fields according to claim 2, characterized in that: The content of the quantum dot tracer in the construction fluid is 0.6-1 mg / L.

4. The online detection method based on quantum dot tracers for oil fields according to claim 1, characterized in that: In S2, the fluid properties include temperature, pH value and turbidity of the fluid.

5. The online detection method based on quantum dot tracers for oil fields according to claim 1, characterized in that: In S4, the calculation expression of the illumination conversion model is: y=F i =987.45x-140.51; R 2 ＝0.9931； The calculation expression of the quantum dot return flow calculation model is: F i校 =F i ÷y(x); y(x)=A*exp(-x / a)+B*exp(-x / b)+y0; F i校 =a×c i校 +b; The standard curve is: F i校 =a×c i校 +b; The correction function is: In the formula, F i F is the quantum dot signal strength detected by the detection device in real time; i校 is the corrected quantum dot signal intensity; c i校 F i校 The quantum dot light intensity signal after correction by the standard curve; i is the number of segments marked by quantum dots; a is the temperature of the fluid during detection; b is the pH value of the fluid during detection; y0 is the turbidity of the fluid during detection; y(x) is the comprehensive factor affecting the quantum dot signal intensity; x is the number of parameters affecting the quantum dot light intensity signal; A is the fluid temperature of the quantum dots when establishing the standard curve; B is the pH value of the fluid of the quantum dots when establishing the standard curve; t is the bottom hole residence temperature of the quantum dots; h is the bottom hole residence time of the quantum dots.

6. The on-line detection method based on quantum dot tracers for oil fields according to claim 1, characterized in that: The online detection device comprises a controller, on which a micro-spectral sensor, a pH value sensor, a temperature sensor, a turbidity sensor and a display screen are arranged.

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