CN110414169B - Fourier infrared gas logging method and device thereof - Google Patents
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Abstract
The invention provides a Fourier infrared gas logging method and a device thereof, wherein the method comprises the following steps: s1, drying and purifying gas in drilling fluid; s2, carrying out Fourier infrared spectrogram measurement on the gas subjected to drying and purification to obtain Fourier infrared spectrogram data; s3, calculating concentration content of each component according to the measured Fourier infrared spectrogram data; the step S3 further includes: s31, performing dimension reduction processing on the infrared spectrogram data measured in the step S2 to obtain first infrared dimension reduction data; s32, forecasting the first infrared dimensionality reduction data to obtain a preliminary forecasting result; and S33, screening a database of the preliminary forecasting result, and carrying out dynamic modeling quantitative forecasting analysis to obtain the concentration content of each component. The advantages are that: by dimension reduction of the infrared spectrogram data, the complexity of the infrared spectrogram data can be greatly reduced and the system operation speed can be improved while the validity of information in the infrared spectrogram data and interference are ensured.
Description
Technical Field
The invention relates to the technical field of geological logging engineering on petroleum drilling sites, in particular to a Fourier infrared gas logging method and a device thereof.
Background
The infrared absorption spectrum is a spectrum formed by a transition of a vibration-rotation energy level of a molecule caused by absorption of infrared radiation by a molecule of a substance, and is called an infrared spectrum because it appears in the infrared region. Infrared radiation was found in 1800 years by william-helschel in the uk. The infrared absorption spectrum of pure substances was studied at the beginning of 1903. During world war ii, the infrared spectrum has only attracted attention and research by chemists due to the urgent need for synthetic rubber and has therefore evolved rapidly. Since it reflects the characteristic absorption of specific groups and chemical bonds in a molecule, it is an analytical method that is extremely useful for identifying organic compounds and determining the structure of a molecule that is widely used.
As an important analysis means, the research of the application of infrared spectroscopic analysis in the field of oil exploration has been in the past several decades. Many geologists and organic geochemists at home and abroad successfully divide the types of the raw kerogen by utilizing infrared spectra, evaluate the hydrocarbon production potential, determine the maturity and the like. At the end of the 70 s, research and development rooms of the Moscow Gu Bojin institute of Petroleum chemistry and natural gas industry and information and measurement technology have developed a scientific research work for rapidly identifying the oil, gas and drilling profile while drilling by using an infrared spectroscopy.
Since the beginning of the sixties, crude oil, biogenetic rock, asphalt, kerogen and the like are analyzed in succession, so that the knowledge of petroleum geology and geochemistry is deepened, and the analysis technology is basically popularized by the petroleum institute. With the development of infrared spectrum technology and computer technology, the application of infrared spectrum in the field of petroleum exploration is more widely studied.
After selective absorption of infrared radiation by molecules of the substance, transitions in the vibrational and rotational energy levels within the molecule are created. If continuous infrared radiation is passed through the measured substances one by an infrared spectrometer, and the transmittance (T) of the infrared radiation is measured one by one and recorded, the infrared absorption spectrum of the substances is obtained. The class of the related compounds is determined by determining which groups are contained based on the characteristic spectrum bands of the infrared spectrum of the compounds, which is an infrared qualitative analysis. Infrared spectroscopy is also commonly used for quantitative analysis, which is based on the principle of calculating the absorbance of a characteristic band of a group in a substance molecule from a spectrum. The calculation formula is that
A＝lgI 0 /I＝lg1/T
Wherein A is absorbance, I 0 For the incident light intensity, I is the transmitted light intensity and T is the transmittance. Then, according to beer's law (a=kbc), the concentration c of the substance can be calculated, and the content of the substance can be calculated.
In the conventional petroleum exploration, the hydrogen flame gas chromatography logging system 12 shown in fig. 1 is mostly adopted, and in order to ensure normal operation, the hydrogen flame gas chromatography logging system 12 is generally required to be equipped with auxiliary production equipment such as an air compressor 123, a hydrogen generator 122, a sample preprocessor 121, etc., but the prices of the air compressor 123 and the hydrogen generator 122 are at a higher level, and the hydrogen flame gas chromatography logging system 12 comprises various vulnerable devices such as air resistance, a pressure stabilizing valve, a flow valve, etc., so that the stability of the whole system equipment is lower, and the service period is shorter. Accordingly, infrared spectroscopy has been increasingly applied to the field of oil exploration.
In general, the infrared analysis technology is the most used non-dispersive infrared analysis technology, and is generally to measure the concentration of a sample by adopting an infrared light source together with an optical filter and a sensor, which is not very suitable for various gas exploration in the petroleum exploration field, so that an infrared analysis system and method which have simple structure, are convenient to maintain and can perform tests with different wavelengths are urgently needed.
Disclosure of Invention
The invention aims to provide a Fourier infrared gas logging method and a device thereof, wherein the Fourier infrared gas logging method tests gas components through a Fourier infrared analyzer to obtain Fourier infrared spectrogram data, then performs dimension reduction processing on the Fourier infrared spectrogram data, combines the dimension reduced Fourier infrared spectrogram data with a quantitative prediction model to obtain concentration content of each component, and can greatly reduce complexity of the Fourier infrared spectrogram data and improve the system operation speed while ensuring the effectiveness of the Fourier infrared spectrogram data information and reducing interference.
In order to achieve the above purpose, the present invention is realized by the following technical scheme:
a fourier infrared gas logging method comprising the steps of:
s1, drying and purifying gas in drilling fluid;
s2, carrying out Fourier infrared spectrogram measurement on the gas subjected to drying and purification to obtain Fourier infrared spectrogram data;
s3, calculating concentration content of each component according to the measured Fourier infrared spectrogram data;
the step S3 further includes:
s31, performing dimension reduction processing on the Fourier infrared spectrogram data measured in the step S2 to obtain first infrared dimension reduction data;
s32, forecasting the first infrared dimensionality reduction data to obtain a preliminary forecasting result;
and S33, screening a database of the preliminary forecasting result, and carrying out dynamic modeling quantitative forecasting analysis to obtain the concentration content of each component.
Preferably, the concentration content of each component is the content of each alkane gas component.
Preferably, the alkane gas component comprises any one or more of methane C1, ethane C2, propane C3, isobutane iC4, n-butane nC4, isopentane iC5, n-pentane nC5.
Preferably, in the step S33, a quantitative prediction model is adopted to perform quantitative prediction analysis on the preliminary prediction result;
the step S33 specifically includes:
s331, judging the concentration according to a preliminary forecasting result, and selecting a preset dimension reduction method to obtain a second infrared dimension reduction data;
s332, screening data in the database according to the correlation of the second infrared data reduction data to obtain a first database;
s333, judging the components and the concentration of the preliminary forecasting result, and selecting a data mining method matched with the first database;
s334, obtaining a quantitative forecasting model through dynamic quantitative modeling by utilizing the first database and a data mining method matched with the first database;
s335, carrying out quantitative prediction by using the quantitative prediction model and the second infrared dimension reduction data to obtain a quantitative prediction result, wherein the quantitative prediction result is the content of each gas component.
Preferably, the dimension reduction method in step S31 and/or step S331 adopts a partial least square method or an artificial neural network method or a principal component analysis method.
Preferably, the step S332 specifically includes:
respectively performing linear fitting on the second infrared dimensionality reduction data and data samples in a database, and calculating correlation coefficients of the second infrared dimensionality reduction data and the data samples to perform correlation sample screening;
and selecting data samples with high correlation coefficients in the databases to form a dynamic modeling database which is a first database.
Preferably, the data mining method in step S333 is a partial least squares method or an artificial neural network method or a principal component analysis method.
Preferably, a fourier infrared gas logging device based on the fourier infrared gas logging method, the device comprises:
the gas drying and purifying device is used for drying and purifying the gas in the drilling fluid;
the Fourier infrared analyzer is used for carrying out infrared spectrogram measurement on the gas subjected to the drying purification;
and the computer is used for analyzing and processing the infrared spectrogram measured by the Fourier infrared analyzer and calculating the content of each component.
Compared with the prior art, the invention has the following advantages:
(1) Compared with a hydrogen flame color spectrum technology, the Fourier infrared gas logging method has the characteristics of high response speed, real-time monitoring and the like, for example, the change condition of the methane gas content of a stratum can be well tracked through online infrared detection of the methane content in drilling fluid, and a well team can make decision in time conveniently;
(2) According to the Fourier infrared gas logging method, the infrared spectrogram data is subjected to dimension reduction, so that the information validity in the infrared spectrogram data is ensured, the interference is reduced, the complexity of the infrared spectrogram data is greatly reduced, and the system operation speed is improved;
(3) The Fourier infrared gas logging method is novel in design, high in forecasting accuracy and high in analysis speed; the infrared spectrogram data of the gas separated from the drilling fluid is subjected to preliminary forecast and accurate quantitative forecast, so that the rapid, accurate and quantitative analysis of the drilling fluid gas logging data in the drilling fluid slurry is realized, the requirements of rapid and efficient logging on the oil gas exploration site can be met, and the method is suitable for the requirements of modern petroleum exploration drilling;
(4) The Fourier infrared gas logging device comprises a gas drying and purifying device, a Fourier infrared analyzer and a computer containing analysis software, is compared with hydrogen flame chromatographic analysis equipment, basically adopts a modularized processing mode in the development process of equipment design, has simple structure and low cost, reduces various vulnerable devices such as gas resistance, pressure stabilizing valves, flow valves and the like, saves auxiliary production equipment, improves the stability of the equipment, is convenient for maintenance and maintenance in daily work, has low requirements on field application technicians, lays a foundation for wide application, and basically can ensure that repeated calibration is not needed within one year after one-time performance calibration of the equipment, and only needs occasional standard gas sample injection detection in the field application process because the technology has the characteristics;
(5) The Fourier infrared gas logging device has stable performance, usually, in order to ensure the normal operation of equipment, auxiliary production equipment such as an air compressor, a sample preprocessor and the like are required to be arranged in a hydrogen flame gas chromatography logging system, and the Fourier infrared gas logging device only requires sample gas to flow through an analysis air chamber according to a stable flow rate in the detection process of the sample gas due to the utilization of an optical absorption analysis gas principle, so that the auxiliary production equipment is not required, and the failure rate is reduced;
(6) The Fourier infrared gas logging device has higher cost performance, and related products of infrared absorption technology are rapidly increased along with the rapid development of domestic infrared optical absorption technology in recent years, so that the manufacturing cost of the Fourier infrared analyzer is relatively reduced; meanwhile, the prices of the air compressor and the hydrogen generator are at a higher level, so that the Fourier infrared gas logging device has obvious price advantage.
Drawings
FIG. 1 is a schematic workflow diagram of a prior art hydrogen flame chromatography system and a Fourier infrared analysis system of the present invention;
FIG. 2 is a schematic flow chart of a method for analyzing and processing spectrogram data of a Fourier infrared gas logging method.
Detailed Description
The invention will be further described by the following detailed description of a preferred embodiment, taken in conjunction with the accompanying drawings.
As shown in fig. 1, the fourier infrared gas logging device of the present invention is a fourier infrared analysis system 11, and is particularly suitable for various gas exploration in the petroleum exploration field, and the device mainly comprises: a gas drying and purifying device 111, a Fourier infrared analyzer 112 and a computer 113 containing analysis software. The specific action process is as follows:
s1, gas in drilling fluid which is degassed and separated from a slurry tank enters a Fourier infrared analysis system 11, and the gas in the drilling fluid is dried and purified by a gas drying and purifying device 111;
s2, directly entering an optical path cell of the Fourier infrared analyzer 112 for Fourier infrared spectrogram measurement after the gas is dried and purified;
s3, the measured Fourier infrared spectrum data enter a computer 113 containing analysis software, the computer 113 analyzes and processes the Fourier infrared spectrum data of the gas, and the concentration content of each alkane gas component is calculated, wherein the alkane gas component comprises: methane C1, ethane C2, propane C3, isobutane iC4, n-butane nC4, isopentane iC5, n-pentane nC5.
As shown in fig. 2, the specific spectrogram data analysis processing procedure is as follows:
s31, performing Partial Least Squares (PLS) dimension reduction on Fourier infrared spectrogram data measured in the step S2 aiming at different alkane gas components (methane C1, ethane C2, propane C3, isobutane iC4, n-butane nC4, isopentane iC5 and n-pentane nC 5) to obtain infrared dimension reduction data 1;
the dimension reduction method can also be an artificial neural network method or a principal component analysis method, and can reduce the dimension of the infrared spectrogram data, ensure the information validity in the infrared spectrogram data, reduce the interference, greatly reduce the complexity of the infrared spectrogram data and improve the system operation speed;
s32, forecasting the infrared dimension reduction data 1 by a partial least square method to obtain a preliminary forecasting result;
and S33, screening a database of the preliminary forecasting result, and carrying out dynamic modeling quantitative forecasting analysis to obtain the concentration content of each component. The database is a complete database established through a large number of tests in the early stage and comprises various test data.
In the step S33, a calculation method corresponding to a quantitative prediction model is adopted to perform quantitative prediction analysis on the preliminary prediction result; the step S33 specifically includes:
s331, judging the concentration of the components according to the preliminary forecasting result, selecting a preset dimension reduction method, and carrying out dimension reduction on the Fourier infrared spectrogram data again to obtain infrared dimension reduction 2.
S332, judging the component concentration of the preliminary forecasting result, and comparing the correlation to obtain a first database with the highest correlation; the method comprises the following steps: and (3) carrying out correlation screening on the database according to the infrared dimension reduction data 2 obtained in the step (S331) to obtain a first database. The concentration content range of the sample data in the first database is closest to the preliminary forecasting result, so that the accuracy of quantitative forecasting of the unknown gas sample can be improved;
the suitable dimension reduction method in step S331 is a partial least square method or an artificial neural network method or a principal component analysis method.
The step S332 specifically includes:
(1) Respectively performing linear fitting on the infrared dimensionality reduction data 2 and data samples in a database, and calculating correlation coefficients of the data samples to perform correlation sample screening; (2) And selecting data samples with high correlation coefficients in the database to form a dynamic modeling database, namely a first database.
The related sample screening method can be used for screening out data samples most related to measured gas rapidly and effectively, and is beneficial to establishing a quantitative and accurate quantitative forecasting model.
Because of the complex alkane components in the gas separated from the drilling fluid and their strong interference of infrared absorption peaks, the accuracy of infrared gas logging is severely affected. By adopting the linear fitting method, the data sample with high correlation coefficient in the first database is selected, and the reference sample with the most similar components and concentration content of the gas to be detected can be obtained from the selected first database, so that the forecasting accuracy can be greatly improved, and meanwhile, the method is rapid in operation, and the real-time performance of system forecasting can be effectively improved.
S333, selecting a data mining method matched with the first database according to different forecasting object components and different concentration contents of different object components in the primary forecasting result, wherein the data mining method can be a PLS (PLS), an artificial neural network method or a principal component analysis method.
S334, obtaining a quantitative prediction model through dynamic quantitative modeling by using the first database obtained in the step S332 and the data mining method matched with the modeling database in the step S333;
the data mining method in the step S333 adopts a partial least square method or an artificial neural network method or a principal component analysis method, is suitable for infrared analysis of hydrocarbon components of gas logging in oil and gas exploration, and can rapidly and accurately forecast the concentration content of the hydrocarbon components; the quantitative forecasting model is obtained through experimental determination according to different alkane components and different concentration contents of the same components.
S335, quantitatively forecasting by using the quantitative forecasting model and the infrared dimension reduction data 2 to obtain quantitative forecasting results, wherein the quantitative forecasting results are the content of each gas component; the method comprises the following steps: substituting the infrared dimension reduction data 2 into the quantitative prediction model, quantitatively predicting the gas sample, and outputting, displaying and storing.
The method is the whole process of the software forecast analysis of the Fourier infrared gas logging, and accurate drilling fluid gas logging data can be obtained quickly and online by carrying out preliminary forecast and accurate quantitative forecast on infrared spectrogram data of gas separated from drilling fluid.
In conclusion, the Fourier infrared field gas logging method provided by the invention is novel in design, high in forecasting accuracy and high in analysis speed. The invention has the advantages of simple result, high reliability, better cost performance than gas chromatography logging, and suitability for the requirements of modern petroleum exploration drilling.
While the present invention has been described in detail through the foregoing description of the preferred embodiment, it should be understood that the foregoing description is not to be considered as limiting the invention. Many modifications and substitutions of the present invention will become apparent to those of ordinary skill in the art upon reading the foregoing. Accordingly, the scope of the invention should be limited only by the attached claims.
Claims (4)
1. A fourier infrared gas logging method comprising the steps of:
s1, drying and purifying gas in drilling fluid;
s2, carrying out Fourier infrared spectrogram measurement on the gas subjected to drying and purification to obtain Fourier infrared spectrogram data;
s3, calculating concentration content of each component according to the measured Fourier infrared spectrogram data;
the step S3 further includes:
s31, performing dimension reduction processing on the Fourier infrared spectrogram data measured in the step S2 to obtain first infrared dimension reduction data;
s32, forecasting the first infrared dimensionality reduction data to obtain a preliminary forecasting result;
s33, screening a database of the preliminary forecasting result, and carrying out dynamic modeling quantitative forecasting analysis to obtain the concentration content of each component;
in the step S33, a quantitative prediction model method is adopted to perform quantitative prediction analysis on the preliminary prediction result;
the step S33 specifically includes:
s331, judging the concentration according to a preliminary forecasting result, and selecting a preset dimension reduction method to obtain a second infrared dimension reduction data;
s332, screening data in the database according to the correlation of the second infrared data reduction data to obtain a first database;
s333, judging the components and the concentration of the preliminary forecasting result, and selecting a data mining method matched with the first database;
s334, obtaining a quantitative forecasting model through dynamic quantitative modeling by utilizing the first database and a data mining method matched with the first database;
s335, quantitatively forecasting by using the quantitative forecasting model and the second infrared dimension-reducing data to obtain quantitative forecasting results, wherein the quantitative forecasting results are the content of each gas component;
the step S332 specifically includes:
respectively performing linear fitting on the second infrared dimensionality reduction data and data samples in a database, and calculating correlation coefficients of the second infrared dimensionality reduction data and the data samples to perform correlation sample screening;
selecting data samples with high correlation coefficients in a database to form a dynamic modeling database which is a first database;
the dimension reduction method in the step S31 and/or the step S331 adopts a partial least square method or an artificial neural network method or a principal component analysis method;
the data mining method in step S333 is a partial least square method or an artificial neural network method or a principal component analysis method.
2. A Fourier infrared gas logging method as in claim 1, wherein,
the concentration content of each component is the content of each alkane gas component.
3. A Fourier infrared gas logging method as in claim 2, wherein,
the alkane gas component comprises any one or more of methane C1, ethane C2, propane C3, isobutane iC4, n-butane nC4, isopentane iC5, n-pentane nC5.
4. A fourier ir logging apparatus based on a fourier ir logging method as in any of claims 1-3, comprising:
a gas drying and purifying device (111) for drying and purifying the gas in the drilling fluid;
a Fourier infrared analyzer (112) for performing infrared spectrogram measurement of the dried and purified gas;
and the computer (113) is used for analyzing and processing the infrared spectrogram measured by the Fourier infrared analyzer (112) and calculating the content of each component.
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| CN114923873A (en) * | 2022-05-27 | 2022-08-19 | 江苏蓝创智能科技股份有限公司 | Gas concentration detection method and device, electronic equipment and storage medium |
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