CN108593584A - A kind of quantitative analysis method being applied to multicomponent mud logging gas infrared spectrum in situ - Google Patents
A kind of quantitative analysis method being applied to multicomponent mud logging gas infrared spectrum in situ Download PDFInfo
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- 238000011065 in-situ storage Methods 0.000 title claims abstract description 21
- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000002329 infrared spectrum Methods 0.000 title claims abstract description 15
- 238000004445 quantitative analysis Methods 0.000 title claims abstract description 14
- 230000001537 neural effect Effects 0.000 claims abstract description 5
- 239000007789 gas Substances 0.000 claims description 62
- 238000001228 spectrum Methods 0.000 claims description 22
- 238000010521 absorption reaction Methods 0.000 claims description 8
- QWTDNUCVQCZILF-UHFFFAOYSA-N isopentane Chemical compound CCC(C)C QWTDNUCVQCZILF-UHFFFAOYSA-N 0.000 claims description 8
- 238000000354 decomposition reaction Methods 0.000 claims description 7
- NNPPMTNAJDCUHE-UHFFFAOYSA-N isobutane Chemical compound CC(C)C NNPPMTNAJDCUHE-UHFFFAOYSA-N 0.000 claims description 6
- ATUOYWHBWRKTHZ-UHFFFAOYSA-N Propane Chemical compound CCC ATUOYWHBWRKTHZ-UHFFFAOYSA-N 0.000 claims description 4
- AFABGHUZZDYHJO-UHFFFAOYSA-N dimethyl butane Natural products CCCC(C)C AFABGHUZZDYHJO-UHFFFAOYSA-N 0.000 claims description 4
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 claims description 4
- 238000012937 correction Methods 0.000 claims description 3
- 239000001282 iso-butane Substances 0.000 claims description 3
- 235000013847 iso-butane Nutrition 0.000 claims description 3
- IJDNQMDRQITEOD-UHFFFAOYSA-N sec-butylidene Natural products CCCC IJDNQMDRQITEOD-UHFFFAOYSA-N 0.000 claims description 3
- OTMSDBZUPAUEDD-UHFFFAOYSA-N Ethane Chemical compound CC OTMSDBZUPAUEDD-UHFFFAOYSA-N 0.000 claims description 2
- 230000035772 mutation Effects 0.000 claims description 2
- 239000001294 propane Substances 0.000 claims description 2
- 230000001850 reproductive effect Effects 0.000 claims 1
- 238000004458 analytical method Methods 0.000 abstract description 9
- 238000005553 drilling Methods 0.000 abstract description 2
- 230000002068 genetic effect Effects 0.000 abstract description 2
- 239000004615 ingredient Substances 0.000 abstract description 2
- 238000001157 Fourier transform infrared spectrum Methods 0.000 abstract 1
- 239000000523 sample Substances 0.000 description 17
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 5
- 238000001514 detection method Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 239000012159 carrier gas Substances 0.000 description 3
- 238000004587 chromatography analysis Methods 0.000 description 3
- 230000003595 spectral effect Effects 0.000 description 3
- 238000004611 spectroscopical analysis Methods 0.000 description 3
- 230000005526 G1 to G0 transition Effects 0.000 description 2
- 238000009835 boiling Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 238000004817 gas chromatography Methods 0.000 description 2
- 229910052757 nitrogen Inorganic materials 0.000 description 2
- 239000012188 paraffin wax Substances 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 239000004215 Carbon black (E152) Substances 0.000 description 1
- 150000001335 aliphatic alkanes Chemical class 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 235000013405 beer Nutrition 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000009395 breeding Methods 0.000 description 1
- 230000001488 breeding effect Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 229910001873 dinitrogen Inorganic materials 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000012530 fluid Substances 0.000 description 1
- 230000004907 flux Effects 0.000 description 1
- 238000004868 gas analysis Methods 0.000 description 1
- 238000003306 harvesting Methods 0.000 description 1
- 229930195733 hydrocarbon Natural products 0.000 description 1
- 150000002430 hydrocarbons Chemical class 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 239000006101 laboratory sample Substances 0.000 description 1
- 238000004811 liquid chromatography Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000004451 qualitative analysis Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 238000001179 sorption measurement Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3504—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing gases, e.g. multi-gas analysis
Abstract
The invention belongs to mud logging gas analyses to apply, and be related to a kind of quantitative analysis method being applied to multicomponent mud logging gas infrared spectrum in situ.The FTIR spectrum that this method passes through analysis mud logging gas, establish the prediction model based on genetic algorithm and radial base neural net, mud logging gas in situ is analyzed by model, obtain mud logging gas ingredient and its content, it realizes quickly analysis landwaste oil-containing situation, judges current drilling depth air content.A kind of quantitative analysis method being applied to multicomponent mud logging gas infrared spectrum in situ designed by the present invention, is better than traditional chromatogram analysis method, can analyze quickly, in real time, it was therefore concluded that, it is more efficient, quick.
Description
Technical field
The present invention relates to a kind of quantitative analysis methods being applied to multicomponent mud logging gas infrared spectrum in situ, more specifically
It says, the present invention relates to a kind of quantitative analysis methods can be used in monodrome gas in multicomponent mud logging gas in situ, pass through foundation
The determination to monodrome gas concentration in multicomponent mud logging gas in situ may be implemented in the decomposition model of dividend external spectrum.
Background technology
Mud logging gas is detected using gas chromatographic technique as representative, has been played in oil-gas exploration and development in recent decades important
Effect, but be periodically detected, auxiliary device is more, be only capable of detection hydrocarbon gas be the widely applied bottleneck of the technology.In recent years
External company and scientific research institution is in the substitute products of exploitation gas chromatograph, wherein mass-spectrometric technique, chromatograph-mass spectrometer coupling technology
It is gradually applied in mud logging gas detection.Chromatography is a kind of isolation technics, mainly utilizes boiling point, polarity and the suction of substance
The difference of attached property realizes the separation of mixture.Sample to be analysed brings chromatographic column by carrier gas (mobile phase), due in sample
Boiling point, polarity or the absorption property of each component are different, each component tends to form distribution between mobile phase and stationary phase
Or adsorption equilibrium.Since carrier gas is flowing, sample component carries out repeated multiple times distribution or absorption during exercise, the result is that
The big component of concentration is distributed in carrier gas and first flows out chromatographic column, and is flowed out after distributing the big component of concentration in stationary phase.Work as component
Detector is immediately entered after outflow chromatographic column, the relevant information (concentration or amount) of sample component is changed into electric signal by detector,
Signal is recorded through amplifying in recorder, and chromatogram has just been obtained.Chromatography can be divided into gas chromatography and liquid chromatography
Two kinds.Gas chromatography is used with gas detection is bored.
The basis of the quantitative analysis method of multicomponent mud logging gas infrared spectrum in situ is langbobier law.Due to lambert
Beer law show that gas not follows strictly this law to the absorption of infrared light in the ideal case.Moreover, various gas
Body has multiple absorption peaks in infrared spectrum wave band, and when containing multiple gases ingredient in sample, the absorption peak of gas may
It can be overlapped so that spectrum becomes sufficiently complex.Therefore seeking gas infrared spectrum data and gaseous species or gas infrared spectrum
When correspondence between data and gas concentration, need to take various rational models to improve analysis precision and accuracy rate.For
Solving the absorption peak of gas may be overlapped so that spectral model solution is difficult to realize, to each component quantifying in mud logging gas
Analysis is difficult to realize, and the present invention is based on genetic algorithms and radial base neural net, devise a kind of new multicomponent well logging in situ
The quantitative analysis method of gas infrared spectrum.
Invention content
The present invention provides a kind of quantitative analysis method of multicomponent mud logging gas infrared spectrum in situ, and this method can be applied
In drilling fluid following drill gas detection technology (also referred to as gas detection logging), landwaste oil-containing situation can be quickly analyzed.
The hardware system of the quantitative analysis method based on multicomponent mud logging gas infrared spectrum in situ includes：
For the infrared spectrometer device of gathered data, the model BRUKER companies of the infrared spectrometer device
Mid-infrared light spectrometer (alpha)；
Mud logging gas hybrid processor one for gas sample manufacture, model prediction correction；
One, the computer for data processing and analysis；
Cabinet one for placing infrared spectrometer, gas mixing processor and embedded control system；
Multicomponent mud logging gas quantitative analysis method in situ designed by the present invention, realization process are：
Step 1：Mud logging gas infrared absorption line is obtained using mud logging gas analyzer, as shown in Figure 1, selection [λ1, λ2]
Spectrum area is pre-processed, the λ1It is the starting point in selection spectrum area, the λ2It is the terminating point in selection spectrum area；
Spectroscopic data pre-processes.4000~800cm-1 of spectrum area (1553 data points) of entire spectrum has higher letter
It makes an uproar and compares, useful spectrum area is less, as shown in Figure 1.It is accurate in order to the model of foundation, it is soft using the OPUS 7.5 of BRUKER companies
Part handles spectroscopic data.The first step shears spectroscopic data, chooses useful spectrum 3250~2750cm-1 of area
(245 data points), as shown in Figure 2.Second step carries out Baseline wander to the data sheared.
Step 2：In order to eliminate the spectrum baseline drift caused by measuring environment, condition variation, using first differential method,
To [the λ described in step 11, λ2] the progress baseline correction of spectrum area, as shown in Fig. 2, and being normalized；
Step 3：By [the λ described in step 11, λ2] spectrum area be divided into N (N ∈ [10,20]) a section, to N number of area
Between encoded, the first generation population of generation is set as x, and primary condition is arranged：It is 30 that Population Size, which is arranged, and maximum breeding is arranged
Algebraically is 100, and setting crossover probability is 0.5, and setting mutation probability is that 0,1 the selection result is as shown in Figure 3；
Step 4：The first generation population x is established into radial base neural net as input variable, utilizes modeling sample
The decomposition model for establishing multicomponent mud logging gas in situ, using the multicomponent mud logging gas decomposition model in situ to pre- test sample
This is predicted, the correlation coefficient r and root-mean-square error RMSPE of predicted value and actual value are solved；
Step 5：The correlation coefficient r and the root-mean-square error RMSPE and optimized individual are established according to formula (1)
The relationship of discriminant function Finesse；
Step 6：Each pure gas in mixed gas is solved according to the multicomponent mud logging gas decomposition model in situ
Concentration, the mixed gas include the gases such as methane, ethane, propane, iso-butane, normal butane, isopentane, isopentane；
In this invention, concrete analysis iso-butane, normal butane, analysis result is as shown in figure 4, finally to solve its a concentration of
d1、d2。
The beneficial effects of the invention are as follows：The multicomponent mud logging gas infrared spectrum in situ introduced through the invention quantifies
Analysis method can realize qualitative and quantitative analysis to the mud logging gas of non-principal component, reach and accurately analyze landwaste oil-containing situation.
Description of the drawings
Fig. 1：Original figure spectrum；
Fig. 2：Pretreated figure；
Fig. 3：Optimized individual schematic diagram；
Fig. 4：Model prediction result figure and residual plot；
Fig. 5：Algorithm flow chart.
Specific implementation mode
Step 1：Experiment material
The alkanes gas and nitrogen provided by Hua Yuan gases Chemical Co., Ltd. of Beijing, wherein paraffin gas are a concentration of
2000ppm, nitrogen gas concn 99.99%.A gas dispenser is designed using the digital mass flowmeter of Azbil companies.It adopts
Light harvesting time spectrum, each sample are taken a breath before entering gas cell with N2, and the influence of a upper sample, the work of spectral preservation instrument are eliminated
Temperature is 46 DEG C, and spectrometer inlet pressure is 0.3Kpa.
Step 2：Laboratory sample obtains
The infrared spectrum of mixed gas, light are acquired using the mid-infrared light spectrometer (alpha) that German BRUKER companies produce
4000~900cm of spectral limit-1, resolution ratio 2.0cm-1, scanning times 16, every group of data acquire 5 times, then take 5 times flat
Mean value is as sample spectra.
The CMQ-V series digit mass flowmenters of Azbil companies of Japan are selected to design a flow dispenser, digital quality
Flowmeter allows through maximum stream flow to be 500ml.Experiment inputs gas using 7 tunnels, and 6 tunnels are paraffin gas, and 1 tunnel is nitrogen.Often
Its flow all is controlled with digital mass flowmeter all the way, it is 3000ml to keep mixed total flow.Change digital mass flow
The flux of meter obtains the sample of 50 groups of known concentrations, and sample is divided into modeling collection and forecast set in 4: 1 ratios.Table 1 is that modeling collects
With the statistical result of forecast set sample concentration, as can be seen from the table, modeling collection sample concentration range is wide, representative.
1 sample concentration statistical result of table
Tab.1 the results of sample concentration
Step 3：Model foundation
RBF networks can approach arbitrary nonlinear function, simple in structure, trained succinct, study fast convergence rate.RBF
It is three-layer forward networks.First layer is input layer, and the number of input node is equal to the dimension n of input vector x, uses spectrum herein
Wave number as input.The second layer is hidden layer, and the number of nodes of hidden layer is determined by training data, and a hidden layer node corresponds to
One training data point.Third layer is output layer, is the linear summation to each node of hidden layer, realizes the sound to input pattern
It answers.
The variable that heredity is screened establishes prediction model as the input of radial base neural net, and algorithm is realized
Process is as shown in Figure 5.
Schematically the present invention and embodiments thereof are described above, this describes no limitation, institute in attached drawing
What is shown is also one of embodiments of the present invention.So if those skilled in the art are enlightened by it, do not departing from
In the case of the invention objective, each component layouts mode of the same item or other forms that take other form, without
Creative designs technical solution similar with the technical solution and embodiment, is within the scope of protection of the invention.
Claims (1)
1. a kind of quantitative analysis method being applied to multicomponent mud logging gas infrared spectrum in situ designed by the present invention, feature
It is：It comprises the following steps：
Step 1：Mud logging gas infrared absorption line is obtained using mud logging gas analyzer, selects [λ1, λ2] spectrum area located in advance
Reason, the λ1It is the starting point in selection spectrum area, the λ2It is the terminating point in selection spectrum area；
Step 2：In order to eliminate the spectrum baseline drift caused by measuring environment, condition variation, using first differential method, to step
[λ described in rapid 11, λ2] spectrum area carries out baseline correction, and is normalized；
Step 3：By [the λ described in step 11, λ2] spectrum area be divided into N (N ∈ [10,20]) a section, to N number of section into
The first generation population of row coding, generation is set as x, and primary condition is arranged：It is 30 that Population Size, which is arranged, and maximum reproductive order of generation is arranged
It is 100, setting crossover probability is 0.5, and setting mutation probability is 0.1；
Step 4：The first generation population x is established into radial base neural net as input variable, is established using modeling sample
The decomposition model of multicomponent mud logging gas in situ, using the multicomponent mud logging gas decomposition model in situ to forecast sample into
Row prediction, solves the correlation coefficient r and root-mean-square error RMSPE of predicted value and actual value；
Step 5：The correlation coefficient r and the root-mean-square error RMSPE are established according to formula (1) with optimized individual to judge
The relationship of function Finesse；
Step 6：Each pure gas concentration in mixed gas is solved according to the multicomponent mud logging gas decomposition model in situ,
The mixed gas includes the gases such as methane, ethane, propane, iso-butane, normal butane, isopentane, isopentane；
The quantitative analysis method for solving each pure gas concentration in mud logging gas finishes.
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Cited By (3)
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| CN109724941A (en) * | 2019-02-27 | 2019-05-07 | 大唐长山热电厂 | A kind of CO based on radial base neural net2High-temperature gas concentration detection method |
| CN110414169A (en) * | 2019-08-05 | 2019-11-05 | 上海神开石油科技有限公司 | A kind of fourier infrared gas detection logging method and device thereof |
| CN116413236A (en) * | 2023-02-27 | 2023-07-11 | 西南石油大学 | Device and method for detecting total hydrocarbon content of drilling return liquid |
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Application publication date: 20180928 |