CN1563980A - Method of quantitatively evaluating gas source rock contribution ratio of hydrid natural gas - Google Patents
Method of quantitatively evaluating gas source rock contribution ratio of hydrid natural gas Download PDFInfo
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Abstract
Based on principle of universality, peaks of chromatogram fingerprint of adsorbing heavy hydrocarbon are selected. Using peak area of near fingerprints calculates ratio parameter of fingerprints of heavy hydrocarbon. Then, based on contributions of different source rocks, artificially assigned proportioning data are introduced into model of analog computation. After training, stencil plate is formed for quantitative analog computing contributions of different source rocks. Finally, ratio parameter of characteristic fingerprints of heavy hydrocarbon chromatogram corresponding to natural gas is introduced into stencil plate of analog computation in order to calculate quantitative contributions from different source rocks to mixed source of natural gas. The method is applicable to 2-4 layers of source rock.
Description
Technical field
The present invention relates to the gas prospecting field, be specifically related to of the ration contribution research of different sources of the gas rock stratum mixed-source natural gas.
Background technology
At present, as a kind of important resource, the exploration of deep natural gas has great potential and good prospect.With China distant basin of pine is example, the distant basin north deep gas prospecting of deep layer pine in decades, step on deep layers acquisition industrial gas such as Lou Ku group, liter dark 1 and Xu Shen 1 Jing Ying city group in fragrant dark 1 of areas such as the prosperous moral, Wang Jiatun of the tame defensive wall rift of Xu, peaceful, Song station, the tame defensive wall of Xu, formed gas fields such as prosperous moral gas reservoir, Wang Jiatun-peaceful, especially obtained 6 * 10 in Xu Shen 1 Jing Ying city group and Shahe son group gas testing
4m
3/ d industrial gas, unobstructed full well have a daily output of 1.18 * 10
6m
3/ d rock gas becomes the maximum focus of China's the Northeast's gas prospecting.General in these deep natural gas geologic medias all from the hydrocarbon source rock of a plurality of layers of position, step on Lou Ku group, battalion's city group, Shahe son group and flint mountain range group, four station slate groups etc. as the tame defensive wall rift deep layer of Xu, it is much that yet rock gas has the ration contribution of mixed-source natural gas from that cover hydrocarbon source rock and different layers position hydrocarbon source rock actually on earth, is the difficult problem that gas prospecting needs to be resolved hurrily always.
The blending ratio of bibliographical information with two types of rock gases of component carbon isotope method research being arranged, referring to Fu Ning. 13-1 gas field, precipice combination gas mixed volume ratio is calculated [J]. Chinese offshore oil and gas (geology), 2000,14 (4): 258～261; With Xiaxin's space, Li Chunyuan, Zhao Lin. rock gas mixes the source is declared in the source effect to isotope influence [J]. petroleum prospecting and exploitation, 1998,25 (3): 89～90.But these researchs all can not solve three types or the mixed source of more rock gases ratio computational problem.
The innovation and creation content
The purpose of this invention is to provide the method for a kind of quantitative evaluation different layers position hydrocarbon source rock to the contribution of rock gas, this method is fit to two-layer to the ration contribution analog computation of four layers of hydrocarbon source rock to mixed-source natural gas.
The method of quantitative evaluation mixed-source natural gas source rock contribution proportion of the present invention may further comprise the steps:
1) get gas in the source rock that produces rock gas, gas chromatography determination wherein adsorbs heavy hydrocarbon, chooses the chromatographic fingerprint peak; Simultaneously with absorption heavy hydrocarbon fingerprint ratio parameter in the calculated by peak area source rock at two close chromatographic fingerprint peaks choosing;
2) with the absorption heavy hydrocarbon fingerprint ratio parameter data of step 1) gas chromatography determination,,, get the characteristic fingerprint ratio parameter of its mean value as this layer hydrocarbon source rock according to principle with hydrocarbon source rock characteristic fingerprint similarity in one deck by each hydrocarbon source rock layering separate processes;
3) with step 2) the different hydrocarbon source rock layerings absorption heavy hydrocarbon characteristic fingerprint ratio parameter values that obtain, set the proportioning data substitution computation model function of different hydrocarbon source rock contribution proportions, utilize non-linear artificial neural network intelligence learning algorithm training to form different hydrocarbon source rock contribution quantitative simulations and calculate masterplate;
Described computation model function is:
Yn=k1*x1n+k2*x2n+ ... + km*xmn, wherein,
X is the characteristic fingerprint ratio parameter of absorption heavy hydrocarbon in the hydrocarbon source rock layering;
N is the right number of choosing in chromatographic fingerprint peak;
M is the number of plies of hydrocarbon source rock layering, m＞2;
K is the ration contribution ratio of hydrocarbon source rock layering to rock gas;
Y is a characteristic fingerprint ratio parameter in the mixed-source natural gas;
4) get corresponding mixed-source natural gas and carry out the heavy hydrocarbon gas chromatographic analysis, calculated by peak area with the chromatographic fingerprint peak of choosing with the same method of step 1) obtains individual features fingerprint ratio parameter, this characteristic fingerprint ratio parameter is imported described analog computation masterplate, calculate the ration contribution ratio of different hydrocarbon source rocks mixed-source natural gas.
In the method for the different source beds of above-mentioned quantitative evaluation mixed-source natural gas contribution proportion, non-linear artificial neural network intelligence learning algorithm training described in the step 3) forms analog computation masterplate process, be to import the layering hydrocarbon source rock characteristic fingerprint ratio parameter that all are chosen one by one, through a series of Sigmoid function and matrix operation, weighting, on average, output to second hidden layer, a series of computings through same principle, output to first hidden layer, pass through a series of computings of same principle again, output layer promptly is the percentage contribution rate of each layering hydrocarbon source rock of mixed-source natural gas, each layer number percent contrast with artificial proportioning, error is successively feedbacked by original path, in the process of feedback,, adjust the weight vector matrix of each node successively by the size of error.Repeat top step once more according to the weight vector matrix after adjusting, so move in circles, the error between output and actual proportioning satisfies desired precision; The analog computation process has designed each layering hydrocarbon source rock contribution rate during masterplate and has thought relative error and precision control setting between the proportioning in training, each layering hydrocarbon source rock contribution rate is divided into 7 range of control:＜1% do not control, 1～5%, 5～10%, 10～25%, 25～50%, 50～75%, 75～100%, when the training masterplate, import the artificial desired relative error of each range of control respectively till; Error between described output and the actual proportioning finally satisfies absolute error less than 5%, and relative deviation is less than 10%; At this moment, store the weight matrix and the correlation parameter of each unit of each layer, just set up the calculating masterplate of mixed-source natural gas layering hydrocarbon source rock ration contribution.
In the method for the different source beds of above-mentioned quantitative evaluation mixed-source natural gas contribution proportion, the step of choosing at the described chromatographic fingerprint of step 1) peak is:
(1) chooses the chromatographic fingerprint peak that all exists in each layer hydrocarbon source rock and the rock gas according to principle of universality;
(2) choose the chromatographic fingerprint peak that each layer hydrocarbon source rock all there are differences according to the otherness principle.
In the method for the different source beds of above-mentioned quantitative evaluation mixed-source natural gas contribution proportion, the described calculated by peak area heavy hydrocarbon fingerprint ratio parameter that utilizes is followed following rule:
X=a/b is in the formula
X is the ratio of close fingerprint peaks area;
A, b are respectively the peak area of close fingerprint peaks.
In the method for the different source beds of above-mentioned quantitative evaluation mixed-source natural gas contribution proportion, the described step of producing gas from hydrocarbon source rock is: get source rock sample and put into the impacting type preparation facilities, after sealing vacuumizes, pulverize sample by the vibration bump, adsorbed gas in the source rock is discharged, adopt drainage to take out gas.
The method of the different source beds of quantitative evaluation mixed-source natural gas of the present invention contribution proportion, when described source rock is made up of four layers of hydrocarbon source rock layering, the described quantitative simulation of step 3) calculates masterplate, calculates according to mixed gas heavy hydrocarbon and the chromatogram characteristic fingerprint ratio parameter value of each hydrocarbon source rock absorption heavy hydrocarbon and the following relationship between its contribution rate:
y1＝k1*x11+k2*x21+k3*x31+k4*x41
y2＝k2*x1?2+k2*x22+k3*x32+k4*x42
……
Yn=k1*x1n+k2*x2n+k3*x3n+k4*x4n, in the formula,
X11, x12......x1n are respectively the characteristic fingerprint ratio parameter value to the absorption heavy hydrocarbon of certain peak in the hydrocarbon source rock 1;
X21, x22......x2n are respectively the characteristic fingerprint ratio parameter value to the absorption heavy hydrocarbon of certain peak in the hydrocarbon source rock 2;
X31, x32......x3n are respectively the characteristic fingerprint ratio parameter value to the absorption heavy hydrocarbon of certain peak in the hydrocarbon source rock 3;
X41, x42......x4n are respectively the characteristic fingerprint ratio parameter value to the absorption heavy hydrocarbon of certain peak in the hydrocarbon source rock 4;
K1, k2......k4 are respectively the ration contribution rate of hydrocarbon source rock 1 to 4 pairs of rock gases of hydrocarbon source rock;
Y1, y2......yn are respectively in the mixed-source natural gas certain peak to the ratio parameter value of characteristic fingerprint compound;
N is the right number of choosing in chromatographic fingerprint peak.
The present invention is calculated as example with the different hydrocarbon source rock contribution of prosperous moral gas reservoir mixed-source natural gas quantitative simulation, new method and the approach of quantitative evaluation hydrocarbon source rock to the contribution of rock gas is provided, this method is fit to two-layer to the ration contribution analog computation of four layers of hydrocarbon source rock to mixed-source natural gas, started the frontier of hydrocarbon source rock and rock gas research, had broad application prospects.
Description of drawings
The nonlinear artificial neural network intelligence learning algorithm synoptic diagram that Fig. 1 adopts for the present invention;
Fig. 2 is four layers of hydrocarbon source rock ration contribution of multi-source mixed gas theoretical model;
Fig. 3 is the linear lab diagram of sample size and peak area enrichment heavy hydrocarbon among the embodiment;
Fig. 4 is rock gas heavy hydrocarbon C1～C7 gas chromatogram among the embodiment;
Fig. 5 is hydrocarbon source rock absorption heavy hydrocarbon C1～C7 gas chromatogram among the embodiment.
Fig. 6-A is asymmetric Sigmoid function synoptic diagram among the present invention;
Fig. 6-B is symmetrical Sigmoid function synoptic diagram.
Embodiment
Below from several respects in detail the present invention is described in detail.
One, the theoretical analysis of the different hydrocarbon source rock contribution of multi-source mixed gas chromatogram heavy hydrocarbon fingerprint technique
1, theoretical foundation
Chromatogram heavy hydrocarbon fingerprint ratio parameter and component carbon isotope index are the main method of rock gas and hydrocarbon source rock comparative study, i.e. the hydrocarbon source rock absorption rock gas heavy hydrocarbon chromatogram characteristic fingerprint ratio parameter that heavy hydrocarbon and its generated has similarity;
Because the difference of different layers position hydrocarbon source rock character and the influence of geologic media, the difference of the chromatographic fingerprint that total existence can measure in the different layers position hydrocarbon source rock absorption heavy hydrocarbon, and mixed-source natural gas and different layers position hydrocarbon source rock to adsorb the otherness of heavy hydrocarbon chromatographic fingerprint characteristic parameter be the result that mixes of homology rock gas not.This is to utilize chromatogram heavy hydrocarbon characteristic fingerprint ratio parameter to study the theoretical foundation of different hydrocarbon source rocks to the contribution of multi-source mixed gas.
Multi-source mixed gas multilayer hydrocarbon source rock ration contribution theoretical model is seen Fig. 2, is example with four layers of hydrocarbon source rock, and following relationship is arranged between the chromatogram characteristic fingerprint ratio parameter value of mixed gas heavy hydrocarbon and each hydrocarbon source rock absorption heavy hydrocarbon and its contribution rate:
y1＝k1*x11+k2*x21+k3*x31+k4*x41
y2＝k2*x12+k2*x22+k3*x32+k4*x42
……
Yn=k1*x1n+k2*x2n+k3*x3n+k4*x4n, in the formula,
X11, x12......x1n are respectively the characteristic fingerprint ratio parameter value to the absorption heavy hydrocarbon of certain peak in the hydrocarbon source rock 1;
X21, x22......x2n are respectively the characteristic fingerprint ratio parameter value to the absorption heavy hydrocarbon of certain peak in the hydrocarbon source rock 2;
X31, x32......x3n are respectively the characteristic fingerprint ratio parameter value to the absorption heavy hydrocarbon of certain peak in the hydrocarbon source rock 3;
X41, x42......x4n are respectively the characteristic fingerprint ratio parameter value to the absorption heavy hydrocarbon of certain peak in the hydrocarbon source rock 4;
K1, k2......k4 are respectively the ration contribution rate of hydrocarbon source rock 1 to 4 pairs of rock gases of hydrocarbon source rock;
Y1, y2......yn are respectively in the mixed-source natural gas certain peak to the ratio parameter value of characteristic fingerprint compound.
Among Fig. 2, A, B......Z are respectively in hydrocarbon source rock absorption heavy hydrocarbon and the mixed-source natural gas heavy hydrocarbon corresponding certain peak to the characteristic fingerprint compound.
For multilayer hydrocarbon source rock ration contribution, described computation model function expands to:
Yn=k1*x1n+k2*x2n+ ... + km*xmn, wherein,
X is the characteristic fingerprint ratio parameter of absorption heavy hydrocarbon in the hydrocarbon source rock layering;
N is the right number of choosing in chromatographic fingerprint peak;
M is the number of plies of hydrocarbon source rock layering, m＞2;
K is the ration contribution ratio of hydrocarbon source rock layering to rock gas;
Y is a characteristic fingerprint ratio parameter in the mixed-source natural gas.
2, the pacing items of the different hydrocarbon source rock ration contributions of mixed gas
(1) repeatability: the relative deviation of hydrocarbon source rock absorption heavy hydrocarbon and rock gas heavy hydrocarbon chromatogram characteristic fingerprint ratio parameter replication should be not more than 5%.
(2) enrichment linearity: hydrocarbon source rock absorption heavy hydrocarbon and the enrichment of rock gas heavy hydrocarbon are analyzed between sample size and the peak area linear.
(3) otherness: there are detectable difference in different hydrocarbon source rock absorption heavy hydrocarbons and rock gas heavy hydrocarbon fingerprint ratio parameter.
(4) similarity: different wells or well depth hydrocarbon source rock absorption heavy hydrocarbon characteristic fingerprint ratio parameter is close or in certain variation range in the same hydrocarbon source rock position.
(5) proportioning: mixing match absorption heavy hydrocarbon characteristic fingerprint ratio parameter is stable, by hydrocarbon source rock characteristic fingerprint ratio parameter and rock gas contribution rate decision separately.
3, the analog computation of chromatogram characteristic fingerprint ratio parameter and ration contribution
Mix at multilayer crude oil and to adopt in the process, document (Zou Yuzheng is arranged, Cai Yuanming, Ma Ting, Deng. how to eliminate the defective [J] that is applied to and adopts the gas chromatography fingerprint technique existence of well crude production rate contribution calculation. oil experiment geology, 2001,23 (2): 213～220.) point out, chromatogram characteristic fingerprint peak generally adopts concentration parameter, because multilayer crude oil mixes and to adopt peak height (peak area) ratio parameter and generally no longer satisfy linear relationship, so employing peak height (peak area) need be set up nonlinear mathematics analog computation model than parameter.
Also there is same problem in quantitative Analysis for the multi-source mixed gas, but because source rock sample has broken away from underground primal environment, unavoidable entrained air during preparation, the gas concentration of the hydrocarbon source rock absorption of preparation, different with the concentration of the rock gas that hydrocarbon source rock generated under the primal environment of stratum, so can not adopt concentration parameter, the hydrocarbon source rock absorption rock gas heavy hydrocarbon chromatogram characteristic fingerprint ratio parameter that heavy hydrocarbon and its generated then has similarity, therefore, the analog computation of the different hydrocarbon source rock ration contributions of mixed gas needs to select peak height (peak area) ratio parameter and nonlinear mathematics analog computation.
The present invention adopts nonlinear artificial neural network intelligence learning algorithm to set up mathematical model, and this Model Calculation process is seen Fig. 1.This computation process is made up of forward-propagating and backpropagation, and in the forward-propagating process, input information is successively handled through hidden layer from input layer, and propagates to output layer, and the neuronic state of each layer only influences the neuronic state of one deck down.If the output in that output layer can not obtain expecting then changes backpropagation over to, error signal is successively returned along original connecting path, revise the neuronic weights of each layer by error signal, make error reduce, reach accuracy requirement until error.
The local error function formula is as follows:
Among the present invention, training forms analog computation masterplate process, be to import the layering hydrocarbon source rock characteristic fingerprint ratio parameter that all are chosen one by one, through a series of Sigmoid function and matrix operation, weighting, on average, output to second hidden layer, a series of computings through same principle, output to first hidden layer, pass through a series of computings of same principle again, output layer promptly is each layer number percent contrast of the percentage contribution rate and the artificial proportioning of each layering hydrocarbon source rock of mixed-source natural gas, error is successively feedbacked by original path, in the process of feedback,, adjust the weight vector matrix of each node successively by the size of error.Repeat top step once more according to the weight vector matrix after adjusting, so move in circles, the error between output and actual proportioning satisfies desired precision; The analog computation process has designed each layering hydrocarbon source rock contribution rate during masterplate and has thought relative error and precision control setting between the proportioning in training, each layering hydrocarbon source rock contribution rate is divided into 7 range of control:＜1% do not control, 1～5%, 5～10%, 10～25%, 25～50%, 50～75%, 75～100%, when the training masterplate, import the artificial desired relative error of each range of control respectively till; Error between described output and the actual proportioning finally satisfies absolute error less than 5%, and relative deviation is less than 10%; At this moment, store the weight matrix and the correlation parameter of each unit of each layer, just set up the calculating masterplate of mixed-source natural gas layering hydrocarbon source rock ration contribution.
The Sigmoid function is neuronic nonlinear interaction function, and asymmetric Sigmoid function is
The functional value scope is (0,1), referring to Fig. 6-A; Symmetry Sigmoid function
Functional value is (1,1), referring to Fig. 6-B.Because the output percentage range of each layering hydrocarbon source rock of mixed-source natural gas is in [0,100%], so the present invention adopts asymmetric Sigmoid function.
When using this calculating masterplate, only need the individual features fingerprint ratio parameter that mixed-source natural gas chromatogram heavy hydrocarbon is analyzed be imported, can calculate the ration contribution of each layering hydrocarbon source rock.
Two, the embodiment of the inventive method
Below be that example illustrates implementation process of the present invention with the distant basin of the pine prosperous moral gas reservoir of the tame defensive wall of Xu.
1, prosperous moral gas reservoir geologic background and deep source rocks distribute
The Song Fang that prosperous moral gas reservoir is positioned at rift Anda-Zhaozhou anticlinal zone middle part collects textural, the tame defensive wall rift of Xu is one of rifted-basin that forms Jurassic period, be held between ancient central uplift belt and the northeast mole track, the stratum is grown more complete in the rift, thickness is bigger, has deposited basement rock, Jurassic systerm, Cretaceous System, the tertiary system and Quaternary system stratum.Deep source rocks comprises the spring head group of Cretaceous System and steps on the Lou Ku group, Jurassic battalion city group, Shahe son group, flint mountain range group, hydrocarbon source rocks such as basement rock.Step on Lou Ku group and be the basin by the transitional sediment of rift to the down warping region growth course, based on sand shale folder conglomerate, mud stone is based on green and redness, and dark mud rock is less; Battalion's city group has ash purple, purplish grey spherulitic ryolite, tuff, devitrification to contain gravel flow liner matter welded tuff, grayish green, gray purple eruptive tuff folder mud stone; That Shahe group has is dark-grey, the grey black argillite presss from both sides acid eruptive tuff, contain gravel eruptive tuff, coal seam etc.; Flint mountain range group has grey tufaceous rubblerock, folder black mud stone, aleuritic texture mud stone etc.; Basement rock mainly contains phyllite, slate, celadon grouan, grouan, crystal tuff etc.
2, experimental technique
Sample collecting: gather the higher source rock sample of the tame defensive wall rift deep layer abundance of organic matter of Xu: step on 3 of Lou Ku groups, 7 of battalion's city groups, 6 of Shahe son groups, 1 of flint mountain range group, 4 of four station slate groups.Gather 6 in the mixed gas sample of 6 mouthfuls of wells of prosperous moral gas reservoir such as virtue is dark 1, dark 2 wells of virtue.
Sample analysis: will do the fingerprint analysis of adsorbed hydrocarbons complexion spectrum heavy hydrocarbon after the source rock sample preparation; Under similarity condition, do the analysis of rock gas heavy hydrocarbon chromatographic fingerprint.
Absorption hydrocarbon gas preparation: get a certain amount of source rock sample and put into the impacting type preparation facilities, after sealing vacuumizes, pulverize sample, adsorbed gas in the hydrocarbon source rock is discharged, adopt drainage to take out gas, carry out the fingerprint analysis of chromatogram heavy hydrocarbon by the vibration bump.
The fingerprint analysis of chromatogram heavy hydrocarbon: under freezing conditions (temperature-75 ℃～-65 ℃), the gas sample is injected enrichment pipe, make that heavy hydrocarbon obtains enrichment in the sample, heating desorption again is by the analysis of six-way valve incision gas chromatograph.Heavy hydrocarbon fingerprint analytical conditions for gas chromatography: Japanese GC-14A gas chromatograph and data processor, 50m elastic quartz capillary chromatograph, flame ionization ditector, carrier gas is a helium, and combustion gas is a hydrogen, and combustion-supporting gas is air, 35 ℃ of post initial temperatures, constant temperature 5min is raised to 180 ℃ with 2 ℃/min, and constant temperature to component has gone out.
3, chromatogram heavy hydrocarbon characteristic fingerprint ratio parameter is selected and the ration contribution analog computation
Choose absorption heavy hydrocarbon chromatographic fingerprint peak according to principle of universality, utilize the calculated by peak area heavy hydrocarbon fingerprint ratio parameter (x=a/b, x are the ratio of close fingerprint peaks area, and a, b are respectively the peak area of close fingerprint) of close fingerprint; With the different hydrocarbon source rock absorption heavy hydrocarbon fingerprint parameters of each layer position, determine different hydrocarbon source rock absorption heavy hydrocarbon characteristic fingerprint ratio parameters again according to similarity and otherness principle; According to the artificial setting proportioning data of different hydrocarbon source rock contributions, it is imported the analog computation model again, the training back forms different hydrocarbon source rock contribution quantitative simulations and calculates masterplate; At last corresponding rock gas heavy hydrocarbon chromatogram characteristic fingerprint ratio parameter is imported the analog computation masterplate, calculate the ration contribution of different hydrocarbon source rocks mixed-source natural gas.
4, experimental result and discussion
4.1 rock gas trace heavy hydrocarbon enrichment repeatability and linear experiment
(1) repeatability
To rise 58 well 1696.4m～1953m and do micro-heavy hydrocarbon enrichment parallel laboratory test respectively with the dark 6 wells 3210.4m of virtue～3409.8m rock gas, trace heavy hydrocarbon chromatographic fingerprint parameter replication the results are shown in Table 1, as seen, maximum relative deviation is 4.70%, minimum relative deviation is 0.47%, relative deviation is not more than 5%, the sample analysis good reproducibility.
Table 1 rock gas trace heavy hydrocarbon chromatographic fingerprint parameter replication result
Pound sign number of times chromatogram feature hydrocarbon fingerprint parameter
2#/3# 4#/5# 5#/6# 6#/7# 7#/8# 13#/10# 4#/6# 5#/7# 5#/8# 6#/8#
1 0.72 2.74 0.47 1.07 0.39 2.10 1.29 0.50 0.20 0.42
Rise 58 2 0.75 2.78 0.50 1.04 0.42 1.96 1.36 0.55 0.21 0.43
Relative deviation % 1.95 0.83 3.05 1.05 2.6 3.52 2.73 4.51 3.00 1.54
1 3.72 2.12 1.07 1.07 2.56 5.78 2.27 1.14 2.93 2.74
Virtue dark 62 3.51 2.00 1.06 1.05 2.33 5.50 2.09 1.05 2.69 2.51
Relative deviation % 2.90 2.91 0.47 0.94 4.7 2.48 4.13 4.11 4.27 4.38
The 2#-isopentane, the 3#-n-pentane, 4#-2, the 2-dimethylbutane, the 5#-cyclopentane, the 6#-2-methylpentane,
Remarks 7#-3-methylpentane, 8#-normal hexane, 10#-2,3-dimethyl pentane, 13#-methyl cyclopentane
(2) linear experiment
Do the linearity experiment of different sample sizes and peak area enrichment heavy hydrocarbon with rising 58 wells 1696.4m～1953.0m rock gas, the result is referring to Fig. 3, as seen, the rock gas sample size is in 50ml～500ml scope, n-pentane has good linear relationship between positive nonane trace heavy hydrocarbon peak area and sample size, related coefficient n-pentane, normal hexane, normal heptane, normal octane, positive nonane are respectively 0.9956,0.9934,0.9938,0.9980,0.9971.
4.2 the mixed source feature of prosperous moral gas reservoir rock gas
Rock gas is in being gathered into the migration process of Tibetan, and the various rock gases that hydrocarbon source rock generates are easy to mix.Research thinks that the reversing of rock gas component carbon isotope is one of the feature in the mixed source of rock gas; Heavy hydrocarbon indexs such as rock gas methylcyclohexane index also are to differentiate the good index of mixed-source natural gas, utilize ethane carbon isotope and methylcyclohexane index to unite the differentiation masterplate, can effectively differentiate mixed-source natural gas.
Prosperous moral gas reservoir rock gas component carbon isotope and heavy hydrocarbon chromatographic fingerprint index analysis the results are shown in Table 2 and Fig. 4.
The prosperous moral gas reservoir of table 2 rock gas geochemical index is analyzed data
Pound sign layer position Methane Carbon Isotope ethane carbon isotope methylcyclohexane isopentane/
‰ ‰ index % n-pentanes
Dark 1 k1d-22.25-23.07 4.51 0.47 of virtue
Dark 2 k1d-22.51 of virtue/4.84 0.51
Dark 4 k1d-30.75 of virtue/72.29 2.75
Dark 5 k1d-26.88-27.64 90.13 2.99 of virtue
Dark 6 k1d of virtue～k1yc-27.78-30.32 89.56 3.72
Dark 8 k1yc of virtue～k1sh-27.53-30.15 85.97 2.95
The result shows, virtue is dark 1, virtue is dark 5, virtue is dark 6, the dark 8 rock gas methane of virtue, ethane carbon isotope have " reversing " feature; It is bigger that the different well rock gas of prosperous moral gas reservoir heavy hydrocarbon chromatographic fingerprint methylcyclohexane exponential sum isopentane/n-pentane index variation range is respectively 4.51%～90.13%, 0.47～3.72 difference, the hydro carbons matrix that the prosperous moral gas reservoir rock gas Cheng Sheng of institute is described has difference, utilize ethane carbon isotope and methylcyclohexane index associating masterplate to differentiate, dark 1 well of virtue is stepped on Lou Ku group rock gas and is dropped on and mix III district, dark 5 wells of virtue and step on Lou Ku group rock gas and drop on zone of transition, virtue dark 6 and the dark 8 well rock gases of virtue and drop on mixing I district, as seen, prosperous moral gas reservoir rock gas has mixed source and migration characteristics.
From 21 blocks of source rock sample adsorbed hydrocarbons methane, the ethane component carbon isotope of analyzing, there are 3 samples reversing to occur, it is respectively the dark 8 well 4146.43m Shahe of virtue group-26.14 ‰ ,-27.78 ‰, start dark 3 well 2757.55m and step on Lou Ku group-18.00 ‰ ,-22.83 ‰, start dark 6 well 3964.28m Shahe son group-24.78 ‰ ,-28.23 ‰, other 18 samples all do not have the reversing phenomenon, and the basement rock source rock sample all is positive sequence characteristics.Therefore, the reversing phenomenon of hydrocarbon source rock adsorbed hydrocarbons methane, the prosperous moral gas reservoir of ethane component carbon isotope analysis presentation of results rock gas is mainly by due to the source of mixing.
4.3 the feature of the different hydrocarbon source rock absorption of deep layer heavy hydrocarbon chromatogram characteristic fingerprint ratio parameter
The analysis of the tame defensive wall rift deep source rocks absorption of Xu heavy hydrocarbon can detect 110 chromatographic fingerprint peaks (rising dark 6 well 3214.13m Shahe son group, referring to Fig. 5) at most, and the quantity and the component of different wells, the detected heavy hydrocarbon fingerprint of different layers position hydrocarbon source rock have difference.According to ubiquity (fingerprint compound all exists in each hydrocarbon source rock and rock gas), the principle selected characteristic fingerprint peaks of otherness (all there is difference in fingerprint compound in each hydrocarbon source rock), the peak area at close characteristic fingerprint peak is divided by, obtain different hydrocarbon source rock absorption heavy hydrocarbon characteristic fingerprint ratio parameter values, referring to table 3, selected 10 the absorption heavy hydrocarbon characteristic fingerprint ratio parameters of table 3, the numerical value that has in one deck position is approaching, the variation that has is bigger, but certain variation range is arranged all, if adopt one or several characteristic fingerprint ratio parameter, then be difficult to distinguish four hydrocarbon source rocks, adopt a plurality of characteristic fingerprint ratio parameters then can make a distinction.Simultaneously, organize most of characteristic fingerprint ratio parameter value of Jurassic Shahe son group and flint mountain range group hydrocarbon source rock, between layer position, portion is arranged from stepping on Lou Ku
The different hydrocarbon source rock absorption of table 3 heavy hydrocarbon characteristic fingerprint ratio parameter analysis result
Feature is stepped on Lou Ku group battalion group Shahe, city+flint mountain range four station slate groups
Group
Parameter k1d k1yc K1sh+k1hs p3s
2#/3# 1.45～1.92(1.76) 2.87～3.63(3.13) 1.53～3.55(2.17) 039～0.86(0.52)
4#/5# 0.78～1.89(1.08) 0.83～1.94(1.05) 0.36～0.77(0.63) 1.14～2.01(1.38)
5#/6# 1.07～1.76(1.27) 1.28～2.32(1.84) 1.47～1.95(1.57) 0.44～0.81(0.73)
6#/7# 1.32～1.55(1.33) 1.49～1.79(1.59) 1.28～1.70(1.44) 1.43～1.88(1.45)
7#/8# 0.93～1.25(0.96) 0.63～1.45(0.92) 0.65～0.95(0.69) 0.29～0.40(0.32)
13#/10# 4.21～8.38(6.80) 1.73～4.42(2.92) 2.12～4.53(3.23) 1.39～1.65(1.55)
4#/6# 0.56～1.87(1.17) 1.05～2.87(1.87) 0.63～0.94(0.76) 0.88～0.93(0.91)
5#/7# 1.30～1.99(1.65) 1.93～4.82(3.11) 1.89～3.53(2.47) 0.75～1.34(1.08)
5#/8# 1.21～2.01(1.62) 2.83～4.15(3.19) 1.30～2.16(1.61) 0.22～0.47(0.33)
6#/8# 1.10～1.42 (1.25) 0.84～2.60 (1.64) 0.88～1.68 (1.19) 0.39～0.51 (1.19) fractional values are overlapping, and variation is continuous, gradual change; And most characteristic parameter indexs of four station slate groups of basement rock with overlying strata be not gradual change and continuity variation characteristic, may be because due to the hydrocarbon source rock character and geologic media of basement rock.And flint mountain range group (sample) and the sub-group analysis index in Shahe are approaching, with the hydrocarbon source rock of two groups as one deck, be the characteristic fingerprint ratio parameter value of this layer position hydrocarbon source rock according to get its mean value (data in table 3 bracket) with hydrocarbon source rock similarity principle in one deck position, be different hydrocarbon source rocks absorption heavy hydrocarbon characteristic fingerprint ratio parameter layering achievement datas, the deep layer of the tame defensive wall rift of Xu (stepping on the Lou Ku group with sub-surface) be divided into step on Lou Ku group, battalion's city group, son group+flint mountain range, Shahe group, four hydrocarbon source rocks of four station slate groups and carry out ration contribution calculating.
4.4 different hydrocarbon source rocks are to the ration contribution of different well mixed-source natural gas
Utilize different hydrocarbon source rocks absorption heavy hydrocarbon characteristic fingerprint ratio parameter layering achievement datas and the artificial different mixing match of setting to adsorb heavy hydrocarbon characteristic fingerprint ratio parameter data (calculated with mathematical model of representing with formula one), set up different hydrocarbon source rock contribution analog computation masterplates after utilizing non-linear artificial neural network intelligence learning algorithm training, masterplate data regression Calculation be the results are shown in Table 4, as seen, the maximum absolute deviation of regression Calculation result is 1.85%, maximum relative deviation is 4.66%.
Table 4 masterplate regression Calculation result
Proportioning sequence number hydrocarbon source rock proportioning is masterplate regression result absolute deviation relative deviation as a result
％ ％ ％ ％
1 k1d 10.00 10.88 0.88 4.21
k1yc 10.00 9.11 0.89 4.66
k1sh+k1hs 10.00 10.09 0.09 0.45
p3s 70.00 69.89 0.11 0.08
2 k1d 10.00 10.56 0.56 2.72
k1yc 10.00 9.18 0.82 4.28
k1sh+k1hs 70.00 69.62 0.38 0.27
p3s 10.00 10.62 0.62 3.01
3 k1d 10.00 9.17 0.83 4.33
k1yc 70.00 69.9 0.10 0.07
k1sh+k1hs 10.00 10.78 0.78 3.75
p3s 10.00 10.14 0.14 0.70
4 k1d 70.00 71.55 1.55 1.10
k1yc 10.00 9.80 0.20 1.01
k1sh+k1hs 10.00 9.38 0.62 3.20
p3s 10.00 9.25 0.75 3.90
5 k1d 20.00 19.24 0.76 1.94
k1yc 20.00 20.95 0.95 2.32
k1sh+k1hs 20.00 20.44 0.44 1.09
p3s 40.00 39.35 0.65 0.82
6 k1d 20.00 19.14 0.86 2.20
k1yc 20.00 20.53 0.53 1.31
k1sh+k1hs 40.00 41.32 1.32 1.62
p3s 20.00 19.00 1.00 2.56
7 k1d 20.00 18.54 1.46 3.79
k1yc 40.00 38.43 1.57 2.00
k1sh+k1hs 20.00 21.11 1.1 2.70
p3s 20.00 21.90 1.90 4.53
8 k1d 40.00 38.56 1.44 1.83
k1yc 20.00 21.39 1.39 3.36
k1sh+k1hs 20.00 20.87 0.87 2.13
p3s 20.00 19.16 0.84 2.15
9 k1d 30.00 29.35 0.65 1.10
k1yc 30.00 28.87 1.13 1.92
k1sh+k1hs 30.00 31.00 1.00 1.64
p3s 10.00 10.76 0.76 3.66
10 k1d 30.00 29.85 0.15 0.25
k1yc 30.00 29.52 0.48 0.81
k1sh+k1hs 10.00 10.77 0.77 3.71
p3s 30.00 29.84 0.16 0.27
11 k1d 30.00 31.57 1.57 2.55
k1yc 10.00 9.55 0.45 2.30
k1sh+k1hs 30.00 28.15 1.85 3.18
p3s 30.00 30.71 0.71 1.17
12 k1d 10.00 10.93 0.93 4.44
k1yc 30.00 28.20 1.80 3.09
k1sh+k1hs 30.00 30.71 0.71 1.17
p3s 30.00 30.14 0.14 0.23
Get the rock gas in the different wells of prosperous moral gas reservoir (totally 6), measure heavy hydrocarbon wherein and choose calculated by peak area characteristic fingerprint peak parameter value with the corresponding characteristic fingerprint of hydrocarbon source rock absorption heavy hydrocarbon peak, result of calculation sees Table 5.
The prosperous moral gas reservoir of table 5 rock gas heavy hydrocarbon characteristic fingerprint ratio parameter
Dark 6 virtues dark 8 of dark 5 virtues of dark 4 virtues of dark 2 virtues of dark 1 virtue of feature virtue
Parameter k1d k1d k1d k1d k1d～k1yc k1yc～k1sh
2#/3# 0.47 0.51 2.75 2.99 3.72 2.95
4#/5# 0.52 0.69 1.95 1.91 2.12 1.92
5#/6# 0.24 0.14 0.98 1.02 1.07 1.05
6#/7# 0.92 1.66 0.93 0.85 1.07 0.99
7#/8# 0.10 0.15 1.14 1.73 2.56 2.32
13#/10# 0.72 1.06 5.47 4.03 5.78 1.94
4#/6# 0.46 0.10 1.91 1.95 2.27 2.01
5#/7# 0.44 0.23 0.91 0.87 1.14 1.04
5#/8# 0.07 0.03 1.04 1.50 2.93 2.40
6#/8# 0.22 0.24 1.06 1.47 2.74 2.29
In the data importing analog computation masterplate with table 5, result of calculation sees Table 6.
The different hydrocarbon source rocks of table 6 are to the different well mixed-source natural gas of prosperous moral gas reservoir contribution calculation result
Pound sign layer position hydrocarbon source rock ration contribution %
Step on son group+flint mountain range, Lou Ku group battalion group Shahe, city group four station slate groups
Dark 1 k1d 10.97 1.22 2.54 85.25 of virtue
Dark 2 k1d 10.68 1.65 3.64 84.01 of virtue
Dark 4 k1d 42.08 11.34 20.56 25.99 of virtue
Dark 5 k1d 15.32 9.32 32.85 42.48 of virtue
Dark 6 k1d of virtue～k1yc 41.15 18.79 19.81 20.23
Dark 8 k1yc of virtue～k1sh 0.00 4.71 82.16 13.11
Learn from table 6, virtue is dark 1, dark 2 wells of virtue are stepped on Lou Ku group rock gas mainly from four station slate group hydrocarbon source rocks of basement rock, account for 85.25%, 84.01% of mixed-source natural gas respectively, account for 10.97%, 10.68% respectively from what step on Lou Ku group, account for 2.54%, 3.64% respectively from Shahe son group and flint mountain range group, that comes self-operation city group accounts for 1.22%, 1.65% respectively; Dark 4 wells of virtue are stepped on Lou Ku group rock gas mainly from stepping on Lou Ku group hydrocarbon source rock, account for 42.08% of this well mixed-source natural gas, account for 11.34%, 20.56%, 25.09% respectively from Jurassic systerm battalion city group, Shahe son group and flint mountain range group, basement rock four station slate groups; Dark 5 wells of virtue are stepped on Lou Ku group rock gas mainly from four station slate group hydrocarbon source rocks, account for 42.48% of this well mixed-source natural gas, from Jurassic systerm battalion city group, Shahe son group and flint mountain range group, step on the Lou Ku group account for 9.32%, 32.85%, 15.32% respectively; The Lou Ku group stepped on by dark 6 wells of virtue and battalion's city group rock gas is mainly organized hydrocarbon source rock from stepping on Lou Ku, account for 41.15% of this well mixed-source natural gas, account for 18.79%, 19.81%, 20.23% respectively from Jurassic systerm battalion city group, Shahe son group and flint mountain range group, basement rock four station slate groups.Virtue dark 8 Jing Ying city groups and Shahe son group rock gas mainly comes Shahe son group and flint mountain range group hydrocarbon source rock, accounts for 82.16% of this well mixed-source natural gas, accounts for 4.71%, 13.11% respectively from what Jurassic systerm was sought city group, basement rock four station slate groups.
Existing research thinks that prosperous moral gas reservoir may and be stepped on Lou Ku group hydrocarbon source rock two cover gas source rock air feed by the tame defensive wall rift Jurassic systerm of Xu, and based on Jurassic systerm rift hydrocarbon source rock anger, by unconformity surface or tomography migration, stepping on Lou Ku group hydrocarbon source rock has certain angry ability; Also have the expert to utilize the research of component carbon isotope method to think, prosperous moral gas reservoir rock gas is mainly from the gas source rock of basement rock.The analysis result of the above embodiment of the present invention, should demonstrate,prove these achievements in research, simultaneously, revise and decide scale understand prosperous moral gas reservoir rock gas by Jurassic systerm, basement rock, step on Lou Ku three cover hydrocarbon source rock air feed, and specifically obtain separately contribution amount, be tremendous replenishing and innovation to existing achievement in research.
In sum, the present invention has following characteristics:
(1) basic theories, condition, the analog computation model of the different hydrocarbon source rock ration contribution of multi-source mixed gas chromatogram heavy hydrocarbon fingerprint technique have been established, utilize hydrocarbon source rock absorption heavy hydrocarbon and rock gas heavy hydrocarbon chromatographic fingerprint characteristic parameter and analog computation software in the world first, finished of the analog computation of four different hydrocarbon source rocks of the northern tame defensive wall rift of Xu in loose distant basin, filled up world's blank of this research field prosperous moral gas reservoir mixed-source natural gas ration contribution.
(2) the different hydrocarbon source rock aerogenesis contribution of the tame defensive wall rift deep layer of embodiment Xu quantitative simulation result of calculation shows, prosperous moral gas reservoir mixed-source natural gas by Jurassic systerm, basement rock, step on Lou Ku three cover hydrocarbon source rock air feed, to the rock gas contribution amount difference of different wells, further perfect, the clear and definite quantitative source of prosperous moral gas reservoir mixed-source natural gas.Virtue dark 1 and dark 2 wells of virtue are stepped on Lou Ku group rock gas mainly from four station slate group hydrocarbon source rocks of basement rock, account for 84.01%～85.25% of mixed-source natural gas, step on the contribution of Lou Ku group hydrocarbon source rock and account for 10.68%～10.97%%, and the Jurassic systerm contribution is below 5.3%; Dark 4 wells of virtue are stepped on Lou Ku group rock gas mainly from stepping on Lou Ku group hydrocarbon source rock, account for 42.08% of this well mixed-source natural gas, account for 31.90%, 25.99% respectively from Jurassic systerm (battalion's city group, Shahe son group and flint mountain range group), four station slate groups; Dark 5 wells of virtue are stepped on Lou Ku group rock gas mainly from four station slate group hydrocarbon source rocks, account for 42.48% of this well mixed-source natural gas, from Jurassic systerm (battalion's city group, Shahe son group and flint mountain range group), step on the Lou Ku group account for 42.17%, 15.32% respectively; Dark 6 wells of virtue are stepped on Lou Ku group and battalion's city group rock gas mainly from stepping on Lou Ku group hydrocarbon source rock, account for 41.15% of this well mixed-source natural gas, account for 38.60%, 20.23% respectively from Jurassic systerm (battalion's city group, Shahe son group and flint mountain range group), four station slate groups.Virtue dark 8 Jing Ying city groups and Shahe son group rock gas mainly comes Jurassic Shahe son group and flint mountain range group hydrocarbon source rock, accounts for 82.16% of this well mixed-source natural gas, accounts for 4.71%, 13.11% respectively from what Jurassic systerm was sought city group, basement rock four station slate groups.
(3) the different hydrocarbon source rock contribution of prosperous moral gas reservoir mixed-source natural gas quantitative simulation calculates, started the frontier of hydrocarbon source rock and rock gas research, for the quantitative evaluation hydrocarbon source rock provides new method and approach to the contribution of rock gas, this method is fit to two-layer to the ration contribution analog computation of four layers of hydrocarbon source rock to mixed-source natural gas, also be fit to of the analog computation of two to four rock gas payzones, have broad application prospects the ration contribution of multilayer producer rock gas.
Claims (8)
1, the method for the different source beds of a kind of quantitative evaluation mixed-source natural gas contribution proportion may further comprise the steps:
1) get gas in the source rock that produces rock gas, gas chromatography determination wherein adsorbs heavy hydrocarbon, chooses the chromatographic fingerprint peak; Simultaneously with absorption heavy hydrocarbon fingerprint ratio parameter in the calculated by peak area source rock at two close chromatographic fingerprint peaks choosing;
2) with the absorption heavy hydrocarbon fingerprint ratio parameter data of step 1) gas chromatography determination,,, get the characteristic fingerprint ratio parameter of its mean value as this layer hydrocarbon source rock according to principle with hydrocarbon source rock characteristic fingerprint similarity in one deck by each hydrocarbon source rock layering separate processes;
3) with step 2) the different hydrocarbon source rock layerings absorption heavy hydrocarbon characteristic fingerprint ratio parameter values that obtain, set the proportioning data substitution computation model function of different hydrocarbon source rock contribution proportions, utilize non-linear artificial neural network intelligence learning algorithm training to form different hydrocarbon source rock contribution quantitative simulations and calculate masterplate;
Described computation model function is:
Yn=k1*x1n+k2*x2n+ ... + km*xmn, wherein,
X is the characteristic fingerprint ratio parameter of absorption heavy hydrocarbon in the hydrocarbon source rock layering;
N is the right number of choosing in chromatographic fingerprint peak;
M is the number of plies of hydrocarbon source rock layering, m＞2;
K is the ration contribution ratio of hydrocarbon source rock layering to rock gas;
Y is a characteristic fingerprint ratio parameter in the mixed-source natural gas;
4) get corresponding mixed-source natural gas and carry out the heavy hydrocarbon gas chromatographic analysis, calculated by peak area with the chromatographic fingerprint peak of choosing with the same method of step 1) obtains individual features fingerprint ratio parameter, this characteristic fingerprint ratio parameter is imported described analog computation masterplate, calculate the ration contribution ratio of different hydrocarbon source rocks mixed-source natural gas.
2, the method for the different source beds of quantitative evaluation mixed-source natural gas according to claim 1 contribution proportion, it is characterized in that, the computation process of nonlinear artificial neural network intelligence learning algorithm is made up of forward-propagating and backpropagation described in the step 3), in the forward-propagating process, input information is successively handled through hidden layer from input layer, and to the output layer propagation, the neuronic state of each layer only influences the neuronic state of one deck down; If the output in that output layer can not obtain expecting then changes backpropagation over to, error signal is successively returned along original connecting path, revise the neuronic weights of each layer by error signal, make error reduce, reach accuracy requirement until error;
The local error function formula is as follows:
3, the method of the different source beds of quantitative evaluation mixed-source natural gas according to claim 1 contribution proportion, it is characterized in that, training described in the step 3) forms analog computation masterplate process, be to import the layering hydrocarbon source rock characteristic fingerprint ratio parameter that all are chosen one by one, through a series of Sigmoid function and matrix operation, weighting, on average, output to second hidden layer, a series of computings through same principle, output to first hidden layer, pass through a series of computings of same principle again, output layer promptly is the percentage contribution rate of each layering hydrocarbon source rock of mixed-source natural gas, each layer number percent contrast with artificial proportioning successively feedbacks error by original path, in the process of feedback, by the size of error, adjust the weight vector matrix of each node successively.Repeat top step once more according to the weight vector matrix after adjusting, so move in circles, the error between output and actual proportioning satisfies desired precision; The analog computation process has designed each layering hydrocarbon source rock contribution rate during masterplate and has thought relative error and precision control setting between the proportioning in training, each layering hydrocarbon source rock contribution rate is divided into 7 range of control:＜1% do not control, 1～5%, 5～10%, 10～25%, 25～50%, 50～75%, 75～100%, when the training masterplate, import the artificial desired relative error of each range of control respectively till; Error between described output and the actual proportioning finally satisfies absolute error less than 5%, and relative deviation is less than 10%; At this moment, store the weight matrix and the correlation parameter of each unit of each layer, just set up the calculating masterplate of mixed-source natural gas layering hydrocarbon source rock ration contribution;
Described Sigmoid function is asymmetric Sigmoid function
The functional value scope is (0,1).
4, the dynamic chromatogram monitoring method of multi-zone produced oil single-zone productivity contribution according to claim 3 is characterized in that, between described output and the actual proportioning error finally satisfy absolute error less than 5%, relative deviation is less than 10%.
5, according to the method for the different source beds of the arbitrary described quantitative evaluation mixed-source natural gas of claim 1 to 4 contribution proportion, it is characterized in that the step of choosing at the described chromatographic fingerprint of step 1) peak is:
(1) chooses the chromatographic fingerprint peak that all exists in each layer hydrocarbon source rock and the rock gas according to principle of universality;
(2) choose the chromatographic fingerprint peak that each layer hydrocarbon source rock all there are differences according to the otherness principle.
6, according to the method for the different source beds of the arbitrary described quantitative evaluation mixed-source natural gas of claim 1 to 4 contribution proportion, it is characterized in that the described calculated by peak area heavy hydrocarbon fingerprint ratio parameter that utilizes is followed following rule:
X=a/b is in the formula
X is the ratio of close fingerprint peaks area;
A, b are respectively the peak area of close fingerprint peaks.
7, according to the method for the different source beds of the arbitrary described quantitative evaluation mixed-source natural gas of claim 1 to 4 contribution proportion, it is characterized in that, the described step of producing gas from hydrocarbon source rock is: get source rock sample and put into the impacting type preparation facilities, after sealing vacuumizes, pulverize sample by the vibration bump, adsorbed gas in the source rock is discharged, adopt drainage to take out gas.
8, according to the method for the different source beds of the arbitrary described quantitative evaluation mixed-source natural gas of claim 1 to 4 contribution proportion, it is characterized in that, described source rock is made up of four layers of hydrocarbon source rock layering, the described quantitative simulation of step 3) calculates masterplate, calculates according to mixed gas heavy hydrocarbon and the chromatogram characteristic fingerprint ratio parameter value of each hydrocarbon source rock absorption heavy hydrocarbon and the following relationship between its contribution rate:
y1＝k1*x11+k2*x21+k3*x31+k4*x41
y2＝k2*x12+k2*x22+k3*x32+k4*x42
......
Yn=k1*x1n+k2*x2n+k3*x3n+k4*x4n, in the formula,
X11, x12......x1n are respectively the characteristic fingerprint ratio parameter value to the absorption heavy hydrocarbon of certain peak in the hydrocarbon source rock 1;
X21, x22......x2n are respectively the characteristic fingerprint ratio parameter value to the absorption heavy hydrocarbon of certain peak in the hydrocarbon source rock 2;
X31, x32......x3n are respectively the characteristic fingerprint ratio parameter value to the absorption heavy hydrocarbon of certain peak in the hydrocarbon source rock 3;
X41, x42......x4n are respectively the characteristic fingerprint ratio parameter value to the absorption heavy hydrocarbon of certain peak in the hydrocarbon source rock 4;
K1, k2........k4 are respectively the ration contribution rate of hydrocarbon source rock 1 to 4 pairs of rock gases of hydrocarbon source rock;
Y1, y2........yn are respectively in the mixed-source natural gas certain peak to the ratio parameter value of characteristic fingerprint compound;
N is the right number of choosing in chromatographic fingerprint peak.
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