CN109931053A - The recognition methods of sand shale-carbonate rock - Google Patents
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Abstract
The present invention provides a kind of recognition methods of sand shale-carbonate rock characterized by comprising S1) content of Si, Al, Ca and Mg element in detection chip sample to be measured；S2 SiO in chip sample to be measured) is calculated2With Al2O3Total content XSS, the total content X of CaO and MgOLD；According to XSSWith XLDJudge the lithology of chip sample to be measured.Compared with prior art, the present invention detects Si, Al, Ca, Mg constituent content in chip sample first, calculates XSS、XLDContent data, realize sand shale-carbonate rock fast and automatically, accurately identify, overcome defect existing in the prior art, this method is easy to operate, Lithology Discrimination result is accurate, it can be conducive to oil-gas resource RESERVOIR RECOGNITION, improve oil-gas resource exploration and development benefit, drilling safety is instructed efficiently to construct.
Description
Technical field
The invention belongs to petroleum natural gas exploration technical field more particularly to the knowledges of sand shale-carbonate rock
Other method.
Background technique
In oil and gas exploration and development process, sedimentary rock, carbonate formation be oil-gas resource generation,
Migration and storage main force stratum are needed for accurate discovery oil-gas resource to deposition by stratum self-characteristic Different Effects
Rock and carbonate formation are identified.Related geological theory shows: sand shale is mainly by the mineral compositions such as quartz, clay, oxygen
Compound main component is SiO2And Al2O3, SiO in sand shale2And Al2O3Content 60~95%；Carbonate rock is mainly by white clouds
Stone, calcite form, CaO or CaO+MgO content is big in the carbonate rocks such as limestone, dolomite, SiO2, Al2O3Equal size is general
Less than 10%, therefore by the content of tetra- kinds of elements of Si, Al, Ca, Mg in measurement analysis drilling strata chip sample, correlation is utilized
Formula calculates CaO, MgO, SiO in rock sample2、Al2O3Content quick standard can go to identify sample rock at the construction field (site)
Property be sand shale, carbonate rock, carbonate matter sand shale, sand shale carbonate rock, realize sand shale-carbonate rock from
Dynamic identification.
Traditional Division identification sedimentary rock-carbonate rock recognition methods mainly relies on well logging field geology technology people
Member identify or by hydrochloric acid solution to landwaste sample by physical features such as the shape, structures of observation drilling strata chip sample
Product, which impregnate, generates chemical reaction, according to production CO2Gas content height carries out judgement sample lithology.
The Chinese patent of Publication No. CN105888657A discloses the Lithology Discrimination that sedimentary rock is carried out using element well logging
Method is specifically disclosed a kind of Lithology Identification Methods for being carried out sedimentary rock using element well logging, is made of following steps: a, processing
Element logging data, is translated into percentage composition；B, using hundred shared by debris-sensitive element and carbonate sensitive elements content
Ratio is divided to distinguish carbonate rock and clastic rock two major classes；C, in carbonate rock, calcium sulphate content is calculated, magnesium calcium carbonate contains
Amount and calcium carbonate content；D, in clastic rock class, sandy content and shale content are calculated；E, by calculated calcium sulfate, carbon
Sour magnesium calcium, calcium carbonate, chiltern and shale content calculate separately out cream matter, white clouds matter, calcium carbonate, chiltern by normalized
And shale content, to determine lithology by its content.But this method is influenced by element mud logging techniques self-technique condition, measurement
The element species arrived are not full up enough, while needing to grind chip sample, the processing such as tabletting, and there are the analytical cycle times
The problems such as long, it is difficult to meet the Lithology Discrimination requirement under the conditions of drilling speed drilling technology.
The Chinese patent of Publication No. CN106469257A discloses a kind of mixed deposit based on three end member mineral contents
Petrographic classification naming method determines the upper limit value of external source clast content in peperite according to effective capacity；According to rock composition, really
Fixed three end member classification schemes；Step is named to determine basic designation according to rock constituents content, secondly by cement and special knot
Structure or diagenesis are named as qualifier participation；Specific naming rule, it is true respectively according to the peperite based on heterogeneity
Determine basic designation, when secondary mineral content is 25%~50%, using ×× matter as additional qualifier, when content is less than 25%,
To contain ×× as additional qualifier.But this method does not provide the characteristic parameter of carbonate rock, cannot achieve sedimentary rock-
Carbonate rock automatic identification.
Summary of the invention
In view of this, the technical problem to be solved in the present invention is that provide a kind of sand shale-carbonate rock laser from
Dynamic recognition methods.
The present invention provides a kind of recognition methods of sand shale-carbonate rock, comprising:
S1 the content of Si, Al, Ca and Mg element in chip sample to be measured) is detected；
S2 SiO in chip sample to be measured) is calculated2With Al2O3Total content XSS, the total content X of CaO and MgOLD；According to XSS
With XLDJudge the lithology of chip sample to be measured.
Preferably, the step S1) specifically:
Element spectrum analysis is carried out to standard lithological electrofacies material sample, obtains Si, Al, Ca and Mg component spectrum intensity-content
Mathematical model；
Element spectrum analysis is carried out to chip sample to be measured, and according to Si, Al, Ca and Mg component spectrum intensity-content number
It learns model and obtains the content of Si, Al, Ca and Mg element in chip sample to be measured.
Preferably, the element spectrum analysis using laser induced breakdown spectrograph or laser lithology automatic identifier into
Row.
Preferably, the standard lithological electrofacies material sample is selected from dolomite, siliceous sandstone, shale, limestone and limestone wind
Change soil.
Preferably, the spectral intensity in Si, Al, Ca and Mg component spectrum intensity-the content mathematical model is characterized wave
Long corresponding spectral intensity；The characteristic wavelength of the Si element is 288.158nm；The characteristic wavelength of the Al element is
309.27nm；The characteristic wavelength of the Ca element is 317.933nm；The characteristic wavelength of the Mg element is 280.271nm.
Preferably, shown in Si, Al, Ca and Mg component spectrum intensity-content mathematical model such as formula (1)~formula (4):
CSi=104765 × I288.158+ 1.866 formulas (1)；
CAl=32180 × I309.271- 2.098 formulas (2)；
CCa=224257 × I317.933- 8.9637 formulas (3)；
CMg=5840 × I280.271+ 0.079 formula (4)；
Wherein, CSiFor Si constituent content；I288.158For spectral intensity number corresponding to Si elemental characteristic wave 288.158nm
According to；CAlFor Al constituent content；I309.271For spectrum intensity data corresponding to Al elemental characteristic wavelength 396.152nm；CCaFor Ca
Constituent content；I317.933For spectrum intensity data corresponding to Ca elemental characteristic wavelength 442.544nm；CMgFor Mg constituent content；
I280.271For spectrum intensity data corresponding to Mg elemental characteristic wavelength 382.936nm.
Preferably, the XSSIt is calculated according to formula (5):
XSS=2.14 × CSi+1.89×CAlFormula (5).
Preferably, the XLDIt is calculated according to formula (6):
XLD=1.40 × CCa+1.66×CMgFormula (6).
The present invention provides a kind of recognition methods of sand shale-carbonate rock characterized by comprising S1) detection
The content of Si, Al, Ca and Mg element in chip sample to be measured；S2 SiO in chip sample to be measured) is calculated2With Al2O3Total content
XSS, the total content X of CaO and MgOLD；According to XSSWith XLDJudge the lithology of chip sample to be measured.Compared with prior art, of the invention
Si, Al, Ca, Mg constituent content in chip sample are detected first, calculate XSS、XLDContent data realizes sand shale-carbonate
Rock fast and automatically, accurately identify, overcome defect existing in the prior art, this method is easy to operate, and Lithology Discrimination result is quasi-
Really, oil-gas resource RESERVOIR RECOGNITION can be conducive to, carbon oil-gas resource exploration and development benefit is improved, instruct drilling well
Safe and efficient construction.
Further, the present invention is contained using Si, Al, Ca, Mg element of laser lithology automatic identifier detection chip sample
Amount, while passing through the characteristic wavelength of preferred Si, Al, Ca, Mg element, the accuracy of testing result is further increased, and then improve
The accuracy of Lithology Discrimination result.
Detailed description of the invention
Fig. 1 is the characteristic spectrum line chart according to preferred Si, Al, Ca, Mg element of standard lithological electrofacies material sample LIBS spectrogram.
Specific embodiment
Below in conjunction with the embodiment of the present invention, technical scheme in the embodiment of the invention is clearly and completely described,
Obviously, described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Based in the present invention
Embodiment, every other embodiment obtained by those of ordinary skill in the art without making creative efforts, all
Belong to the scope of protection of the invention.
The present invention provides a kind of recognition methods of sand shale-carbonate rock, comprising:
S1 the content of Si, Al, Ca and Mg element in chip sample to be measured) is detected；
S2 SiO in chip sample to be measured) is calculated2With Al2O3Total content XSS, the total content X of CaO and MgOLD；According to XSS
With XLDJudge the lithology of chip sample to be measured.
The present invention is not particularly limited the source of all raw materials, is commercially available.
The present invention detects the content of Si, Al, Ca and Mg element in chip sample to be measured first, preferably according to the following steps into
Row: element spectrum analysis is carried out to standard lithological electrofacies material sample, obtains Si, Al, Ca and Mg component spectrum intensity-content mathematical modulo
Type；Element spectrum analysis is carried out to chip sample to be measured, and according to Si, Al, Ca and Mg component spectrum intensity-content mathematical model
Obtain the content of Si, Al, Ca and Mg element in chip sample to be measured.
Wherein, the standard lithological electrofacies material sample is standard lithological electrofacies material sample well known to those skilled in the art,
Special limitation is had no, is preferably dolomite (GBW07217a), siliceous sandstone (GBW03112), shale in the present invention
(GBW03104), limestone (GBW03105a) and limestone saprolite (GBW07404)；The method of the element spectrum analysis is
Method well known to those skilled in the art has no special limitation, preferably uses laser induced breakdown spectroscopy in the present invention
Instrument or laser lithology automatic identifier carry out, petrochemical industry Central Plains well logging company, petroleum works Co., Ltd production more preferably in use
Laser lithology automatic identifier；The elemental analysis is preferably within the scope of 207~320nm of wavelength；Within this range Si, Al,
Ca, Mg element have stronger the intensity of spectral line, but between different element spectral lines there is interfere with each other, strength degree phenomena such as,
According to spectral intensity, cross jamming principle, the preferably characteristic spectral line of Si, Al, Ca, Mg element are avoided, as shown in FIG. 1, FIG. 1 is roots
According to the characteristic spectrum line chart of preferred Si, Al, Ca, Mg element of standard lithological electrofacies material sample LIBS spectrogram；The feature of the Si element
Wavelength is 288.158nm；The characteristic wavelength of the Al element is 309.27nm；The characteristic wavelength of the Ca element is
317.933nm；The characteristic wavelength of the Mg element is 280.271nm；Thus Si, Al, Ca and Mg component spectrum intensity-established
Shown in content mathematical model such as formula (1)~formula (4):
CSi=104765 × I288.158+ 1.866 formulas (1)；
CAl=32180 × I309.271- 2.098 formulas (2)；
CCa=224257 × I317.933- 8.9637 formulas (3)；
CMg=5840 × I280.271+ 0.079 formula (4)；
Wherein, CSiFor Si constituent content；I288.158For spectral intensity number corresponding to Si elemental characteristic wave 288.158nm
According to；CAlFor Al constituent content；I309.271For spectrum intensity data corresponding to Al elemental characteristic wavelength 396.152nm；CCaFor Ca
Constituent content；I317.933For spectrum intensity data corresponding to Ca elemental characteristic wavelength 442.544nm；CMgFor Mg constituent content；
I280.271For spectrum intensity data corresponding to Mg elemental characteristic wavelength 382.936nm.
SiO in chip sample is preferably also calculated separately out according to the content of Si, Al, Ca and Mg element according to the present invention2、
Al2O3, CaO and MgO content.
Calculate SiO in chip sample2With Al2O3Total content XSS, the total content X of CaO and MgOLD；Wherein, the XSSIt is excellent
Choosing is calculated according to formula (5)；The XLDIt is preferred that being calculated according to formula (6).
XSS=2.14 × CSi+1.89×CAlFormula (5)
XLD=1.40 × CCa+1.66×CMgFormula (6)
According to XSSWith XLDJudge the lithology of chip sample to be measured.Work as XSS>=60%, and XLDWhen≤10%, the landwaste lithology
For sand shale；Work as XLDWhen >=50%, and XSS≤ 10%, which is carbonate rock；As 35% ﹤ XSS﹤ 60%, and 10% ﹤
XLDThe landwaste lithology of ﹤ 30% is carbonate matter sand shale；As 10% ﹤ XSS≤ 35%, and 30%≤XLDThe landwaste lithology of ﹤ 50%
For sand shale carbonate rock.
The present invention detects Si, Al, Ca, Mg constituent content in chip sample first, calculates XSS、XLDContent data is realized
Sand shale-carbonate rock fast and automatically, accurately identify, overcome defect existing in the prior art, this method is easy to operate,
Lithology Discrimination result is accurate, can be conducive to oil-gas resource RESERVOIR RECOGNITION, improves the exploration of carbon oil-gas resource and opens
Benefit is sent out, drilling safety is instructed efficiently to construct.
Further, the present invention is contained using Si, Al, Ca, Mg element of laser lithology automatic identifier detection chip sample
Amount, while passing through the characteristic wavelength of preferred Si, Al, Ca, Mg element, the accuracy of testing result is further increased, and then improve
The accuracy of Lithology Discrimination result.
In order to further illustrate the present invention, with reference to embodiments to sand shale-carbonate rock provided by the invention
Laser automatic identifying method is described in detail.
Reagent used in following embodiment is commercially available.
Embodiment
The ZY-LLA type laser lithology automatic identification that petrochemical industry Central Plains well logging company, petroleum works Co., Ltd produces in
Instrument, the identifier include controller, industrial personal computer, spectrometer, laser, sample stage and power supply, and laser passes through optical fiber and sample
Platform is connected, and sample stage is connected by optical fiber with spectrometer, and spectrometer is connected by data line with the input terminal of controller, controller
Output end be connected with industrial personal computer by data line, controller, industrial personal computer, spectrometer and laser pass through respectively power supply line with it is electric
Source is connected；Chip sample is placed on sample stage, after starting the identifier, controller control laser launches superlaser
It is irradiated to the chip sample surface to be measured being placed on sample stage, it is made to generate plasma, plasma returns to normal temperature state
When sample contained by difference element launch spectrum spectrometer be sent by optical fiber and handled, it is logical through spectrometer treated data
It crosses data line and is sent into controller, controller handle to the data received from spectrometer and data pass through work by treated
Control machine informs that staff, staff can be obtained the element information of chip sample.
1, Si, Al, Ca, Mg element light intensity-content mathematical model are established
(1) characteristic wavelength of preferred Si, Al, Ca, Mg element.
It is (siliceous using laser lithology automatic identifier detection national standard substance GBW07217a (dolomite), GBW03112
Sandstone), GBW03104 (shale), GBW03105a (limestone), GBW07404 (limestone saprolite), five kinds of comparative analysis mark
Quasi- substance LIBS spectrogram, between wavelength 270nm~320nm range, Si, Al, Ca, Mg element have stronger the intensity of spectral line,
But between different element spectral lines there is interfere with each other, strength degree phenomena such as, according to spectral intensity, avoid cross jamming former
Then, the preferred characteristic spectral line of Si, Al, Ca, Mg element, wherein Si elemental characteristic wavelength is 288.158nm, Al elemental characteristic wavelength
For 309.271nm, Ca elemental characteristic wavelength is 317.933nm, and the characteristic wavelength of Mg element is 280.271nm.
(2) Si, Al, Ca, Mg element light intensity-content mathematical model are established.
National standard substance matter GBW07217a (dolomite), GBW03112 (silicon are detected using laser lithology automatic identifier
Matter sandstone), GBW03104 (shale), GBW03105a (limestone) and GBW07404 (limestone saprolite) sample, record respectively
Wavelength is spectral intensity values I corresponding to 288.158nm, 309.271nm, 317.933nm and 280.271nm288.15、I309.271、
I317.933、I280.271, establish I288.15、I309.271、I317.933、I280.271Element light intensity-content mathematical model:
CSi=104765 × I288.158+ 1.866 formulas (1)；
CAl=32180 × I309.271- 2.098 formulas (2)；
CCa=224257 × I317.933- 8.9637 formulas (3)；
CMg=5840 × I280.271+ 0.079 formula (4)；
Wherein formula (1) is Si component spectrum intensity-content mathematical model, CSiFor Si constituent content；I288.158For Si element
Spectrum intensity data corresponding to characteristic wave 288.158nm；
Formula (2) is Al component spectrum intensity-content mathematical model, CAlFor Al constituent content；I309.271For Al elemental characteristic
Spectrum intensity data corresponding to wavelength 396.152nm.
Formula (3) is Ca component spectrum intensity-content mathematical model, CCaFor Ca constituent content；I317.933For Ca elemental characteristic
Spectrum intensity data corresponding to wavelength 442.544nm；
Formula (4) is Mg component spectrum intensity-content mathematical model, CMgFor Mg constituent content；I280.271For Mg elemental characteristic
Spectrum intensity data corresponding to wavelength 382.936nm.
2, test sample Si, Al, Ca, Mg constituent content
(1) element spectrum analysis is carried out using carbonate samples of the laser lithology automatic identifier to lithology to be identified,
Record I288.158、I396.152、I442.544And I382.936Data.
(2) sample Si, Al, Ca, Mg constituent content are calculated
According to I288.158、I396.152、I442.544And I382.936, by formula (1)~formula (4) calculate separately out Si in sample,
Al, Ca, Mg constituent content.
3, SiO is calculated2And Al2O3Total content XSS, CaO and MgO total content XLD
According to Si, Al, Ca, Mg constituent content, SiO is calculated according to following formula respectively2And Al2O3Total content XSS, CaO and MgO always contain
Measure XLD。
XSS=2.14 × CSi+1.89×CAlFormula (5)
XLD=1.40 × CCa+1.66×CMgFormula (6)
4, automatic identification sand shale-carbonate rock
(1) work as XSS>=60%, and XLDWhen≤10%, which is sand shale；
(2) work as XLDWhen >=50%, XSS≤ 10%, which is carbonate rock；
(3) as 35% ﹤ XSS﹤ 60%, and 10% ﹤ XLDThe landwaste lithology of ﹤ 30% is carbonate matter sand shale；
(4) as 10% ﹤ XSS≤ 35%, and 30%≤XLDThe landwaste lithology of ﹤ 50% is sand shale carbonate rock.
The present embodiment carries out identification judgement to the carbonate rock of construction site using above-mentioned recognition methods, specifically:
1#, 2#, 3#, 4# core sample progress for carbonate rock are had confirmed that scene using ZY-LLA type laser lithology automatic identifier
Element spectrum analysis obtains the corresponding spectral intensity I of Si, Al, Ca, Mg characteristic wavelength in each sample288.158、I396.152、
I442.544And I382.936, SiO in each sample is calculated separately out using formula (1)~formula (6)2And Al2O3Total content XSS, CaO and
MgO total content XLD, according to XSS、XLDIt identifies sample lithology relationship (table 1), automatically identifies sample and correspond to lithology.
1 core sample element spectrum analysis result of table
| Sample number into spectrum | I288.158 | I396.152 | I442.544 | I382.936 | XSS | XLD | Sample lithology |
| 1# | 0.0000060 | 0.0000706 | 0.0031054 | 0.0000208 | 9.82 | 78.42 | Carbonate rock |
| 2# | 0.0000706 | 0.0005612 | 0.0001800 | 0.0000436 | 54.93 | 1.27 | Carbonate matter sand shale |
| 3# | 0.0000653 | 0.0010869 | 0.0003703 | 0.0000951 | 86.55 | 9.76 | Sand shale |
| 4# | 0.0000102 | 0.0000747 | 0.0010782 | 0.0003303 | 11.00 | 44.24 | Argillo arenaceous carbonate rock |
As shown in Table 1, the present embodiment lithology automatic identification conclusion is consistent with traditional qualification result of thin section identification method, table
Bright recognition methods of the present invention is realized to carbonate rock fine description, can quick and precisely judge formation lithology, lithology automatically
Recognition result is accurate, can be conducive to oil-gas resource RESERVOIR RECOGNITION, improves carbon oil-gas resource exploration and development effect
Benefit instructs drilling safety efficiently to construct.
Claims (8)
1. a kind of recognition methods of sand shale-carbonate rock characterized by comprising
S1 the content of Si, Al, Ca and Mg element in chip sample to be measured) is detected；
S2 SiO in chip sample to be measured) is calculated2With Al2O3Total content XSS, the total content X of CaO and MgOLD；According to XSSWith XLD
Judge the lithology of chip sample to be measured.
2. recognition methods according to claim 1, which is characterized in that the step S1) specifically:
Element spectrum analysis is carried out to standard lithological electrofacies material sample, obtains Si, Al, Ca and Mg component spectrum intensity-content mathematics
Model；
Element spectrum analysis is carried out to chip sample to be measured, and according to Si, Al, Ca and Mg component spectrum intensity-content mathematical modulo
Type obtains the content of Si, Al, Ca and Mg element in chip sample to be measured.
3. recognition methods according to claim 2, which is characterized in that the element spectrum analysis uses laser-induced breakdown
Spectrometer or laser lithology automatic identifier carry out.
4. recognition methods according to claim 2, which is characterized in that the standard lithological electrofacies material sample be selected from dolomite,
Siliceous sandstone, shale, limestone and limestone saprolite.
5. recognition methods according to claim 2, which is characterized in that Si, Al, Ca and Mg component spectrum intensity-contains
Spectral intensity in amount mathematical model is characterized the corresponding spectral intensity of wavelength；The characteristic wavelength of the Si element is
288.158nm；The characteristic wavelength of the Al element is 309.27nm；The characteristic wavelength of the Ca element is 317.933nm；It is described
The characteristic wavelength of Mg element is 280.271nm.
6. recognition methods according to claim 2, which is characterized in that Si, Al, Ca and Mg component spectrum intensity-contains
It measures shown in mathematical model such as formula (1)~formula (4):
CSi=104765 × I288.158+ 1.866 formulas (1)；
CAl=32180 × I309.271- 2.098 formulas (2)；
CCa=224257 × I317.933- 8.9637 formulas (3)；
CMg=5840 × I280.271+ 0.079 formula (4)；
Wherein, CSiFor Si constituent content；I288.158For spectrum intensity data corresponding to Si elemental characteristic wave 288.158nm；CAl
For Al constituent content；I309.271For spectrum intensity data corresponding to Al elemental characteristic wavelength 396.152nm；CCaContain for Ca element
Amount；I317.933For spectrum intensity data corresponding to Ca elemental characteristic wavelength 442.544nm；CMgFor Mg constituent content；I280.271
For spectrum intensity data corresponding to Mg elemental characteristic wavelength 382.936nm.
7. recognition methods according to claim 6, which is characterized in that the XSSIt is calculated according to formula (5):
XSS=2.14 × CSi+1.89×CAlFormula (5).
8. recognition methods according to claim 6, which is characterized in that the XLDIt is calculated according to formula (6):
XLD=1.40 × CCa+1.66×CMgFormula (6).
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Cited By (5)
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| CN111537663A (en) * | 2020-04-20 | 2020-08-14 | 中国石油天然气集团有限公司 | Lithology identifier carrying device and lithology identification system and method based on lithology identifier carrying device |
| CN113008872A (en) * | 2019-12-20 | 2021-06-22 | 雄贝(上海)科技有限公司 | Rock debris lithology laser identification method based on mineral components |
| CN113125412A (en) * | 2019-12-31 | 2021-07-16 | 中石化石油工程技术服务有限公司 | Sandstone-mudstone recognition plate lithology recognition method based on laser element information |
| CN113177919A (en) * | 2021-04-28 | 2021-07-27 | 成都艾立本科技有限公司 | Lithology classification and principal component element content detection method combining LIBS and deep learning |
| CN115602253A (en) * | 2022-05-10 | 2023-01-13 | 铜仁学院（Cn） | Method for evaluating influence of exogenous acid on chemical weathering and geological carbon sink of carbonate rock |
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