CN107605465A - Based on XRF elements well logging with the method that shale TOC parameters are obtained in brill - Google Patents
Based on XRF elements well logging with the method that shale TOC parameters are obtained in brill Download PDFInfo
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Abstract
The invention discloses a kind of method based on XRF elements well logging with acquisition shale TOC parameters in brill, including：1. grasping the stratum characteristic information in the region of work area in a manner of well logging and/or experimental analysis, the stratum characteristic information grasped is subjected to data preparation by the depth in work area region；2. the rock composition information in the region of work area is obtained by XRF elements well logging, the rock composition information obtained is carried out to the comparison of corresponding depth by the depth in work area region with the stratum characteristic information grasped, the playback for the rock composition information realization uniform depth for making grasped stratum characteristic information and being obtained is handled, and forms the combined data collection of uniform depth scale；3. being concentrated in combined data, sensitive elements are selected for the shale TOC parameters for needing to obtain；4. carrying out data fitting with multiple linear regression analysis method, the multiple regression transformation model established between element and shale TOC parameters, shale TOC parameters are obtained by transformation model.
Description
Technical field
The present invention relates to the method that shale evaluating is obtained in mud logging operation, is specifically that one kind is based on XRF element well loggings
With the method that shale TOC parameters are obtained in brill.
Background technology
Mud logging operation is the most basic technology in oil-gas exploration and development activity, is discovery, assesses oil-gas reservoir most in time, be most straight
The means connect, have and obtain the characteristics of subsurface information is timely, various and analysis interpretation is quick, information is provided for drillng operation
Service.
, it is necessary to obtain the shale evaluating of underground, wherein shale TOC in time in the exploration and development activity of shale gas reservoir
Parameter (the total organic carbon parameter i.e. in shale) is one of emphasis parameter of concern, can be with by acquired shale TOC parameters
Geology characteristic, oil accumulation factor to shale gas reservoir etc. are integrated, global analysis, and then are obtained and grasped the effective of shale gas well
Drilling information.
At present, the acquisition of shale TOC parameters is mainly realized in a manner of log measurement after brill or laboratory testing analysis.
However, because the oil accumulation factor of shale gas reservoir is complicated, the page after brill acquired in the mode of log measurement or laboratory testing analysis
Rock TOC parameters are relative to have time lag, the not high technical problem of expensive, cost performance, and shale gas well is carried out with this data
Drilling when, it is difficult to which exploration to shale gas well and exploitation provide timely, reliable information support.
The content of the invention
The technical purpose of the present invention is：For above-mentioned the deficiencies in the prior art, there is provided one kind, which can be evaluated shale, joins
Number-T0C parameters realize in time, it is quick, accurately and reliably obtain, that exploration and exploitation that can be to shale gas well provide is accurate, can
Lean on, effectively information support based on XRF elements well logging with brill obtain shale TOC parameters method.
The present invention realize its technical purpose the technical scheme adopted is that it is a kind of based on XRF elements well logging with being obtained in brill
The method of shale TOC parameters, comprises the following steps：
Step 1. grasps the stratum characteristic information in the region of work area in a manner of well logging and/or experimental analysis；
Step 2. obtains the rock composition information in the region of work area, the rock composition that will be obtained by XRF elements well logging
Information carries out the comparison of corresponding stratigraphic horizon and depth with the stratum characteristic information grasped, and makes grasped stratum characteristic information
The playback of unified layer position and depth is handled with the rock composition information realization that is obtained, forms the total amount of uniform depth scale
According to collection；
Step 3. is concentrated in combined data, and sensitive elements are selected for the shale TOC parameters for needing to obtain；
Step 4. carries out data fitting with multiple linear regression analysis method, establishes polynary between element and shale TOC parameters
Transformation model is returned, the transformation model is：TOC=β0+β1*X1+β2*X2+…+βk*Xk；In formula, β0、β1、β2…βkTo return
Coefficient, X1、X2…XkThe content of respectively different elements；
Shale TOC parameters are obtained by transformation model.
The comparison of rock composition information stratigraphic horizon corresponding with stratum characteristic information and depth is to be obtained in step 2
The rock composition information obtained is compared by corresponding depth interpolation in the stratum characteristic information grasped, or, it will be grasped
Stratum characteristic information vacuate by corresponding depth and be compared afterwards with the rock composition information obtained.Preferably, walk
The comparison of rock composition information stratigraphic horizon corresponding with stratum characteristic information and depth is in rapid 2, and the stratum grasped is special
Reference breath is vacuated by corresponding depth and is compared afterwards with the rock composition information obtained.
Sensitive elements selection in step 3 is that first each element is classified in a manner of Hierarchical Clustering by interdependence, then
The element of these classification is selected in the way of principal component analysis, screening obtains corresponding sensitive elements.
Preferably, the sensitive elements comprise at least tetra- kinds of elements of Si, S, Ca and Fe.
The method have the benefit that：The above method is based on XRF (X-ray fluorescence spectra analysis) element well logging, from
And shale evaluating-shale TOC parameters can be effectively and reliably obtained in brill, the acquisition of shale TOC parameters is relative
With it is timely, quick, accurate, reliable the characteristics of, to instruct the drilling of shale gas well with shale T0C parameters acquired in brill,
It can be to shale gas well exploration and exploitation quick, accurate, reliable, effectively information support is provided, be advantageous to shale gas well
Realize high efficiency, high quality drilling.
Brief description of the drawings
Fig. 1 is calculating contrast effect figure of the shale TOC parameters with XRF elements of test well-YY2 wells.
Embodiment
The present invention relates to the method that shale evaluating is obtained in mud logging operation, is specifically that one kind is based on XRF element well loggings
With the method that shale TOC parameters are obtained in brill.The technology contents of the present invention are carried out in detail, clearly with multiple embodiments below
Explanation.
Embodiment 1
The present invention includes following order step：
Step 1. grasps the stratum characteristic information in the region of shale gas reservoir work area in a manner of well logging and/or experimental analysis,
Using the stratum characteristic information grasped according to shale gas reservoir work area region depth as data preparation scale, carry out data it is whole
Reason；
Step 2. carries out mud logging operation to the work area region of shale gas reservoir, and the mud logging operation is with XRF element well loggings with brill
Mode is realized, the rock composition information in the region of shale gas reservoir work area is obtained, by the rock composition information obtained according to work area
Scale of the depth in region as data preparation, carry out data preparation；
Using the work area regional depth of shale gas reservoir as scale, by the rock composition information obtained and the stratum grasped
Characteristic information carries out the comparison of corresponding stratigraphic horizon and depth；In the comparison of corresponding stratigraphic horizon and depth, due to not Tongfang
The data that method is obtained have it is different measurement spacing, depth disunity, it is then desired to by the stratum characteristic information grasped according to
Corresponding depth carries out vacuating processing, in this way, the stratum characteristic information that part is grasped is abandoned, but the rock that complete reservation is obtained
Stone composition information, under uniform depth scale, the two data message is compared, makes grasped stratum characteristic information and institute
The playback processing of the rock composition information realization uniform depth of acquisition, form the combined data collection of uniform depth scale；
Step 3. is concentrated in combined data, and sensitive elements are selected for the shale TOC parameters for needing to obtain, sensitivity member
Element comprises at least but is not limited to tetra- kinds of elements of Si, S, Ca and Fe；The selection of sensitive elements is, first by each element with Hierarchical Clustering
Mode by interdependence classify, then by these classification elements selected in the way of principal component analysis, screening obtain it is final,
Corresponding sensitive elements；
Step 4. carries out data fitting with multiple linear regression analysis method, establishes polynary between element and shale TOC parameters
Transformation model is returned, the transformation model is as follows：
TOC=β0+β1*X1+β2*X2+…+βk*Xk；
In formula, TOC is shale TOC parameters (the total organic carbon parameter i.e. in shale)；
β0、β1、β2…βkFor regression coefficient；
X1、X2…XkThe content of respectively different elements；
Shale TOC parameters are obtained by above-mentioned transformation model.
Make further details of elaboration to the present invention with reference to test data.
The present invention is tested experiment on the imperial one section of stratum of Longma small stream group of Yongchuan work area YY2 wells, its shale TOC parameters
Source be DH2020 type fixed logging instruments analysis result, element data using CIT-3000SY type elements logging analysis,
159 pieces of core samples are analyzed altogether, and sampling spacing is 0.50~1.00 meter, and the element of measurement includes Mg (magnesium), Al (aluminium), Si
(silicon), P (phosphorus), S (sulphur), Mn (manganese), Fe (iron),
K (potassium), Ti (titanium), Ca (calcium), Cl (chlorine), V (vanadium) etc. more than 20 is planted.
The thinking of experiment is with flow：Element is the most basic unit of petrochemistry composition, establishes element and joins with shale TOC
Mathematical function between number, it can be achieved with being calculated with brill for shale TOC parameters；But because rock constituents are complex, exist
Obvious conllinear sex chromosome mosaicism is optimized or boundary constraint using specific algorithm, it is necessary to according to area feature, it is difficult to is directly pushed away
Extensively it is applied to other regions；In this way, basic ideas are the shale TOC parameters point by XRF elements well logging and rock pyrolysis well logging
Analyse data comparison, the transformation model established by Mathematical Fitting between element and shale TOC parameters；Calculation process is by polynary
Mathematical Fitting analysis, the mathematical modeling established between element and shale TOC parameters are carried out in linear regression.
Shale TOC parameters with bore computational methods be：
(1) TOC, XRF Elemental analysis data of experiment well are obtained；
TOC, the element data of YY2 wells are shown in Table 1；
The YY2 wells TOC of table 1 and element data table
(2) foundation of transformation model
Data fitting is carried out using multiple linear regression analysis method, multivariate regression models expression formula is：
TOC=β0+β1*X1+β2*X2+…+βk*Xk；
In formula, β0, β1, β2…,βkFor regression coefficient；
X1, X2..., XkRespectively different constituent contents；
Carry out the preferred of mathematical modeling using stepwise regression method (StepwiseRegression), determine best model；
Full model comprising whole elements is referred to as Mp, in MpOn the basis of reduce by an element, establish one it is only first comprising p-1
The new model of element is Mp-1, in Mp-1On the basis of reduce by an element again, establish an only new model comprising p-2 element
Mp-2, repeatedly p modeling process, obtains p model, contrasts the coefficient R of each model by that analogy2, select R2
Larger model alternately model, by analyzing TOC geological Significance, not exclusively according to R2As preferably foundation, suitably enter
The constraint of row model boundary, therefrom selects an optimal mathematical modeling, and specific computation model is shown in Table 2；
The TOC computation models of table 2
| TOC computation models | Coefficient correlation (R2) |
| Y=f (Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Cu) | 0.8733 |
| Y=f (Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Cu) | 0.87416 |
| Y=f (Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe) | 0.87444 |
| Y=f (Mg, Al, Si, P, S, Cl, K, Ca, Ti, Cr, Mn, Fe) | 0.87051 |
| Y=f (Mg, Al, Si, P, S, K, Ca, Ti, Cr, Mn, Fe) | 0.87099 |
| Y=f (Mg, Al, Si, P, S, K, Ca, Ti, Mn, Fe) | 0.86906 |
| Y=f (Mg, Al, Si, S, K, Ca, Ti, Mn, Fe) | 0.86766 |
| Y=f (Mg, Al, Si, S, K, Ca, Ti, Fe) | 0.86731 |
| Y=f (Mg, Al, Si, S, K, Ca, Fe) | 0.8631 |
| Y=f (Al, Si, S, K, Ca, Fe) | 0.86291 |
| Y=f (Al, Si, S, Ca, Fe) | 0.85715 |
| Y=f (Si, S, Ca, Fe) | 0.85095 |
| Y=f (Si, S, Fe) | 0.75608 |
| Y=f (Si, Fe) | 0.44939 |
Using different element combinations, the coefficient correlation of its mathematical modeling difference；
In order to facilitate the application of model, the foundation of this selection mathematical modeling is：Not exclusively according to R2Size be used as according to
According to, but ensureing R2On the premise of larger, the less formula of prioritizing selection element；The calculating mould of tetra- kinds of elements of Si, S, Ca, Fe
Type its coefficient correlation is 0.85095, and compared to the computation model of the element of selection kind more than 10, coefficient correlation reduced by only 0.02, and
Its coefficient correlation of the mathematics computing model of tri- kinds of elements of Si, S, Fe is used as 0.756, the coefficient correlation of a upper model reduces
0.1, reacted tetra- kinds of elements of Si, S, Ca, Fe be TOC calculate base indispensable element, therefore YY2 well TOC computation models using Si, S,
Ca, Fe element, its specific formula are：
TOC=-3.74848+0.11582*Si+1.944*S+0.24225*Ca-0.66147*Fe；
Wherein, the percentage value of Si, S, Ca, Fe measured by sample XRF, %；
Fig. 1 is shown in the contrast of TOC and rock pyrolysis well logging TOC after calculating, and YY2 wells XRF elements are fitted as can be seen from Fig.
Although as a result and former TOC has some deviations, overall trend is consistent substantially, and computation model can meet that shale TOC is evaluated
Demand, do not influence evaluation reliability.
Embodiment 2
The present invention includes following order step：
Step 1. grasps the stratum characteristic information in the region of shale gas reservoir work area in a manner of well logging and/or experimental analysis,
Using the stratum characteristic information grasped according to shale gas reservoir work area region depth as data preparation scale, carry out data it is whole
Reason；
Step 2. carries out mud logging operation to the work area region of shale gas reservoir, and the mud logging operation is with XRF element well loggings with brill
Mode is realized, the rock composition information in the region of shale gas reservoir work area is obtained, by the rock composition information obtained according to work area
Scale of the depth in region as data preparation, carry out data preparation；
Using the work area regional depth of shale gas reservoir as scale, by the rock composition information obtained and the stratum grasped
Characteristic information carries out the comparison of corresponding depth；In the comparison of corresponding depth, by the data that distinct methods are obtained have not
With measurement spacing, depth disunity, it is then desired to which the rock composition information obtained is entered at row interpolation according to corresponding depth
Reason, it so completely make use of the stratum characteristic information for log data-grasped, but the need of the rock composition information to being obtained
Artificial interpolation is carried out, so under uniform depth scale, the two data message is compared, makes grasped stratum special
The playback for the rock composition information realization uniform depth that reference ceases and obtained is handled, and forms the combined data of uniform depth scale
Collection；
Step 3. is concentrated in combined data, and sensitive elements are selected for the shale TOC parameters for needing to obtain, sensitivity member
Element comprises at least but is not limited to tetra- kinds of elements of Si, S, Ca and Fe；The selection of sensitive elements is, first by each element with Hierarchical Clustering
Mode by interdependence classify, then by these classification elements selected in the way of principal component analysis, screening obtain it is final,
Corresponding sensitive elements；
Step 4. carries out data fitting with multiple linear regression analysis method, establishes polynary between element and shale TOC parameters
Transformation model is returned, the transformation model is as follows：
TOC=β0+β1*X1+β2*X2+…+βk*Xk；
In formula, TOC is shale TOC parameters (the total organic carbon parameter i.e. in shale)；
β0、β1、β2…βkFor regression coefficient；
X1、X2…XkThe content of respectively different elements；
Shale TOC parameters are obtained by above-mentioned transformation model.
Although the present embodiment can be based on XRF elements well logging and obtain shale TOC parameters with brill, due to the upper page in longitudinal direction
The anisotropism of rock is stronger, and the rock composition information obtained is carried out into interpolation processing according to corresponding depth in step 2, it is difficult to
Reliable interpolation algorithm is found, the reliability of interpolation cannot be verified, thus the optimal technical scheme of the present embodiment non-invention.
Various embodiments above is only to illustrate the present invention, rather than its limitations；Although with reference to the various embodiments described above to this hair
It is bright to be described in detail, it will be understood by those within the art that：The present invention still can be to the various embodiments described above
In concrete technical scheme modify, or to which part technical characteristic carry out equivalent substitution, and these modification or replace
Change, the essence of appropriate technical solution is departed from the spirit and scope of the present invention.
Claims (4)
1. a kind of method based on XRF elements well logging with acquisition shale TOC parameters in brill, comprise the following steps：
Step 1. grasps the stratum characteristic information in the region of work area in a manner of well logging and/or experimental analysis；
Step 2. obtains the rock composition information in the region of work area, the rock composition information that will be obtained by XRF elements well logging
The comparison of corresponding stratigraphic horizon and depth is carried out with the stratum characteristic information grasped, makes grasped stratum characteristic information and institute
The playback of the unified layer position of the rock composition information realization of acquisition and depth is handled, and forms the combined data of uniform depth scale
Collection；
Step 3. is concentrated in combined data, and sensitive elements are selected for the shale TOC parameters for needing to obtain；
Step 4. carries out data fitting, the multiple regression established between element and shale TOC parameters with multiple linear regression analysis method
Transformation model, the transformation model are：
TOC=β0+β1*X1+β2*X2+…+βk*Xk；
In formula, β0、β1、β2…βkFor regression coefficient；
X1、X2…XkThe content of respectively different elements；
Shale TOC parameters are obtained by transformation model.
2. according to claim 1 based on XRF elements well logging with the method that shale TOC parameters are obtained in brill, it is characterised in that
The comparison of rock composition information stratigraphic horizon corresponding with stratum characteristic information and depth is the rock that will be obtained in step 2
Composition information by corresponding depth interpolation in the stratum characteristic information grasped, or, the stratum characteristic information grasped is pressed
Corresponding depth vacuates to be compared with the rock composition information obtained afterwards.
3. according to claim 1 based on XRF elements well logging with the method that shale TOC parameters are obtained in brill, it is characterised in that
Sensitive elements selection in step 3 is that first each element is classified in a manner of Hierarchical Clustering by interdependence, then by these points
The element of class selects in the way of principal component analysis, and screening obtains corresponding sensitive elements.
4. existed according to claim 1 or 3 based on XRF elements well logging with the method that shale TOC parameters are obtained in brill, its feature
In the sensitive elements comprise at least tetra- kinds of elements of Si, S, Ca and Fe.
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| CN111352162A (en) * | 2020-03-19 | 2020-06-30 | 中国石油天然气集团有限公司 | Shale stratum element phase dividing method and element phase evaluation method |
| CN112065375A (en) * | 2019-05-21 | 2020-12-11 | 中国石油化工股份有限公司 | Method and system for calculating gas content of shale stratum |
| CN112147711A (en) * | 2019-06-28 | 2020-12-29 | 中国石油化工股份有限公司 | Method and system for rapidly acquiring marine shale total organic carbon in field |
| CN112343574A (en) * | 2020-09-28 | 2021-02-09 | 中国石油化工集团有限公司 | Porosity logging calculation method for corrosion type reservoir |
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| CN113803062A (en) * | 2021-10-20 | 2021-12-17 | 中国石油化工股份有限公司 | Method for determining continental facies shale horizon attribution |
| CN114076776A (en) * | 2020-08-12 | 2022-02-22 | 中国石油化工股份有限公司 | Method for predicting organic carbon content of shale and application thereof |
| CN114427451A (en) * | 2020-09-11 | 2022-05-03 | 中国石油化工股份有限公司 | Method for obtaining shale reservoir static parameters based on while-drilling data |
| CN112343588B (en) * | 2020-09-28 | 2024-06-21 | 中国石油化工集团有限公司 | Method for acquiring rock poisson ratio in logging while drilling based on XRF element |
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| CN112065375B (en) * | 2019-05-21 | 2024-01-30 | 中国石油化工股份有限公司 | Method and system for calculating gas content of shale stratum |
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| CN113775329A (en) * | 2020-06-09 | 2021-12-10 | 中国石油化工股份有限公司 | Method and system for acquiring deep carbonate rock mechanical parameters |
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| CN114427451A (en) * | 2020-09-11 | 2022-05-03 | 中国石油化工股份有限公司 | Method for obtaining shale reservoir static parameters based on while-drilling data |
| CN112343574A (en) * | 2020-09-28 | 2021-02-09 | 中国石油化工集团有限公司 | Porosity logging calculation method for corrosion type reservoir |
| CN112343574B (en) * | 2020-09-28 | 2024-04-16 | 中国石油化工集团有限公司 | Method for calculating porosity logging of corrosion type reservoir |
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| CN113803062A (en) * | 2021-10-20 | 2021-12-17 | 中国石油化工股份有限公司 | Method for determining continental facies shale horizon attribution |
| CN113803062B (en) * | 2021-10-20 | 2024-02-20 | 中国石油化工股份有限公司 | Method for determining land mud shale horizon attribution |
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