CN108627878A - The crack identification method and system of tight sand formation - Google Patents
The crack identification method and system of tight sand formation Download PDFInfo
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Abstract
Disclose a kind of crack identification method and system of tight sand formation.Including：Based on deep investigation induction log data and medium investigation induction log data, deep induction response and middle induced response value are obtained, obtains deep induction response average value and middle induced response average value；Based on deep induction response, middle induced response value, deep induction response average value and middle induced response average value, the first regression coefficient is obtained；Based on the first regression coefficient, deep induction response average value and middle induced response average value, the second regression coefficient is obtained；Based on deep induction response, middle induced response value, deep induction response average value, the first regression coefficient and the second regression coefficient, double induction coefficients of variation are obtained；Given threshold compares threshold value and double induction coefficients of variation, identifies crack.The present invention effectively identifies high angle fracture in tight sand, is not influenced by variations such as formation lithology, physical property, oiliness by calculating double induction coefficients of variation with threshold comparison.
Description
Technical field
The present invention relates to oil exploration and development fields, more particularly, to a kind of crack identification side of tight sand formation
Method and system.
Background technology
At present for logging technique, imaging logging is crack identification evaluation best bet, but this method is expensive and takes
When, it is only used in some importance prospect pit, conventional logging is most widely used in petroleum exploration and development, utilizes conventional logging song
Line identifies crack also in reservoir has had the history of decades, well logging scholar to be built using the various logging response characters in crack
Go out a series of most basic crack identification parameters, such as three porosity ratio method, secondary porosity index method, hole diameter relative anomalies
Method, resistivity invasion correction ratiometer method etc., these methods are more applicable in the high resistants such as carbonate rock, igneous rock compacted zone, obtain
Good recognition effect.A kind of Zeng Lianbo etc. (horizontal well crack identification method, CN201510729546.5) reconstruct is split
Fractal index curve, FRACTURE CHARACTERISTICS exponential curve and the response intensity in stratum brittleness index curve magnification crack are stitched, is eliminated non-
Crack influences, and extracts crack information comprehensively from well-log information, accurately identifies horizontal well surrounding formation crack；Li Hongbing etc. (knows
The method of other reservoir micro-fractures, CN201510353677.8) according to optimal soft hole volume percent porosity, identify reservoir fine fisssure
Seam；Appoint outstanding person equal (a kind of method of tight sandstone reservoir crack identification, CN201410601495.3) to pass through and analyzes the survey of individual well crack
Relationship between well response characteristic parameters establishes the relevant feature parameters of individual well crack identification, and then uses weighted arithmetic mean
Method builds crack comprehensive evaluation model parameter --- crack composite index, realizes in individual well crack tight sandstone reservoir to be identified
Section identifies crack by analyzing the size of crack composite index；Bao Dandan etc. (a kind of recognition methods of buried hill fissure and system,
CN201410586454.1) on the basis of core experiment, verification is combined using al-lateral resistivity well logging and acoustic travel time logging
And determine fracture intensity；Wei repair equality (Reservoir Fracture recognition methods and imaging logging Reservoir Fracture recognition methods,
CN201410130972.2) in the dried layer of reservoir to be analyzed, the sound wave hole in other intervals compare porosity curve combination
It writes music line and density porosity curve, based on comparative result according to the types of fractures for presetting fractured model and determining corresponding interval；Cao
Just (method of glutenite crack identification, CN201310610148.2) is waited to determine region according to seismic data, regional background data
Tectonic stress；Build intensity indicative curve；Crack is identified according to intensity indicated value；Determine FRACTURE CHARACTERISTICS parameter；Poplar
Snow etc. (carrying out crack identification, Jilin geology, 2013 using Conventional Logs) is with provincialism the relationship between lithology and logging from regarding sound wave hole
The actual measurement resistivity curve for spending the resistivity and stratum that find out has certain difference, can be to splitting in rock stratum by this species diversity
Seam is identified；Xu Junyu (city group crack identification, Xinjiang petroleum geology, 2012 are sought in ten room oil field of Song-liao basin) summarizes research area
Crack bilaterally on microspheric focused log curve and on mutative scale fractal curve 3 kinds of different shapes and its reflected
The property in crack, for microspheric focused resistivity value around the fluctuation up and down of bilaterally value, the crack identified is mainly low angle
Crack；Bilaterally with microspheric focused resistivity value positive variance, the crack identified is mainly high angle fracture；Wang Cuili etc.
(Zhen-Jing area Chang-8 oil formation group FRACTURE CHARACTERISTICS and crack identification method, 2011) proposes to introduce probabilistic neural network (PNN) method pair
It is preferred that 35 samples gone out are trained, crack identification model is established；Zhao Yong just waits (the southwestern Ordos Basin Zhenjing oilfield
Extension group tight sandstone reservoir fracture logging identification, modern geology, 2013) it proposes based on hole diameter, resistivity, density, sound wave etc.
Logging Curves calculate 8 crack instruction parameters, then construct a crack synthesis identification ginseng using this 8 parameters
Number.However thin interbed is developed in tight sand formation, and opposite low-resistance, matrix pores are larger, and based on high angle fracture, split
Seam response is faint, although above-mentioned identification technology obtains good recognition effect, not for the response of tight sand all slits
It is all applicable in, and commonly uses dual induction log in tight sand formation, and in the high resistants tight formation such as carbonate rock, igneous rock
The dual laterolog of middle use differs greatly in measuring principle, and the crack identification precision further resulted in tight sand formation is inclined
It is low.Therefore, it is necessary to develop a kind of crack identification method and system of tight sand formation.
The information for being disclosed in background of invention part is merely intended to deepen the reason of the general background technology to the present invention
Solution, and it is known to those skilled in the art existing to be not construed as recognizing or imply that the information is constituted in any form
Technology.
Invention content
The present invention proposes a kind of crack identification method and system of tight sand formation, can be by calculating double inductions
Coefficient of variation, and and threshold comparison, high angle fracture in effectively identification tight sand is realized, not by formation lithology, physical property, oil-containing
Property etc. variations influence.
According to an aspect of the invention, it is proposed that the crack identification method of tight sand formation a kind of.The method can be with
Including：Based on deep investigation induction log data and medium investigation induction log data, deep induction response and middle induced response value are obtained respectively, into
And obtain deep induction response average value and middle induced response average value；Based on the deep induction response, the middle induced response
Value, deep induction response average value and the middle induced response average value, obtain the first regression coefficient；Based on described first time
Return coefficient, deep induction response average value and the middle induced response average value, obtains the second regression coefficient；Based on the depth
Induced response value, the middle induced response value, deep induction response average value, first regression coefficient and described second time
Return coefficient, obtains double induction coefficients of variation；The double induction coefficient of variation threshold values of setting, double induction coefficient of variation threshold values with
Double induction coefficients of variation, to identify crack.
Preferably, first regression coefficient is：
Wherein, b1Indicate the first regression coefficient, miIndicate the middle induced response value of ith sample point, diIt indicates to adopt for i-th
The deep induction response of sampling point, n indicate double induction sampled point quantity,Indicate that deep induction responds average value,Incude in expression
Average value is responded, i indicates sampled point serial number.
Preferably, second regression coefficient is：
Wherein, b0Indicate the second regression coefficient.
Preferably, double induction coefficients of variation are：
Wherein, RcorIndicate double induction coefficients of variation.
According to another aspect of the invention, it is proposed that the crack identification system of tight sand formation a kind of, the system can
To include：Pretreatment unit, for based on deep investigation induction log data and medium investigation induction log data, obtaining deep induction response respectively
With middle induced response value, and then deep induction response average value and middle induced response average value are obtained；
First regression coefficient computing unit, for based on the deep induction response, the middle induced response value, the depth
Induced response average value and the middle induced response average value, obtain the first regression coefficient；
Second regression coefficient computing unit, for based on first regression coefficient, the deep induction response average value with
The middle induced response average value obtains the second regression coefficient；
Double induction coefficient of variation computing units, for based on the deep induction response, the middle induced response value, described
Deep induction responds average value, first regression coefficient and second regression coefficient, obtains double induction coefficients of variation；
Recognition unit, for setting double induction coefficient of variation threshold values, double induction coefficient of variation threshold values with it is described
Double induction coefficients of variation, to identify crack.
Preferably, first regression coefficient is：
Wherein, b1Indicate the first regression coefficient, miIndicate the middle induced response value of ith sample point, diIt indicates to adopt for i-th
The deep induction response of sampling point, n indicate double induction sampled point quantity,Indicate that deep induction responds average value,Incude in expression
Average value is responded, i indicates sampled point serial number.
Preferably, second regression coefficient is：
Wherein, b0Indicate the second regression coefficient.
Preferably, double induction coefficients of variation are：
Wherein, RcorIndicate double induction coefficients of variation.
Advantage is：By the double induction coefficients of variation of calculating, and and threshold comparison, it realizes and effectively identifies fine and close sand
High angle fracture in rock；It is adaptable, there is good theoretical foundation, it is multiple to can be widely applied to tight sand, shale oil gas etc.
Miscellaneous reservoir, and do not influenced by variations such as lithology, physical property, oiliness；Strong operability, relational expression is clear between each parameter, is convenient for
It obtains, and there is stringent mathematic(al) representation, be easy to computer programming calculation.
Methods and apparatus of the present invention has other characteristics and advantages, these characteristics and advantages attached from what is be incorporated herein
It will be apparent in figure and subsequent specific implementation mode, or will be in the attached drawing being incorporated herein and subsequent specific reality
It applies in mode and is stated in detail, the drawings and the detailed description together serve to explain specific principles of the invention.
Description of the drawings
Exemplary embodiment of the invention is described in more detail in conjunction with the accompanying drawings, it is of the invention above-mentioned and its
Its purpose, feature and advantage will be apparent, wherein in exemplary embodiment of the invention, identical reference label
Typically represent same parts.
Fig. 1 shows the flow chart of the step of crack identification method of tight sand formation according to the present invention.
Fig. 2 shows the signals that double induction coefficients of variation according to embodiment of the present invention identify crack achievement
Figure.
Specific implementation mode
The present invention is more fully described below with reference to accompanying drawings.Although showing the preferred implementation side of the present invention in attached drawing
Formula, however, it is to be appreciated that may be realized in various forms the present invention without should be limited by embodiments set forth herein.Phase
Instead, these embodiments are provided so that the present invention is more thorough and complete, and can be by the scope of the present invention completely
It is communicated to those skilled in the art.
Fig. 1 shows the flow chart of the step of crack identification method of tight sand formation according to the present invention.
In this embodiment, the crack identification method of tight sand formation according to the present invention may include：Step
101, based on deep investigation induction log data and medium investigation induction log data, deep induction response and middle induced response value are obtained respectively, into
And obtain deep induction response average value and middle induced response average value；Step 102, deep induction response, middle induced response are based on
Value, deep induction response average value and middle induced response average value, obtain the first regression coefficient；Step 103, it is based on first and returns system
Number, deep induction response average value and middle induced response average value, obtain the second regression coefficient；Step 104, deep induction is based on to respond
Value, middle induced response value, deep induction response average value, the first regression coefficient and the second regression coefficient, obtain double induction difference systems
Number；And step 105, double induction coefficient of variation threshold values, relatively more double induction coefficient of variation threshold values and double induction coefficients of variation are set,
To identify crack.
The embodiment effectively identifies in tight sand by the double induction coefficients of variation of calculating, and with threshold comparison, realization
High angle fracture is not influenced by variations such as formation lithology, physical property, oiliness.
The following detailed description of the specific steps of the crack identification method of tight sand formation according to the present invention.
In one example, deep investigation induction log data and medium investigation induction log data are based on, obtain deep induction response respectively
With middle induced response value, and then deep induction response average value and middle induced response average value are obtained.
In one example, deep induction response, middle induced response value, deep induction response average value is based on to ring with middle induction
Average value is answered, the first regression coefficient is obtained.
In one example, the first regression coefficient is：
Wherein, b1Indicate the first regression coefficient, miIndicate the middle induced response value of ith sample point, diIt indicates to adopt for i-th
The deep induction response of sampling point, n indicate double induction sampled point quantity,Indicate that deep induction responds average value,Incude in expression and rings
Average value, i is answered to indicate sampled point serial number.
Specifically, since deep, the middle induction vertical geometrical factor in dual induction log differs greatly, deep induction longitudinal direction geometry
For the factor in the distribution symmetrical above and below of record point, lateral geometrical factor is wider slow, and middle induction vertical geometrical factor is non-up and down in record point
Symmetrically, lateral geometrical factor narrows closer near wellbore zone steepening, and for conventional reservoir, the two passes through Deconvolution Correction, phase
It is high like degree, and the presence of high angle fracture, causing near wellbore zone, there are strong anisotropism, and deep investigation induction log is influenced
Less, and due to the asymmetry of middle induction vertical geometrical factor, cause middle induction Deconvolution Correction deficiency that tooth feature is presented,
So that double induction similarity degrees reduce.Therefore, deep investigation induction log data and medium investigation induction log data can be based on, are obtained respectively
Deep induction response and middle induced response value are obtained, and then calculates separately deep induction response average value and middle induced response average value,
Deep induction response, middle induced response value, deep induction response average value and middle induced response average value are substituted into formula (1), meter
Calculation acquires the first regression coefficient.
In one example, it is based on the first regression coefficient, deep induction response average value and middle induced response average value, is obtained
Second regression coefficient.
In one example, the second regression coefficient is：
Wherein, b0Indicate the second regression coefficient.
Specifically, the first regression coefficient, deep induction response average value are substituted into formula (2) with middle induced response average value
In, calculating acquires the second regression coefficient.
In one example, deep induction response, middle induced response value, deep induction response average value, the first recurrence are based on
Coefficient and the second regression coefficient obtain double induction coefficients of variation.
In one example, double induction coefficients of variation are：
Wherein, RcorIndicate double induction coefficients of variation.
In one example, the double induction coefficient of variation threshold values of setting, relatively more double induction coefficient of variation threshold values and double inductions are poor
Different coefficient, to identify crack.
Specifically, in general, double induction coefficients of variation of the tight sand formation of fracture development to be apparently higher than nearby do not send out
The tight sand formation in crack is educated, can be demarcated by using data such as rock core, Electrical imagings to set double induction coefficient of variation thresholds
Value, relatively more double induction coefficient of variation threshold values identify crack with double induction coefficients of variation.By deep induction response, middle induction
Response, deep induction response average value, the first regression coefficient are substituted into the second regression coefficient in formula (3), and calculating acquires double senses
Coefficient of variation is answered, double induction coefficient of variation threshold values, relatively more double induction coefficient of variation threshold values and double induction coefficients of variation are set, if double
Incude coefficient of variation and be more than double induction coefficient of variation threshold values, then identifies that the position is crack.
Using example
A concrete application example is given below in the scheme and its effect of embodiment of the present invention for ease of understanding.Ability
Field technique personnel should be understood that the example only for the purposes of understanding that the present invention, any detail are not intended in any way
The limitation present invention.
Certain oil field river rising in Ningxia and flowing into central Shaanxi river 25 well length 81 2Section 1340-1356m develops a plurality of high angle fracture crack, microcrack, and crude oil edge is split
Seam face is enriched with.
Fig. 2 shows the signals that double induction coefficients of variation according to embodiment of the present invention identify crack achievement
Figure.
The a length of 1m of window is set, step-length is the well logging sampling interval, is based on deep investigation induction log data and medium investigation induction log data, point
Not Huo get deep induction response and middle induced response value, and then it is average with middle induced response to calculate separately deep induction response average value
Deep induction response, middle induced response value, deep induction response average value are substituted into formula (1) by value with middle induced response average value,
Calculating acquires the first regression coefficient；First regression coefficient, deep induction response average value are substituted into public affairs with middle induced response average value
In formula (2), calculating acquires the second regression coefficient.By deep induction response, middle induced response value, deep induction response average value, the
One regression coefficient is substituted into the second regression coefficient in formula (3), and calculating acquires double induction coefficients of variation, sets double induction difference systems
Number threshold value is 0.25, relatively more double induction coefficient of variation threshold values and double induction coefficients of variation, if double induction coefficients of variation are more than 0.25,
Then identify that the position is crack, as seen from Figure 2 in fracture development section, double induction coefficients of variation, therefore can be with more than 0.25
Effectively identify the well crack.
In conclusion this method is by calculating double induction coefficients of variation, and and threshold comparison, realize the fine and close sand of effectively identification
High angle fracture in rock；It is adaptable, there is good theoretical foundation, it is multiple to can be widely applied to tight sand, shale oil gas etc.
Miscellaneous reservoir, and do not influenced by variations such as lithology, physical property, oiliness；Strong operability, relational expression is clear between each parameter, is convenient for
It obtains, and there is stringent mathematic(al) representation, be easy to computer programming calculation.
It will be understood by those skilled in the art that above to the purpose of the description of embodiments of the present invention only for illustratively
The advantageous effect for illustrating embodiments of the present invention is not intended to embodiments of the present invention being limited to given any show
Example.
According to the embodiment of the present invention, a kind of crack identification system of tight sand formation is provided, the system can
To include：Pretreatment unit, for based on deep investigation induction log data and medium investigation induction log data, obtaining deep induction response respectively
With middle induced response value, and then deep induction response average value and middle induced response average value are obtained；First regression coefficient calculates single
Member, for based on deep induction response, middle induced response value, deep induction response average value and middle induced response average value, obtaining
First regression coefficient；Second regression coefficient computing unit, for based on the first regression coefficient, deep induction response average value and middle sense
Average value should be responded, the second regression coefficient is obtained；Double induction coefficient of variation computing units, for based on deep induction response, in
Induced response value, deep induction response average value, the first regression coefficient and the second regression coefficient, obtain double induction coefficients of variation；Know
Other unit, for setting double induction coefficient of variation threshold values, relatively more double induction coefficient of variation threshold values and double induction coefficients of variation, to
Identify crack.
The embodiment effectively identifies in tight sand by the double induction coefficients of variation of calculating, and with threshold comparison, realization
High angle fracture is not influenced by variations such as formation lithology, physical property, oiliness.
In one example, the first regression coefficient is：
Wherein, b1Indicate the first regression coefficient, miIndicate the middle induced response value of ith sample point, diIt indicates to adopt for i-th
The deep induction response of sampling point, n indicate double induction sampled point quantity,Indicate that deep induction responds average value,Incude in expression and rings
Average value, i is answered to indicate sampled point serial number.
In one example, the second regression coefficient is：
Wherein, b0Indicate the second regression coefficient.
In one example, double induction coefficients of variation are：
Wherein, RcorIndicate double induction coefficients of variation.
Therefore, this system effectively identifies high angle in tight sand by calculating double induction coefficients of variation with threshold comparison
Crack is not influenced by variations such as formation lithology, physical property, oiliness.
It will be understood by those skilled in the art that above to the purpose of the description of embodiments of the present invention only for illustratively
The advantageous effect for illustrating embodiments of the present invention is not intended to embodiments of the present invention being limited to given any show
Example.
The embodiments of the present invention are described above, above description is exemplary, and non-exclusive, and
It is also not necessarily limited to disclosed each embodiment.It is right without departing from the scope and spirit of illustrated each embodiment
Many modifications and changes will be apparent from for those skilled in the art.The choosing of term used herein
It selects, it is intended to best explain the principle, practical application or the improvement to the technology in market of each embodiment, or make this technology
Other those of ordinary skill in field can understand each embodiment disclosed herein.
Claims (8)
1. a kind of crack identification method of tight sand formation, including：
Based on deep investigation induction log data and medium investigation induction log data, deep induction response and middle induced response value are obtained respectively, into
And obtain deep induction response average value and middle induced response average value；
It is rung based on the deep induction response, the middle induced response value, deep induction response average value and the middle induction
Average value is answered, the first regression coefficient is obtained；
Based on first regression coefficient, deep induction response average value and the middle induced response average value, second is obtained
Regression coefficient；
System is returned based on the deep induction response, the middle induced response value, deep induction response average value, described first
Number and second regression coefficient obtain double induction coefficients of variation；
The double induction coefficient of variation threshold values of setting, double induction coefficient of variation threshold values and double induction coefficients of variation, from
And identify crack.
2. the crack identification method of tight sand formation according to claim 1, wherein first regression coefficient is：
Wherein, b1Indicate the first regression coefficient, miIndicate the middle induced response value of ith sample point, diIndicate ith sample point
Deep induction response, n indicates double induction sampled point quantity,Indicate that deep induction responds average value,Induced response is flat in expression
Mean value, i indicate sampled point serial number.
3. the crack identification method of tight sand formation according to claim 2, wherein second regression coefficient is：
Wherein, b0Indicate the second regression coefficient.
4. the crack identification method of tight sand formation according to claim 3, wherein double induction coefficients of variation
For：
Wherein, RcorIndicate double induction coefficients of variation.
5. a kind of crack identification system of tight sand formation, including：
Pretreatment unit, for based on deep investigation induction log data and medium investigation induction log data, obtain respectively deep induction response with
Middle induced response value, and then obtain deep induction response average value and middle induced response average value；
First regression coefficient computing unit, for based on the deep induction response, the middle induced response value, the deep induction
Average value and the middle induced response average value are responded, the first regression coefficient is obtained；
Second regression coefficient computing unit, for based on first regression coefficient, the deep induction response average value with it is described
Middle induced response average value obtains the second regression coefficient；
Double induction coefficient of variation computing units, for being based on the deep induction response, the middle induced response value, described feeling deeply
Average value, first regression coefficient and second regression coefficient should be responded, double induction coefficients of variation are obtained；
Recognition unit, for setting double induction coefficient of variation threshold values, double induction coefficient of variation threshold values and double senses
Coefficient of variation is answered, to identify crack.
6. the crack identification system of tight sand formation according to claim 5, first regression coefficient are：
Wherein, b1Indicate the first regression coefficient, miIndicate the middle induced response value of ith sample point, diIndicate ith sample point
Deep induction response, n indicates double induction sampled point quantity,Indicate that deep induction responds average value,Induced response is flat in expression
Mean value, i indicate sampled point serial number.
7. the crack identification system of tight sand formation according to claim 6, wherein wherein, described second returns system
Number is：
Wherein, b0Indicate the second regression coefficient.
8. the crack identification system of tight sand formation according to claim 7, wherein double induction coefficients of variation
For：
Wherein, RcorIndicate double induction coefficients of variation.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113138107A (en) * | 2021-04-15 | 2021-07-20 | 东北石油大学 | Rock brittleness evaluation method based on while-drilling rock debris logging information |
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| CN113138107A (en) * | 2021-04-15 | 2021-07-20 | 东北石油大学 | Rock brittleness evaluation method based on while-drilling rock debris logging information |
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| CN108627878B (en) | 2019-12-13 |
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