CN106803207A - A kind of method for quantitatively evaluating and device for oil field oil-containing gas - Google Patents
A kind of method for quantitatively evaluating and device for oil field oil-containing gas Download PDFInfo
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Abstract
Provided by the present invention for the method for quantitatively evaluating of oil field oil-containing gas, it is related to oilfield prospecting developing technology, the method according to the oil-source condition in the oil field, transport poly- condition, reservoir conditions, trap condition, preservation condition and complementary conditions, determine buried depth, porosity, relative physical property, permeability, top separator thickness and the fault gouge ratio SGR indexes in the oil field, and then the buried depth in the oil field, porosity, relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes are brought into oily probability regression modelIn obtain the oily probability in the oil field, realize the quantum chemical method of oil gas field oily probability, improve the dependable with function of oil field oil-containing gas evaluation method, meet the demand of Oil/gas Well fine granularing scalability.
Description
Technical field
The present invention relates to oilfield prospecting developing technology, more particularly to a kind of quantitatively evaluating side for oil field oil-containing gas
Method and device.
Background technology
Evaluation of oil and gas bearing property is the important content of oil-gas geology research, and it can be straight by effective quantization signifying oil-gas possibility
Reflection petroleum distribution situation is seen, in-depth Hydrocarbon Formation Reservoirs understanding conveniently instructs decision and deployment, weight is increasingly subject in oil-gas exploration
Depending on.Characterized currently for evaluation of oil and gas bearing property and petroleum distribution and carried out a large amount of correlative studys, but still suffer from some problems and not
Foot；The evaluation method of use is based on geologic risk probabilistic method, image factoring etc. and relies primarily on expertise and determine mostly
Evaluation index and marking, often subjective, the combination of shortage and actual exploration data, evaluation model is relatively simple, reliable
And practicality is poor.Therefore, exigence provides a kind of demand that disclosure satisfy that fine granularing scalability, and dependable with function is stronger
Oil field oil-containing gas evaluation method.
The content of the invention
The present invention provides a kind of method for quantitatively evaluating and device for oil field oil-containing gas, it is intended to meet fine granularing scalability
Demand, improves the dependable with function that oil field oil-containing gas is evaluated.
On the one hand, the present invention provides a kind of method for quantitatively evaluating for oil field oil-containing gas, and methods described includes：
Determine the oil-source condition in the oil field, transport poly- condition, reservoir conditions, trap condition, preservation condition and complementary conditions；
Oil-source condition, the poly- condition of fortune, reservoir conditions, trap condition, preservation condition and complementary conditions according to the oil field,
Determine that the buried depth in the oil field, porosity, relative physical property, permeability, top separator thickness and fault gouge ratio SGR refer to
Number；
The oily probability P in the oil field is determined according to oily probability regression model, wherein, the oily probability is returned
The model is returned to be：
In formula, x1It is the buried depth in the oil field, x2It is the porosity in the oil field, x3It is the permeability in the oil field,
x4It is the relative physical property in the oil field, x5It is the top separator thickness in the oil field, x6It is the fault gouge ratio SGR in the oil field
Index.
Optionally, the oil-source condition for determining the oil field, the poly- condition of fortune, reservoir conditions, trap condition, preservation condition
And complementary conditions, including：
The overall geological structure in the oil field is obtained using method of seismic exploration；
According to the overall geological structure, determine the oil-source condition in the oil field, transport poly- condition, reservoir conditions, trap bar
Part, preservation condition and complementary conditions.
Optionally, oil-source condition, the poly- condition of fortune, reservoir conditions, trap condition, the preservation condition according to the oil field
And complementary conditions, determine buried depth, porosity, relative physical property, permeability, top separator thickness and the fault gouge in the oil field
Ratio SGR indexes, including：
Oil-source condition, the poly- condition of fortune, reservoir conditions, trap condition, preservation condition and complementary conditions according to the oil field,
Determine the capture oil gas ability in the oil field, preserve oil gas ability and preserve oil gas ability；
According to the capture oil gas ability, it is described preserve oil gas ability and the preservation oil gas ability, choose the oil field
Buried depth, porosity, relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes as the oil field
The quantitatively evaluating factor of oil-gas possibility；
The overall geological structure in the oil field obtained according to method of seismic exploration, determines buried depth, the hole in the oil field
The concrete numerical value of porosity, relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes.
Optionally, the oily probability P that the oil field is determined according to oily probability regression model, including：
According to Logistic regression models by whether the classified variable of oily is converted to probability of happening problem, and by
Logit is converted and maximal possibility estimation realizes that the nonlinear fitting of relation between destination probability and independent variable is returned, and obtains oil-containing
Spirit rate regression model, wherein, oily probability regression model is：
By the buried depth in the oil field, porosity, relative physical property, permeability, top separator thickness and fault gouge ratio
The concrete numerical value of SGR indexes brings the oily probability regression model into, obtains the oily probability P in the oil field.
Optionally, it is described according to Logistic regression models by whether the classified variable of oily is converted to probability of happening asks
Topic, and realize that the nonlinear fitting of relation between destination probability and independent variable is returned by logit conversion and maximal possibility estimation,
Oily probability regression model is obtained, including：
Event is designated as 1,0 is not designated as, event occurrence condition probability is p, and probability of happening is not 1-p, and P is entered
Row logit is converted, and obtains regression equation：
Wherein, x1,x2,…,xmIt is the m independent variable of influence dependent variable Y, β0, β1, β2..., βmIt is logistic regression to be estimated
Coefficient, β0It is constant term；
The likelihood function of its joint probability of happening is constructed according to known sampleUsing maximum
Principle of probability selects the estimates of parameters that likelihood function can be made to reach maximum to determine that each to be estimated is patrolled by mathematical iterations computing
Collect regression coefficient；
According to each logistic regression coefficient to be estimated and the regression equation, the oily probability regression model is obtained.
On the other hand, the present invention also provides a kind of quantitatively evaluating device for oil field oil-containing gas, the quantitatively evaluating
Device includes：
First determining module, for determining the oil-source condition in the oil field, transporting poly- condition, reservoir conditions, trap condition, guarantor
Deposit condition and complementary conditions；
Second determining module, for the oil-source condition according to the oil field, transports poly- condition, reservoir conditions, trap condition, guarantor
Deposit condition and complementary conditions, determine the buried depth in the oil field, porosity, relative physical property, permeability, top separator thickness and
Fault gouge ratio SGR indexes；
3rd determining module, the oily probability P for determining the oil field according to oily probability regression model, its
In, the oily probability regression model is：
In formula, x1It is the buried depth in the oil field, x2It is the porosity in the oil field, x3It is the permeability in the oil field,
x4It is the relative physical property in the oil field, x5It is the top separator thickness in the oil field, x6It is the fault gouge ratio SGR in the oil field
Index.
Optionally, first determining module includes：
First acquisition submodule, Ying Yu obtains the overall geological structure in the oil field using method of seismic exploration；
First determination sub-module, for according to the overall geological structure, determining the oil-source condition in the oil field, transporting poly- bar
Part, reservoir conditions, trap condition, preservation condition and complementary conditions.
Optionally, the second described determining module specifically for：
Oil-source condition, the poly- condition of fortune, reservoir conditions, trap condition, preservation condition and complementary conditions according to the oil field,
Determine the capture oil gas ability in the oil field, preserve oil gas ability and preserve oil gas ability；
According to the capture oil gas ability, it is described preserve oil gas ability and the preservation oil gas ability, choose the oil field
Buried depth, porosity, relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes as the oil field
The quantitatively evaluating factor of oil-gas possibility；
The overall geological structure in the oil field obtained according to method of seismic exploration, determines buried depth, the hole in the oil field
The concrete numerical value of porosity, relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes.
Optionally, the 3rd determining module includes：
3rd determination sub-module, for according to Logistic regression models by whether the classified variable of oily is converted to hair
Raw probability problem, and realize the non-linear of relation between destination probability and independent variable by logit conversion and maximal possibility estimation
Fitting is returned, and obtains oily probability regression model, wherein, oily probability regression model is：
3rd calculating sub module, for by the buried depth in the oil field, porosity, relative physical property, permeability, top every
The concrete numerical value of thickness degree and fault gouge ratio SGR indexes brings the oily probability regression model into, obtains the oil field
Oily probability P.
Optionally, the 3rd determination sub-module specifically for：
Event is designated as 1,0 is not designated as, event occurrence condition probability is p, and probability of happening is not 1-p, and P is entered
Row logit is converted, and obtains regression equation：
Wherein, x1,x2,…,xmIt is the m independent variable of influence dependent variable Y, β0, β1, β2..., βmIt is logistic regression to be estimated
Coefficient, β0It is constant term；
The likelihood function of its joint probability of happening is constructed according to known sampleUsing maximum
Principle of probability selects the estimates of parameters that likelihood function can be made to reach maximum to determine that each to be estimated is patrolled by mathematical iterations computing
Collect regression coefficient；
According to each logistic regression coefficient to be estimated and the regression equation, the oily probability regression model is obtained.
Method for quantitatively evaluating for oil field oil-containing gas provided in an embodiment of the present invention, the oil sources bar according to the oil field
Part, transport poly- condition, reservoir conditions, trap condition, preservation condition and complementary conditions, determine the buried depth in the oil field, porosity,
With respect to physical property, permeability, top separator thickness and fault gouge ratio SGR indexes, and then by the buried depth in the oil field, hole
Degree, relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes are brought into oily probability regression modelIn obtain containing for the oil field
Oil gas probability, realizes the quantum chemical method of oil gas field oily probability, improves the reliability of oil field oil-containing gas evaluation method
And practicality, meet the demand of Oil/gas Well fine granularing scalability.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
The accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments of invention, for those of ordinary skill in the art, without having to pay creative labor, may be used also
Other accompanying drawings are obtained with according to these accompanying drawings.
Fig. 1 is the schematic flow sheet of the method for quantitatively evaluating for oil field oil-containing gas that the embodiment of the present invention one is provided；
Fig. 2 is the overall geological structure schematic diagram in Gaoyou Depression oil field；
Fig. 3 is a kind of schematic flow sheet of method for quantitatively evaluating provided in an embodiment of the present invention；
Fig. 4 is a kind of quantitatively evaluating apparatus structure schematic diagram for oil field oil-containing gas provided in an embodiment of the present invention；
Fig. 5 is a kind of structural representation of quantitatively evaluating device provided in an embodiment of the present invention；
Fig. 6 is a kind of structural representation of quantitatively evaluating device provided in an embodiment of the present invention.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.It is based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made
Embodiment, belongs to the scope of protection of the invention.
Term " comprising " and " having " in description and claims of this specification and above-mentioned accompanying drawing and they
Any deformation, it is intended that covering is non-exclusive to be included, for example, containing the process of series of steps or unit, method, being
System, product or equipment are not necessarily limited to those steps or the unit clearly listed, but may include not list clearly or
For these processes, method, product or other intrinsic steps of equipment or unit.
Method for quantitatively evaluating for oil field oil-containing gas provided in an embodiment of the present invention can be performed by terminal device.This
Terminal device in inventive embodiments can include that the handheld device of display screen, mobile unit, wearable device, calculating set
It is standby, and various forms of user equipmenies (User Equipment；Referred to as：UE), mobile station (Mobile Station；Letter
Claim：) and terminal (terminal) etc. MS.Example, the terminal device of the embodiment of the present invention can be desktop computer, server etc.
Deng.
Method for quantitatively evaluating for oil field oil-containing gas provided in an embodiment of the present invention, for oil-gas exploration
Cheng Zhong, the oil-gas possibility of evaluating oilfield, oil-source condition, the poly- condition of fortune according to the oil field, reservoir conditions, trap bar
Part, preservation condition and complementary conditions, it is first determined the buried depth in the oil field, porosity, relative physical property, permeability,
Top separator thickness and fault gouge ratio SGR indexes, so by the buried depth in the oil field, porosity, relative physical property,
Permeability, top separator thickness and fault gouge ratio SGR indexes are brought into oily probability regression modelIn obtain containing for the oil field
Oil gas probability, realizes the quantum chemical method of oil gas field oily probability, improves the reliability of oil field oil-containing gas evaluation method
And practicality, meet the demand of Oil/gas Well fine granularing scalability.
Technical scheme is described in detail with specific embodiment below.These specific implementations below
Example can be combined with each other, and may be repeated no more in some embodiments for same or analogous concept or process.
Fig. 1 is the schematic flow sheet of the method for quantitatively evaluating for oil field oil-containing gas that the embodiment of the present invention one is provided.
As shown in figure 1, the method for quantitatively evaluating for oil field oil-containing gas that the embodiment of the present invention one is provided is comprised the following steps：
Step S101：Determine the oil field oil-source condition, transport poly- condition, reservoir conditions, trap condition, preservation condition and
Complementary conditions.
In the implementation process of step S101, the integrally texture in the oil field is generally obtained using method of seismic exploration first
Make, specifically, obtain the geological structure data in the oil field by method of seismic exploration, so by computer carry out data processing and
Draw the geologic structure diagram in the oil field.It should be noted that method of seismic exploration implements process, those skilled in the art can
With reference to prior art.Example, be recessed by the Cenozoic fault basins Gaoyou, northern Suzhou of method of seismic exploration acquisition shown in ground Fig. 2
Fall into the overall geological structure in oil field.
After obtaining the geological structure in the oil field by method of seismic exploration, and then according to the geological structure in the oil field, it is determined that
The oil-source condition in the oil field, transport poly- condition, reservoir conditions, trap condition, preservation condition and complementary conditions.
Determine certain geological structure whether oily be multinomial accumulating condition comprehensive function result, typically relate generally to oil
The aspects such as source condition, the poly- condition of fortune, reservoir conditions, trap condition, preservation condition and complementary conditions.As a example by shown in Fig. 2, Gaoyou
, essentially from bottom four sections of hydrocarbon source rocks of mound, the set Thermal Evolution of Source Rocks degree is high, and generation and expulsion intension is big, and Gaoyou is recessed for depression oil gas
Fall into directly covering thereon, in bump contact, oil gas supply is sufficient；Gaoyou Depression sand body is developed, and is the front-delta deposition, thing
Source comes from east northeast direction, and plane distribution is wide, extends remote；In the thick-layer dark mud rock of a set of stabilization of Gaoyou Depression deposited atop, it is
Zonal quality caprock；Gaoyou Depression is influenceed to develop trap largely relevant with tomography by faulting, trap quantity is more, class
Type is close；Tomography also constitutes main migration pathway, and bottom four sections of primary rock producing hydrocarbon olefiant gas of mound are with the vertical migration along tomography
It is main, and it is aided with the lateral transporting of sand body；In the main Pool-forming time of oil gas (three pile groups deposit latter stage), sinking rank is stablized in Gaoyou Depression entrance afterwards
Section, tectonic activity is weak, is destroyed without big oil gas.Therefore in general, Gaoyou Depression has " nearly source aggregation, vertical migration, fracture
Control is hidden " Hydrocarbon Accumulation Characteristics, source-reservoir-seal assemblage is good, and overall accumulating condition configuration is superior, and oil-gas possibility difference is more receives for its
Control in trap in itself into Tibetan ability and geological conditions, it is main to include capture oil gas ability (the poly- condition of fortune), preserve oil gas ability
(reservoir conditions) and preserve the aspects such as oil gas ability (Seal Condition).
Step S102：Oil-source condition according to the oil field, transport poly- condition, reservoir conditions, trap condition, preservation condition and
Complementary conditions, determine buried depth, porosity, relative physical property, permeability, top separator thickness and the fault gouge ratio in the oil field
Rate SGR indexes.
Specifically, with reference to shown in Fig. 3, the implementation procedure of step S102 can include following steps：
Step S1021：Oil-source condition, the poly- condition of fortune according to the oil field, reservoir conditions, trap condition, preservation condition
And complementary conditions, determine the capture oil gas ability in the oil field, preserve oil gas ability and preserve oil gas ability；
Step S1022：According to the capture oil gas ability, described preserve oil gas ability and the preservation oil gas ability, choosing
Buried depth, porosity, relative physical property, permeability, top separator thickness and the fault gouge ratio SGR indexes for taking the oil field are made
It is the quantitatively evaluating factor of the oil field oil-containing gas；
Step S1023：The overall geological structure in the oil field obtained according to method of seismic exploration, determines burying for the oil field
Hide depth, porosity, the concrete numerical value of relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes.
Specifically, oil-source condition according to the Hydrocarbon Accumulation Characteristics in the oil field, the i.e. oil field, transport poly- condition, reservoir conditions,
Trap condition, preservation condition and complementary conditions, it may be determined that the accumulating condition configuration in the oil field, and then, it may be determined that the oil field
Into ability and geological conditions is hidden, that is, obtain the capture oil gas ability (correspond to fortune poly- condition) in the oil field, preserve oil gas ability
(corresponding to reservoir conditions) and preserve oil gas ability (corresponding to Seal Condition).
It should be noted that the oil-source condition of the embodiment of the present invention, the poly- condition of fortune, reservoir conditions, trap condition, preservation bar
Part and complementary conditions and capture oil gas ability, to preserve oil gas ability and preserve oil gas ability be that the qualitative of the oil field is retouched
State, be not specific numerical value.It is of course also possible to limit the oil-source condition in the oil field from quantitative angle, transport poly- condition, reservoir
Condition, trap condition, preservation condition and complementary conditions and capture oil gas ability, preserve oil gas ability and preserve oil gas ability
Deng, the embodiment of the present invention in this regard, not limiting, specifically, those skilled in the art refer to prior art.
After obtaining the capture oil gas ability in the oil field, preserving oil gas ability and preserve oil gas ability, and then according to the oil
The capture oil gas ability in field, preserve oil gas ability and preserve oil gas ability, it is determined that for the oil-gas possibility in the quantitatively evaluating oil field
Quantitatively evaluating factor, example, capture oil gas ability according to the oil field, preserve oil gas ability and preserve oil gas ability, really
Buried depth, porosity, the phase in the oil field that the quantitatively evaluating factor of the fixed oil-gas possibility for the quantitatively evaluating oil field includes
To physical property, permeability, top separator thickness and fault gouge ratio SGR indexes.
Wherein, buried depth be used for characterize circle source distance, bury deeper, from mature source rock more close to, be often easier to obtain
Oil gas；It is that above different evaluation unit, according to the good and bad sequence of physical property, can be used to represent interlayer heterogeneity pair for longitudinal direction with respect to physical property
Oil gas finds that the difference of different interval physical property can cause on longitudinal direction along the influence of tomography migration shunting according to Related Experimental Study
Oil gas is partial to the preferable reservoir of relative physical property during vertical filling, or even is formed under certain condition " other super phenomenon ",
The flowing and distribution of oil gas are influenceed, therefore buried depth and relatively physical property can be classified as the poly- conditional indicator of fortune of oil gas, reflection circle
Close the ability of capture oil gas.Sand thickness, porosity and permeability are the important parameters for characterizing Reservoir Scale and performance, can be classified as
The ability of oil gas is preserved in the reservoir conditions index of oil gas, reflection trap.Top shale interlayer between sand group can be used as partial cover
Layer intercepts the vertical of oil gas and scatters and disappears, and its thickness influences the validity and abundance of oil-gas accumulation, fault gouge ratio to a certain extent
SGR is the important means of Quantitative Evaluation on Fault lateral seal, can be used to represent that tomography blocks ability to the lateral of oil gas, therefore
Top separator thickness, fault gouge ratio SGR can be classified as the Seal Condition of oil gas, and reflection trap preserves the ability of oil gas.
Further, it is determined that after for the quantitatively evaluating factor of the oil-gas possibility in the quantitatively evaluating oil field, according to earthquake
Prospecting obtain the oil field overall geological structure, it is determined that for the quantitatively evaluating oil field oil-gas possibility quantitatively evaluating because
The concrete numerical value of element, including the buried depth in the oil field, porosity, relative physical property, permeability, top separator thickness and fault gouge
The concrete numerical value of ratio SGR indexes.
Example, by taking the Gaoyou Depression oil field shown in Fig. 2 as an example, according to the overall geological structure in the oil field, it may be determined that
The buried depth in the oil field is that 3.35km or so, porosity are that 9.89%, permeability is that 3.41mD, relative physical property are 2 (on longitudinal direction
By contrast its with respect to physical property come the 2), top separator thickness is 19m and fault gouge ratio SGR indexes are 0.71, i.e. x1=
3.35,x2=2, x3=9.89, x4=3.41, X5=19, X6=0.71.
Step S103：The oily probability P in the oil field is determined according to oily probability regression model, wherein, it is described to contain
Oil gas probability regression model is：
In formula, x1It is the buried depth in the oil field, x2It is the porosity in the oil field, x3It is the permeability in the oil field,
x4It is the relative physical property in the oil field, x5It is the top separator thickness in the oil field, x6It is the fault gouge ratio SGR in the oil field
Index.
According to Logistic regression models by whether the classified variable of oily is converted to probability of happening problem, and by
Logit is converted and maximal possibility estimation realizes that the nonlinear fitting of relation between destination probability and independent variable is returned, and obtains oil-containing
Spirit rate regression model.
Concrete implementation process is as follows：
(1) it is Y to set dependent variable, and event is designated as 1, is not designated as 0, and event occurrence condition probability is p, is not occurred general
Rate is 1-p, and the m independent variable of influence dependent variable Y is designated as x1,x2,…,xm.Because probability P value is limited between 0-1, nothing
The regression equation that method is directly set up between destination probability and independent variable, thus Logit conversion is carried out to P, by probability of happening and not
The ratio of probability of happening takes natural logrithm and obtains Ln [P/ (1-P)], is designated as Logit (P), and its span is changed into (- ∞, ﹢ ∞), then
Set up regression equation
In formula, β0, β1, β2..., βmIt is logistic regression coefficient to be estimated, β0It is constant term.
(2) above-mentioned regression equation is entered into the expression formula that line translation obtains probability P
In formula, β0, β1, β2..., βmIt is logistic regression coefficient to be estimated, β0It is constant term.
Due to the particularity of dependent variable, to each unknowm coefficient ask for no longer be applicable least square method, need to be using more
Universal Maximum-likelihood estimation, its main method be by known sample construct its joint probability of happening likelihood function or logarithm seemingly
Right function, passing mathematical iterations computing selection in principle according to maximum probability can make the estimates of parameters that likelihood function reaches maximum
It is each logistic regression coefficient to be estimated.
Or
In formula, Yi=1 or Yi=0, n are evaluation unit sample number.
Finally, so that whether oily is dependent variable (1 represents oily, and 0 represents not oily), with the evaluation index screened
It is independent variable, it is sample point that unit is evaluated in the refinement of research area, is substituted into logistic formula simultaneously according to actual exploration data
Regressing calculation is carried out, the oily probability regression model for being adapted to research area is finally given：
In formula, x1It is the buried depth in the oil field, x2It is the porosity in the oil field, x3It is the permeability in the oil field,
x4It is the relative physical property in the oil field, x5It is the top separator thickness in the oil field, x6It is the fault gouge ratio SGR in the oil field
Index.
Oily probability regression model is obtained, by the buried depth in the above-mentioned oil field, porosity, relative physical property, has been oozed
The concrete numerical value of saturating rate, top separator thickness and fault gouge ratio SGR indexes substitutes into the regression model and is calculated, you can obtain
The oily probability P in oil field, realizes the quantitatively evaluating to the oil field oil-containing gas.
Example, the concrete numerical value of the quantitatively evaluating factor in the Gaoyou Depression oil field shown in Fig. 2 is substituted into the oil-containing spirit
Rate regression model is that to can obtain the oily probability P in Gaoyou Depression oil field be 0.748, and judgement belongs to oily classification, with reality
Drilling situation is consistent, after tested the oil field day oil-producing 23.45m3。
Method for quantitatively evaluating for oil field oil-containing gas provided in an embodiment of the present invention, the oil sources bar according to the oil field
Part, transport poly- condition, reservoir conditions, trap condition, preservation condition and complementary conditions, determine the buried depth in the oil field, porosity,
With respect to physical property, permeability, top separator thickness and fault gouge ratio SGR indexes, and then by the buried depth in the oil field, hole
Degree, relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes are brought into oily probability regression model
In be somebody's turn to do
The oily probability in oil field, realizes the quantum chemical method of oil gas field oily probability, improves oil field oil-containing gas evaluation method
Dependable with function, meet the demand of Oil/gas Well fine granularing scalability.
Fig. 4 is the structural representation of the quantitatively evaluating device for oil field oil-containing gas provided in an embodiment of the present invention.Such as
Shown in Fig. 4, quantitatively evaluating device provided in an embodiment of the present invention includes：
First determining module 401, for determining the oil-source condition in the oil field, transporting poly- condition, reservoir conditions, trap bar
Part, preservation condition and complementary conditions；
Second determining module 402, for the oil-source condition according to the oil field, transports poly- condition, reservoir conditions, trap bar
Part, preservation condition and complementary conditions, determine buried depth, porosity, relative physical property, permeability, the top separator in the oil field
Thickness and fault gouge ratio SGR indexes；
3rd determining module 403, the oily probability P for determining the oil field according to oily probability regression model,
Wherein, the oily probability regression model is：
In formula, x1It is the buried depth in the oil field, x2It is the porosity in the oil field, x3It is the permeability in the oil field,
x4It is the relative physical property in the oil field, x5It is the top separator thickness in the oil field, x6It is the fault gouge ratio SGR in the oil field
Index.
Optionally, first determining module 401 includes：
First acquisition submodule 4011, Ying Yu obtains the overall geological structure in the oil field using method of seismic exploration；
First determination sub-module 4012, for according to the overall geological structure, determining oil-source condition, the fortune in the oil field
Poly- condition, reservoir conditions, trap condition, preservation condition and complementary conditions.
Optionally, the second described determining module 402 specifically for：
Oil-source condition, the poly- condition of fortune, reservoir conditions, trap condition, preservation condition and complementary conditions according to the oil field,
Determine the capture oil gas ability in the oil field, preserve oil gas ability and preserve oil gas ability；
According to the capture oil gas ability, it is described preserve oil gas ability and the preservation oil gas ability, choose the oil field
Buried depth, porosity, relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes as the oil field
The quantitatively evaluating factor of oil-gas possibility；
The overall geological structure in the oil field obtained according to method of seismic exploration, determines buried depth, the hole in the oil field
The concrete numerical value of porosity, relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes.
Optionally, the 3rd determining module 403 includes：
3rd determination sub-module 4031, for according to Logistic regression models by whether oily classified variable conversion
It is probability of happening problem, and the non-of relation between destination probability and independent variable is realized by logit conversion and maximal possibility estimation
Linear fit is returned, and obtains oily probability regression model, wherein, oily probability regression model is：
3rd calculating sub module 4032, for by the buried depth in the oil field, porosity, with respect to physical property, permeability, top
The concrete numerical value of portion's compartment thickness and fault gouge ratio SGR indexes brings the oily probability regression model into, obtains the oil
The oily probability P in field.
Optionally, the 3rd determination sub-module 4032 specifically for：
Event is designated as 1,0 is not designated as, event occurrence condition probability is p, and probability of happening is not 1-p, and P is entered
Row logit is converted, and obtains regression equation：
Wherein, x1,x2,…,xmIt is the m independent variable of influence dependent variable Y, β0, β1, β2..., βmIt is logistic regression to be estimated
Coefficient, β0It is constant term；
The likelihood function of its joint probability of happening is constructed according to known sampleUsing maximum
Principle of probability selects the estimates of parameters that likelihood function can be made to reach maximum to determine that each to be estimated is patrolled by mathematical iterations computing
Collect regression coefficient；
According to each logistic regression coefficient to be estimated and the regression equation, the oily probability regression model is obtained.
It should be noted that：The quantitatively evaluating device for oil field oil-containing gas that above-described embodiment is provided, only with above-mentioned
The division of each functional module is carried out for example, in practical application, as needed can distribute by different above-mentioned functions
Functional module is completed, will the internal structure of equipment be divided into different functional modules, with complete it is described above whole or
Partial function.In addition, the quantitatively evaluating device for oil field oil-containing gas that provides of above-described embodiment be used for oil field oil-containing gas
The method for quantitatively evaluating embodiment of property belongs to same design, and it implements process and refers to embodiment of the method, repeats no more here.
One of ordinary skill in the art will appreciate that：Realizing all or part of step of above-mentioned each method embodiment can lead to
The related hardware of programmed instruction is crossed to complete.Foregoing program can be stored in a computer read/write memory medium.The journey
Sequence upon execution, performs the step of including above-mentioned each method embodiment；And foregoing storage medium includes：ROM, RAM, magnetic disc or
Person's CD etc. is various can be with the medium of store program codes.
Finally it should be noted that：Various embodiments above is merely illustrative of the technical solution of the present invention, rather than its limitations；To the greatest extent
Pipe has been described in detail with reference to foregoing embodiments to the present invention, it will be understood by those within the art that：Its according to
The technical scheme described in foregoing embodiments can so be modified, or which part or all technical characteristic are entered
Row equivalent；And these modifications or replacement, the essence of appropriate technical solution is departed from various embodiments of the present invention technology
The scope of scheme.
Claims (10)
1. a kind of method for quantitatively evaluating for oil field oil-containing gas, it is characterised in that methods described includes：
Determine the oil-source condition in the oil field, transport poly- condition, reservoir conditions, trap condition, preservation condition and complementary conditions；
Oil-source condition, the poly- condition of fortune, reservoir conditions, trap condition, preservation condition and complementary conditions according to the oil field, it is determined that
The buried depth in the oil field, porosity, relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes；
The oily probability P in the oil field is determined according to oily probability regression model, wherein, the oily probability returns mould
Type is：
In formula, x1It is the buried depth in the oil field, x2It is the porosity in the oil field, x3It is the permeability in the oil field, x4For
The relative physical property in the oil field, x5It is the top separator thickness in the oil field, x6It is the fault gouge ratio SGR indexes in the oil field.
2. method for quantitatively evaluating according to claim 1, it is characterised in that the oil-source condition in the determination oil field,
Poly- condition, reservoir conditions, trap condition, preservation condition and complementary conditions are transported, including：
The overall geological structure in the oil field is obtained using method of seismic exploration；
According to the overall geological structure, determine the oil-source condition in the oil field, transport poly- condition, reservoir conditions, trap condition, guarantor
Deposit condition and complementary conditions.
3. method for quantitatively evaluating according to claim 1, it is characterised in that the oil-source condition according to the oil field,
Transport poly- condition, reservoir conditions, trap condition, preservation condition and complementary conditions, determine the buried depth in the oil field, porosity,
With respect to physical property, permeability, top separator thickness and fault gouge ratio SGR indexes, including：
Oil-source condition, the poly- condition of fortune, reservoir conditions, trap condition, preservation condition and complementary conditions according to the oil field, it is determined that
The capture oil gas ability in the oil field, preserve oil gas ability and preserve oil gas ability；
According to the capture oil gas ability, it is described preserve oil gas ability and the preservation oil gas ability, choose burying for the oil field
Depth, porosity, relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes are hidden as the oil field oil-containing
The quantitatively evaluating factor of gas；
The overall geological structure in the oil field obtained according to method of seismic exploration, determine the buried depth in the oil field, porosity,
With respect to the concrete numerical value of physical property, permeability, top separator thickness and fault gouge ratio SGR indexes.
4. the method for quantitatively evaluating according to claim 1 or 3, it is characterised in that described that mould is returned according to oily probability
Type determines the oily probability P in the oil field, including：
According to Logistic regression models by whether the classified variable of oily is converted to probability of happening problem, and by logit
Conversion and maximal possibility estimation realize that the nonlinear fitting of relation between destination probability and independent variable is returned, and obtain oily probability
Regression model, wherein, oily probability regression model is：
The buried depth in the oil field, porosity, relative physical property, permeability, top separator thickness and fault gouge ratio SGR are referred to
Several concrete numerical values brings the oily probability regression model into, obtains the oily probability P in the oil field.
5. method for quantitatively evaluating according to claim 4, it is characterised in that described to be according to Logistic regression models
The classified variable of no oily is converted to probability of happening problem, and realizes that target is general by logit conversion and maximal possibility estimation
The nonlinear fitting of relation is returned between rate and independent variable, obtains oily probability regression model, including：
Event is designated as 1,0 is not designated as, event occurrence condition probability is p, and probability of happening is not 1-p, and P is carried out
Logit is converted, and obtains regression equation：
Wherein, x1,x2,…,xmIt is the m independent variable of influence dependent variable Y, β0, β1, β2..., βmIt is logistic regression coefficient to be estimated,
β0It is constant term；
The likelihood function of its joint probability of happening is constructed according to known sampleUsing maximum probability
Passing mathematical iterations computing selection in principle can make the estimates of parameters that likelihood function reaches maximum determine that each logic to be estimated is returned
Return coefficient；
According to each logistic regression coefficient to be estimated and the regression equation, the oily probability regression model is obtained.
6. a kind of quantitatively evaluating device for oil field oil-containing gas, it is characterised in that described device includes：
First determining module, for determining the oil-source condition in the oil field, transporting poly- condition, reservoir conditions, trap condition, preservation bar
Part and complementary conditions；
Second determining module, for the oil-source condition according to the oil field, transports poly- condition, reservoir conditions, trap condition, preservation bar
Part and complementary conditions, determine buried depth, porosity, relative physical property, permeability, top separator thickness and the tomography in the oil field
Mud ratio SGR indexes；
3rd determining module, the oily probability P for determining the oil field according to oily probability regression model, wherein, institute
Stating oily probability regression model is：
In formula, x1It is the buried depth in the oil field, x2It is the porosity in the oil field, x3It is the permeability in the oil field, x4For
The relative physical property in the oil field, x5It is the top separator thickness in the oil field, x6It is the fault gouge ratio SGR indexes in the oil field.
7. quantitatively evaluating device according to claim 6, it is characterised in that first determining module includes：
First acquisition submodule, Ying Yu obtains the overall geological structure in the oil field using method of seismic exploration；
First determination sub-module, for according to the overall geological structure, determine the oil field oil-source condition, transport poly- condition,
Reservoir conditions, trap condition, preservation condition and complementary conditions.
8. device according to claim 6, it is characterised in that the second described determining module specifically for：
Oil-source condition, the poly- condition of fortune, reservoir conditions, trap condition, preservation condition and complementary conditions according to the oil field, it is determined that
The capture oil gas ability in the oil field, preserve oil gas ability and preserve oil gas ability；
According to the capture oil gas ability, it is described preserve oil gas ability and the preservation oil gas ability, choose burying for the oil field
Depth, porosity, relative physical property, permeability, top separator thickness and fault gouge ratio SGR indexes are hidden as the oil field oil-containing
The quantitatively evaluating factor of gas；
The overall geological structure in the oil field obtained according to method of seismic exploration, determine the buried depth in the oil field, porosity,
With respect to the concrete numerical value of physical property, permeability, top separator thickness and fault gouge ratio SGR indexes.
9. the method for quantitatively evaluating according to claim 6 or 8, it is characterised in that the 3rd determining module includes：
3rd determination sub-module, for according to Logistic regression models by whether the classified variable of oily to be converted to generation general
Rate problem, and the nonlinear fitting of relation between destination probability and independent variable is realized by logit conversion and maximal possibility estimation
Return, obtain oily probability regression model, wherein, oily probability regression model is：
3rd calculating sub module, for the buried depth in the oil field, porosity, relative physical property, permeability, top separator is thick
The concrete numerical value of degree and fault gouge ratio SGR indexes brings the oily probability regression model into, obtains the oil-containing in the oil field
Gas probability P.
10. quantitatively evaluating device according to claim 9, it is characterised in that the 3rd determination sub-module specifically for：
Event is designated as 1,0 is not designated as, event occurrence condition probability is p, and probability of happening is not 1-p, and P is carried out
Logit is converted, and obtains regression equation：
Wherein, x1,x2,…,xmIt is the m independent variable of influence dependent variable Y, β0, β1, β2..., βmIt is logistic regression coefficient to be estimated,
β0It is constant term；
The likelihood function of its joint probability of happening is constructed according to known sampleUsing maximum probability
Passing mathematical iterations computing selection in principle can make the estimates of parameters that likelihood function reaches maximum determine that each logic to be estimated is returned
Return coefficient；
According to each logistic regression coefficient to be estimated and the regression equation, the oily probability regression model is obtained.
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