A kind of more geologic(al) factor quantitative assessment expulsive efficiency methods
Technical field
The present invention relates to a kind of more geologic(al) factor quantitative assessment expulsive efficiency methods, belong to oil and gas resource evaluation analytical technology
Field.
Background technology
Oil gas will be gathered into conventional oil gas reservoir, and first having to migrate from hydrocarbon source rock comes out, and the primary migration of oil gas is entire
The first step of oil-gas migration.The meaning of expulsive efficiency be exactly migration efficiency of the oil gas in hydrocarbon source rock and from hydrocarbon source rock to fortune
Carrier layer, the efficiency of reservoir migration.The hydrocarbon expulsion process of hydrocarbon source rock is various complicated geological combined factors effects as a result, being one
Complicated geological process influences many because being known as of expulsive efficiency, and the internal factor including hydrocarbon source rock, such as organic matter type has
Machine matter abundance, maturity of organic matter, while also include some external factor, such as hydrocarbon source rock inner pore, crack, rock texture, interior
Portion's pressure, formation temperature, interfacial tension, capillary pressure, specific surface etc..Both factors to the expulsive efficiency of hydrocarbon source rock all
There is great influence.
About hydrocarbon source rock expulsive efficiency, forefathers have carried out expulsive efficiency more in-depth study, put it briefly including
8 kinds of methods below:Residual hydrocarbons amount method, multi-phase porous flow theory method, hydrocarbon saturation method, geologic analogy method, original hydrocarbon potentiality are extensive
Multiple method, evolution trend face minusing, hydrocarbon potentiality method, material balance method.However, the shortcomings that various methods have its respectively, such as
The shortcomings that residual hydrocarbons amount method is exactly main still according to warp for the linear relationship slope K e values between residual hydrocarbons and Hydrocarbon yield
It tests;As long as and think the presence for having residual hydrocarbons, just have corresponding discharge, reached critical hydrocarbon exhaust condition without considering whether
Deng;The shortcomings that multi-phase porous flow theory method is that the minimum critical saturation (S) of hydrocarbon will generally be more than 20%, therefore in this situation
Under, hydrocarbon is largely discharged with regard to highly difficult etc.;Hydrocarbon saturation method main assumption hydrocarbon source rock discharge fluid in hydrocarbon saturation with
The hydrocarbon saturation of fluid is identical in hydrocarbon source rock, but the hypothesis has no basis;Geologic analogy method assumes that Hydrocarbon yield is oil in place,
But much smaller than practical discharge rate of oil in place that resource assessment comes out;It is real that hydrocarbon thermal simulation experiment method carries out row's hydrocarbon simulation
It tests, measures the residual hydrocarbons of analog sample and discharge hydrocarbon amount, but row's hydrocarbon mechanism is different from practical geology, and lighter hydrocarbons loss does not consider;
Hydrocarbon potentiality method is needed using actual measurement hydrocarbon source rock geochemistry data, but the anisotropism of hydrocarbon source rock is strong, and one will be had by measuring sample
Determine specific aim, meet and be just distributed very much, and oil gas can not separate;Material balance method mainly utilizes chemical dynemics (or hot-die
Quasi-experimental method) the hydrocarbon amount of hydrocarbon source rock is calculated, then obtained with the method that geochemical logging, logging evaluation, sample analysis are combined
The residual hydrocarbons amount of hydrocarbon source rock obtains Hydrocarbon yield by the difference of hydrocarbon amount and residual hydrocarbon amount, and Hydrocarbon yield is imitated than upper hydrocarbon amount up to hydrocarbon is arranged
Rate, the advantages of this method, which is that of avoiding, directly describes complicated hydrocarbon expulsion process, and shortcoming is that evaluation procedure is excessively complicated, is evaluated
Any one walks out of existing error in journey, can all influence expulsive efficiency;Evolution trend face minusing is difficult to determine whether hydrocarbon source rock is not arranged
Hydrocarbon.In contrast, basic data needed for this 3 kinds of methods of original hydrocarbon potentiality restoring method, hydrocarbon potentiality method and material balance method is held
It easily obtains, and the method that complicated hydrocarbon expulsion process and our common calculating expulsive efficiencies can be avoided.
Generally speaking, above-mentioned 8 kinds of methods all need what many experiments analyzing test data or the experimentation cycle of operation were grown
Defect virtually adds scientific research cost and the scientific research cycle of operation, and do not account for hydrocarbon source rock expulsive efficiency by a variety of geology because
Element influences, as configuration relation, sedimentary facies and tectonic evolution pattern are stored up, and real in abundance of organic matter, type, maturity, source rock thickness, source
Testing data, there are certain errors with the expulsive efficiency under geological conditions.
And deepen with the degree of prospecting in ripe prospect pit area, current expulsive efficiency evaluation method cannot meet currently
The demand of intensity is explored, there is an urgent need for explore a kind of to facilitate feasible, quickness and high efficiency, expulsive efficiency evaluation side easy to utilize
Method.
Invention content
For overcome the deficiencies in the prior art, thus, the present invention proposes a kind of more geologic(al) factor quantitative assessment expulsive efficiencies
Method, it is convenient and efficient, can plane promote and apply, current exploration knowledge and available data can be utilized, quantitative assessment go out every mouthful
The high continuous expulsive efficiency in well destination layer position hydrocarbon source rock longitudinal direction, with reference to more mouthfuls of drilling datas in plane, establish out meet precision will
The hydrocarbon source rock expulsive efficiency said three-dimensional body asked.
A kind of more geologic(al) factor quantitative assessment expulsive efficiency methods, contain following steps;
Step 1) establishes a kind of expulsive efficiency evaluation method based on life residence thermal simulation experiment, while it is extensive to establish lighter hydrocarbons
Complex coefficient evaluation model solves the lighter hydrocarbons lost in life residence thermal simulation experiment;In addition, the row evaluated with reference to hydrocarbon potentiality method
Hydrocarbon efficiency and life residence measured value accurately evaluate the expulsive efficiency of typical well;
Step 2), the influence factor for filtering out expulsive efficiency:Considering influences the internal factor of expulsive efficiency and external
Factor;Hydrocarbon source rock influnecing factor considers organic matter type, abundance of organic matter, maturity of organic matter, outside hydrocarbon source rock because
Element considers hydrocarbon source rock inner pore, crack, rock texture, internal pressure, formation temperature, interfacial tension, capillary pressure, compares table
Face;Comprehensive sedimentary facies and mode is buried, filter out abundance of organic matter, organic matter type, maturity of organic matter and source storage configuration and close
It is 4 kinds of factors;
Step 3) establishes single geologic(al) factor of expulsive efficiency and the relationship model of expulsive efficiency:Considering influences hydrocarbon source
The internal factor and external factor of rock expulsive efficiency filter out organic matter type, abundance of organic matter, maturity of organic matter and source storage
Four key parameters of configuration relation store up configuration relation factor by abundance of organic matter, organic matter type, maturity of organic matter and source
It is analyzed with expulsive efficiency mathematical relationship, it is determined that under the logarithmic relationship of abundance of organic matter and expulsive efficiency, organic matter type constraint
Maturity and expulsive efficiency exponential relationship, source storage configuration relation constraint under maturity of organic matter and expulsive efficiency it is multinomial
Formula relationship;
Step 4), the evaluation model for establishing more geologic(al) factors and expulsive efficiency:Determine abundance of organic matter and expulsive efficiency
Having under logarithmic relationship, the exponential relationship of the maturity under organic matter type constraint and expulsive efficiency, source storage configuration relation constraint
The polynomial relation of machine matter maturity and expulsive efficiency, i.e., the list geologic(al) factor is to the contribution rate of expulsive efficiency;Intended using curve
Software is closed, more geologic(al) factors based on single factor evaluation model, meeting geological knowledge, meeting geologic rule is established out and quantifies
Evaluate expulsive efficiency evaluation model;
Step 5) is promoted and applied in the plane using more geologic(al) factor quantitative assessment expulsive efficiency evaluation models, is commented
Valency goes out hydrocarbon source rock expulsive efficiency flat distribution map, illustrates the conventional distribution characteristics with unconventionaloil pool, it is indicated that it is conventional with it is unconventional
Accumulation zone.
It is an advantage of the invention that:
It is an advantage of the invention that taking full advantage of available data, overcoming previous evaluation expulsive efficiency needs unconfined reality
Drawback is tested, plan defines a kind of more geologic(al) factor quantitative assessment expulsive efficiency methods, realizes destination layer position hydrocarbon source rock expulsive efficiency
The evaluation of said three-dimensional body, enrich it is conventional with the preferred evaluation method of unconventionaloil pool favo(u)rable target in perfect In Oil Field Exploration And Development,
Obtain the accreditation of field operations personnel.
Description of the drawings
When considered in conjunction with the accompanying drawings, by referring to following detailed description, can more completely more fully understand the present invention with
And easily learn many of which with the advantages of, but attached drawing described herein is used to provide further understanding of the present invention,
The part of the present invention is formed, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, does not form to this hair
Bright improper restriction, such as figure are wherein:
Fig. 1 is the structural diagram of the present invention;
Fig. 2 is three kinds of data source overall merit J88 wells, 1976.99 meters of mud stone expulsive efficiency figures.
Fig. 3 is one of Song-liao basin the north Qingshankou group TOC logging evaluations model;
Fig. 4 is two models of Song-liao basin the north Qingshankou group TOC logging evaluations;
Fig. 5 is Song-liao basin the north Qingshankou group TOC block diagrams (golden 88 well overall efficiency figures-modeling figure);
Fig. 6 is Song-liao basin the north Qingshankou group TOC block diagrams (golden 87 well resultant effect figures-proof diagram);
Fig. 7 is one of TOC and expulsive efficiency relationship figure;
Fig. 8 is two figures of TOC and expulsive efficiency relationship;
Fig. 9 is three figures of TOC and expulsive efficiency relationship;
Figure 10 is four figures of TOC and expulsive efficiency relationship;
Figure 11 is five figures of TOC and expulsive efficiency relationship;
Figure 12 is six figures of TOC and expulsive efficiency relationship;
Figure 13 is hydrocarbon source rock maturity of organic matter and expulsive efficiency relational graph;
Figure 14 is one of maturity of organic matter and expulsive efficiency relationship under different abundances of organic matter, difference HI index conditions
Figure;
Figure 15 is two of maturity of organic matter and expulsive efficiency relationship under different abundances of organic matter, difference HI index conditions
Figure;
Figure 16 is three of maturity of organic matter and expulsive efficiency relationship under different abundances of organic matter, difference HI index conditions
Figure;
Figure 17 is four of maturity of organic matter and expulsive efficiency relationship under different abundances of organic matter, difference HI index conditions
Figure;
Figure 18 is five of maturity of organic matter and expulsive efficiency relationship under different abundances of organic matter, difference HI index conditions
Figure;
Figure 19 is six of maturity of organic matter and expulsive efficiency relationship under different abundances of organic matter, difference HI index conditions
Figure;
Figure 20 is seven of maturity of organic matter and expulsive efficiency relationship under different abundances of organic matter, difference HI index conditions
Figure;
Figure 21 is eight of maturity of organic matter and expulsive efficiency relationship under different abundances of organic matter, difference HI index conditions
Figure;
Figure 22 is one of source storage configuration relation sampling design figure;
Figure 23 is two figures of source storage configuration relation sampling design;
Figure 24 is three figures of source storage configuration relation sampling design;
Figure 25 is four figures of source storage configuration relation sampling design;
Figure 26 is the mud stone maturity of organic matter and expulsive efficiency relational graph of not homologous storage configuration relation;
Figure 27 is the mud stone abundance of organic matter and expulsive efficiency relational graph of not homologous storage configuration relation;
Figure 28 is one of abundance of organic matter and expulsive efficiency single factor evaluation model;
Figure 29 is two models of organic matter type and expulsive efficiency single factor evaluation;
Figure 30 is the expulsive efficiency evaluation model of not homologous storage configuration relation
Figure 31 be study area in expulsive efficiency extrapolation select well flat distribution map;
Figure 32 is expulsive efficiency flat distribution map in research area;
Figure 33 is expulsive efficiency 4 block diagrams of evaluation of programme point;
Figure 34 is different type hydrocarbon source rock expulsive efficiency correction coefficient KJZ。
The present invention is further described with reference to the accompanying drawings and examples.
Specific embodiment
Obviously, those skilled in the art belong to the guarantor of the present invention based on many modifications and variations that spirit of the invention is done
Protect range.
Embodiment 1:As shown in Figure 1, Figure 2, Fig. 3, Fig. 4, Fig. 5, Fig. 6, Fig. 7, Fig. 8, Fig. 9, Figure 10, Figure 11, Figure 12, Figure 13, figure
14th, Figure 15, Figure 16, Figure 17, Figure 18, Figure 19, Figure 20, Figure 21, Figure 22, Figure 23, Figure 24, Figure 25, Figure 26, Figure 27, Figure 28, figure
29th, shown in Figure 30, Figure 31, Figure 32, Figure 33, Figure 34,
A kind of more geologic(al) factor quantitative assessment hydrocarbon source rock expulsive efficiency methods, include the following steps:
A, data is compiled:Geochemical data, log data, well-log information and the geologic information in collection research area;
Wherein, geochemical data includes rock pyrolysis analysis test data, chloroform bitumen " A " analyzing test data, organic carbon analysis
Test data, kerogen microscopy;Well-log information includes natural gamma, interval transit time, microelectrode, micronormal, deep lateral and shallow side
To grade logs;Log data includes landwaste and log data;Geologic information includes deposition phase-plane diagram;
B, a kind of hydrocarbon source rock expulsive efficiency evaluation method is established:Rely on component hydrocarbon-generating dynamics, PYGC data, international stream
PetroMod2014 editions hydrocarbon model sample component data of row and thermal simulation experiment data, establish it is a kind of restored based on lighter hydrocarbons and
The expulsive efficiency evaluation method of life residence thermal simulation experiment data, the expulsive efficiency evaluated with reference to hydrocarbon potentiality method and row's hydrocarbon effect
Rate measured data, three kinds of method overall merits go out destination layer position hydrocarbon source rock expulsive efficiency;
However the expulsive efficiency only row's hydrocarbon situation at the next well point of geological conditions, it represents research area and integrally arranges hydrocarbon effect
Rate there is some difference property, and study and find that expulsive efficiency is influenced by a variety of geologic(al) factors, thus it is necessary to establish geologic(al) factor
With the quantitative assessment relationship of expulsive efficiency, the evaluation model of more geologic(al) factors and expulsive efficiency is finally established out, to study area three
Dimension expulsive efficiency evaluation lays the foundation;
C, the influence factor of expulsive efficiency is filtered out:The hydrocarbon expulsion process of hydrocarbon source rock is various complicated geological combined factors effects
As a result, be a complicated geological process, influence many because being known as of expulsive efficiency, the internal factor including hydrocarbon source rock, such as
Organic matter type, abundance of organic matter, maturity of organic matter;Also include some external factor simultaneously, such as hydrocarbon source rock inner pore, split
Seam, rock texture, internal pressure, formation temperature, interfacial tension, capillary pressure, specific surface etc.;Both factors are to hydrocarbon source
The expulsive efficiency of rock suffers from great influence.
The application considers the internal factor and external factor of expulsive efficiency, deeply dissects sedimentary facies and the difference side of burying
For persistently burying type, it is ripe to be divided into abundance of organic matter, organic matter type, organic matter by formula for the influence factor of expulsive efficiency
Degree, source storage four key parameters of configuration relation consider that abundance of organic matter, organic matter type, maturity of organic matter, source storage are matched respectively
Influence of the relationship single-factor variable to expulsive efficiency is put, to establish single geologic(al) factor evaluation model, a variety of geologic(al) factors evaluation row
Hydrocarbon efficiency Model provides basis;
Using organic anisotropism logging evaluation technology, with reference to resistivity, acoustic travel time logging curve and actual measurement TOC numbers
According to establishing organic anisotropism Logging estimation model;The upper high score in longitudinal direction is predicted according to resistivity and interval transit time log
The TOC data of resolution (0.125m), in addition, the organic matter type determined according to field data, maturity, source storage configuration relation etc.
The influence of expulsive efficiency;
D, single geologic(al) factor and expulsive efficiency evaluation model are established:Single geologic(al) factor is mainly with expulsive efficiency evaluation model
Expulsive efficiency and each single geologic(al) factor mathematical relationship are determined, according to step C) in analysis determine abundance of organic matter, organic matter
The geologic(al) factor of type, maturity of organic matter and source storage four kinds of influence expulsive efficiencies of configuration relation, establishes single geologic(al) factor and row
The evaluation model of hydrocarbon efficiency, quantitatively characterizing go out logarithmic relationship evaluation model, the organic matter type of abundance of organic matter and expulsive efficiency
The exponential relationship evaluation model of the lower maturity of constraint and expulsive efficiency, the maturity of organic matter under the storage configuration relation constraint of source and
The polynomial relation evaluation model of expulsive efficiency;
E, the mathematical model of more geologic(al) factors and expulsive efficiency is established:According to step D) in each single geologic(al) factor mould for determining
The data relationship of type, it is ensured that each geologic(al) factor contributes form, establishes the evaluation mould of more geologic(al) factors and hydrocarbon source rock expulsive efficiency
Type realizes more geologic(al) factor quantitative assessment expulsive efficiencies, lays the foundation to evaluate destination layer position hydrocarbon source rock three-dimensional expulsive efficiency;
F, research area destination layer position hydrocarbon source rock three-dimensional expulsive efficiency is evaluated:The grid of 5km × 5km is established in research area,
It is selected in each grid and represents well flatly, establish organic anisotropism Logging estimation model, obtain the TOC of longitudinal continuity from above;
Simultaneously according to hydrocarbon source rock sedimentary facies distribution, different type hydrocarbon source rock is determined;Determine hydrocarbon source rock maturation evolution condition and source storage group
Conjunction relationship;According to step E) in more geologic(al) factors evaluation expulsive efficiency model for determining, the well screened is arranged
Hydrocarbon efficiency rating geology is extrapolated, the high-resolution expulsive efficiency in longitudinal direction based on multiple wells, establishes out research area three-dimensional row's hydrocarbon effect
Rate geologic body works out expulsive efficiency plan view, predicts conventional and unconventional favorable oil/gas area.
The application is based on PetroMod2014 editions component hydrocarbon-generating dynamics, PYGC data, international popular hydrocarbon model samples
Product component data, thermal simulation experiment data and Pyrolysis Experiment data are restored and life residence thermal simulation experiment using based on lighter hydrocarbons
The 3 aspect expulsive efficiency data such as expulsive efficiency evaluation method, hydrocarbon potentiality method and life residence measured data, hydrocarbon of accurately grading out
Source rock expulsive efficiency;Consider the internal factor and external factor of influence hydrocarbon source rock expulsive efficiency, analyse in depth sedimentary facies and deposition
Method is buried, filters out abundance of organic matter, organic matter type, maturity of organic matter and source storage four key parameters of configuration relation,
Establish the quantitative evalution model of expulsive efficiency and single geologic(al) factor;By means of the mathematical relationship of expulsive efficiency and each single factor test, i.e.,
Each list geologic(al) factor is established a variety of geologic(al) factor evaluation expulsive efficiency models, is realized a variety ofly to the contribution form of expulsive efficiency
Quality factor quantitative assessment expulsive efficiency.
Expulsive efficiency is all most important for conventional and unconventional oil-gas exploration, for conventional gas and oil exploration, hydrocarbon
The oil gas of source rock generation can just contribute to the Gas Accumulation and Cheng Zang in later stage after only discharging;Shale oil gas is come
It says, the oil gas only remained in shale is more than enough could to form shale oil-gas reservoir.
Embodiment 2:By taking the Qingshankou group hydrocarbon source rock of Song-liao basin the north as an example, with ground data, geologic information, well-log information
It is supporting point with log data, using the application " a kind of more geologic(al) factor quantitative assessment expulsive efficiency methods ", establishes Qingshankou
Group hydrocarbon source rock three-dimensional expulsive efficiency geologic body, by taking wherein certain level as an example illustrate expulsive efficiency flat distribution map, analytic routines with
Unconventionaloil pool distribution characteristics.Technology path is shown in Fig. 1, the specific steps are:
(1), data is compiled:Geochemical data, log data, well-log information and the geology money in collection research area
Material;Wherein, geochemical data includes rock pyrolysis analysis test data, chloroform bitumen " A " analyzing test data, organic carbon point
Analyse test data, kerogen microscopy;It is lateral and shallow that well-log information includes natural gamma, interval transit time, microelectrode, micronormal, depth
It is lateral to wait logs;Log data includes landwaste and log data;Geologic information includes deposition phase-plane diagram;
Exposition geochemical data in text, is shown in Table 1.Wherein, the first well-name for being classified as test data, the second column data
For test sample distribution layer position;Third column data be test data well point depth, the 4th column data be TOC, the 5th column data
To be pyrolyzed S1Data, the 6th column data are pyrolysis S2Data, the 7th column data are chloroform bitumen " A " data;8th column data is to survey
The thermal evolutionary maturity of test agent.
1 Qingshankou group hydrocarbon source rock Geochemical Parameters of table
200 mouthfuls of collection research area well logging, log data, wherein, the main sieve residue log data of log data, well-log information master
To be gamma ray curve, interval transit time, micro- electric grade, micronormal, shallow lateral, deeply lateral etc. logs.To be subsequently a variety of
Quality factor quantitative assessment expulsive efficiency lays the foundation.
(2), initial expulsive efficiency is established:Rely on component hydrocarbon-generating dynamics, PYGC data, international popular
PetroMod2014 editions hydrocarbon model sample component data and thermal simulation experiment data are established a kind of based on lighter hydrocarbons recovery and raw row
The expulsive efficiency ranking method of hydrocarbon thermal simulation experiment data, with neat family's Cologne recess J88 1976.99 meter of II 1 type mud stone vertical compression of well
For formula thermal simulation experiment.The specific Geochemical Parameters of sample are shown in Table 2, and thermal simulation hydrocarbon experimental data is shown in Table 3.
The Basic Geological Geochemical Characteristics of 2 simulated experiment used sample of table
The northern golden 88 well Qingshankou group Dark grey mud stone direct press type thermal simulation experiment results of 3 Song-liao basin of table
88 well 1976.99m II of gold are directly evaluated using direct press type thermal simulation experiment data1The expulsive efficiency of type mud stone,
The loss of lighter hydrocarbons when having ignored extracting residual hydrocarbons so that the expulsive efficiency evaluated is bigger than normal.
Expulsive efficiency correction mainly considers direct press type thermal simulation experiment condition, corrects out loss during extracting residual hydrocarbons
Lighter hydrocarbons part, evaluate the expulsive efficiency for being more in line with practical geological conditions.Thus, using II in lighter hydrocarbons recovery coefficient plate
1 type recovery coefficient is corrected, the expulsive efficiency P after being corrected0(Fig. 2).Result after correction is than directly using direct press type
Thermal simulation experiment data evaluation is more in line with geological knowledge, and difference reaches 20% before and after expulsive efficiency correction.
Restore the evaluation expulsive efficiency method with life residence thermal simulation experiment data based on lighter hydrocarbons;The row's hydrocarbon effect evaluated
Rate evaluates expulsive efficiency and expulsive efficiency measured data with reference to hydrocarbon potentiality method, and three kinds of method overall merits go out destination layer position
The hydrocarbon source rock expulsive efficiency of typical well;Consider expulsive efficiency and the measured data data that hydrocarbon potentiality method evaluates, prove
Thermal simulation experiment method evaluates the accuracy of hydrocarbon source rock expulsive efficiency.On this basis, the hydrocarbon source of Qingshankou group typical case's well is provided
The final expulsive efficiency of rock.
However the expulsive efficiency only row's hydrocarbon situation at the next well point of geological conditions, it represents research area and integrally arranges hydrocarbon effect
Rate there is some difference property, and study and find that expulsive efficiency is influenced by a variety of geologic(al) factors, thus it is necessary to establish geologic(al) factor
With the quantitative assessment relationship of expulsive efficiency, the evaluation model of more geologic(al) factors and expulsive efficiency is finally established out, to study area three
Dimension expulsive efficiency evaluation lays the foundation;
(3), the influence factor of expulsive efficiency is filtered out:The hydrocarbon expulsion process of hydrocarbon source rock is that various complicated geological combined factors are made
As a result, be a complicated geological process, many because being known as of expulsive efficiency are influenced, the internal factor including hydrocarbon source rock,
Such as organic matter type, abundance of organic matter, maturity of organic matter;Also include some external factor simultaneously, such as hydrocarbon source rock inner pore, split
Seam, rock texture, internal pressure, formation temperature, interfacial tension, capillary pressure, specific surface etc.;Both factors are to hydrocarbon source
The expulsive efficiency of rock suffers from great influence.
The application considers the internal factor and external factor of expulsive efficiency, deeply dissects sedimentary facies and the difference side of burying
For persistently burying type, it is ripe to be divided into abundance of organic matter, organic matter type, organic matter by formula for the influence factor of expulsive efficiency
Degree, source storage four key parameters of configuration relation consider that abundance of organic matter, organic matter type, maturity of organic matter, source storage are matched respectively
Influence of the single geologic(al) factor of four kinds of relationship to expulsive efficiency is put, to establish single geologic(al) factor evaluation model, a variety of geologic(al) factors are commented
Valency expulsive efficiency model provides basis;
Using organic anisotropism logging evaluation technology, with reference to resistivity, acoustic travel time logging curve and actual measurement TOC numbers
According to, establish organic anisotropism Logging estimation model (Fig. 3, Fig. 4), evaluation analysis Qingshankou group TOC Vertical Distribution Characteristics (Fig. 5,
Fig. 6);The TOC data of the upper high-resolution (0.125m) in longitudinal direction are predicted according to resistivity and interval transit time log, in addition,
The influence of the expulsive efficiencies such as the type, maturity, the source storage configuration relation that are determined according to field data;
Since hydrocarbon source rock expulsive efficiency influence factor is very complicated, it is relatively difficult to study each influence factor, the application
By induction and conclusion, consider sedimentary facies and difference bury mode, for persistently burying type, by the influence of expulsive efficiency because
Element is divided into abundance of organic matter, organic matter type, maturity of organic matter, source storage four aspects of configuration relation.Organic matter is considered respectively
The influence of abundance, organic matter type, maturity of organic matter, source storage configuration relation list geologic(al) factor variable to expulsive efficiency, and build
Vertical single factor evaluation model finally establishes the evaluation model of a variety of geologic(al) factor evaluation expulsive efficiencies.
1), abundance of organic matter influences
Abundance of organic matter refers to the quantity of organic matter in unit mass rock.Differentiation abundance of organic matter index mainly has and always has
Machine carbon (TOC), hydrocarbon potentiality (S1+S2), chloroform bitumen " A " and total hydrocarbon.And the most commonly used is carry out table with total organic carbon (TOC, %)
Show.Due to the effect of hydrocarbon source rock row's hydrocarbon, the organic carbon for discharging hydro carbons is not included in the measured value of abundance of organic matter, so actual measurement
Abundance of organic matter can be less than organic matter original abundance.But if when other conditions are close, organic matter contains in hydrocarbon source rock
Amount is higher, and hydrocarbon source rock matrix is better, and hydrocarbon generation capacity is higher, and expulsive efficiency also can be bigger.
Green one section of Song-liao basin the north Qingshankou group abundance of organic matter is apparently higher than two or three sections of blueness, and one section of blueness is generally
The source rock of high organic abundance;Green two or three sections of top abundances of organic matter are low, and lower part is similar with one section green, higher, is in integrally
The process being now gradually reduced from down to up.From the individual well point of Ha18Jing, Jin88Jing, 12 well of English, 16 well of English, Mao206Jing, Xu11Jing
As can be seen that TOC has good correspondence, TOC increases with expulsive efficiency on analysis figure, expulsive efficiency increases therewith, and TOC subtracts
Small, expulsive efficiency also reduces therewith.The rule of Song-liao basin the north Qingshankou group expulsive efficiency and abundance of organic matter is coincide very
It is good, it is gradually reduced from top to bottom.And from Ha18Jing, Jin88Jing, 12 well of English, 16 well of English, Mao206Jing, Xu11Jing TOC with row hydrocarbon
It is also seen that expulsive efficiency is increased with the increase of TOC in the scatter plot of efficiency.
A M206 wells TOC and expulsive efficiency scatter plot;B H18 wells TOC and expulsive efficiency scatter plot;C X11 wells TOC and row
Hydrocarbon efficiency scatter plot;D J88 wells TOC and expulsive efficiency scatter plot;E Y12 wells TOC and expulsive efficiency scatter plot;F Y16 wells TOC
With expulsive efficiency scatter plot;(such as Fig. 7 to Figure 12)
2), organic matter type influences
Since different type Source Organic Matter, composition have a very big difference, different organic matters into hydrocarbon potentiality, into the hydrocarbon phase time,
It is also different into hydrocarbon products.Organic matter type weighs organic matter production hydrocarbon ability, while also determines that its product is based on oil, also
It is based on gas.The type of organic matter can both reflect by the composition characteristic of insoluble organic matter, can also be by its product-solvable
The feature of organic matter and wherein hydro carbons reflects.Pyrolysis data analysis is for elemental analysis, kerogen maceral analysis
Data are easier to obtain, and can include most of testing site.So the application divides organic matter class using IH-Tmax plates
Type, the type plate of Song-liao basin are as shown.
According to the expulsive efficiency that material balance method calculates, the relationship of different type organic matter and expulsive efficiency is analyzed, from fish
As can be seen that expulsive efficiency has good correspondence with organic matter type on the single well analysis figure of 15 wells, organic matter type is not
Good, expulsive efficiency is lower.In addition, between 2050-2060 meters of 16 well of English, expulsive efficiency is respectively present I type from top to down
55.87%- II1Type 51.65%- II2I type 56%- II of type 18%-1I types 57.62% of type 54.7%-.Both organic matter type was got over
Good, adjacent expulsive efficiency is higher, otherwise lower.15 well of fish is between 2040-2060 meters, the scatter plot of Ro and expulsive efficiency
(Figure 13), it can be seen from the figure that maturity has not been the principal element for the expulsive efficiency for influencing this section of mud stone, organic matter
Type is major control factors.Figure 13 is 15 well Ro of fish and the scatter plot of expulsive efficiency, is clear that from figure in phase
In the case of near maturity, type is better, and expulsive efficiency is higher.
The study found that when abundance of organic matter it is certain (0.5%~1.0%, 1.0%~2.0%, 2.0%~3.0%, >
3.0%) when, under conditions of identical maturity, the more good corresponding expulsive efficiency of organic matter type is higher, conversely, lower.
3), maturity of organic matter influences
For organic matter in continuous buried depth maturation, also constantly variation is occurring, and in certain ripe rank in itself
Start to generate oil gas after section.In order to weigh the degree that the variation degree of itself and organic matter are converted to oil gas, we will determine
Relevant mature indicator.As the index of maturity, just its organic matter must can be embodied in organic matter maturation evolutionary process
Some changing rules of itself, while the changing rule of its product can also be embodied.Due to the measure of vitrinite reflectance (Ro)
It is not influenced by organic matter composition transfer, there is good relationship between maturity of organic matter, measure is easier, as a result
It is more accurate, and with metastable comparativity, therefore be most widely used by the use of Ro as mature indicator.
The Song-liao basin Qingshankou group hydrocarbon source rock of the application is thicker, and maturity has certain variation, in different depth
The sample that section is taken out does Ro measuring reflectances, and combines other experimental analyses, such as divides TOC, pyrolysis, chloroform bitumen " A " extracting,
Study influence of the maturity to expulsive efficiency.
The expulsive efficiency analysis expulsive efficiency and the relationship of maturity calculated according to material balance method, Figure 14 to Figure 21 is profit
The relational graph up to 23 wells, the expulsive efficiency of luxuriant 206 well measured values and actual measurement Ro calculated with material balance method, can be bright from figure
Aobvious finds out, as maturity increases, expulsive efficiency increase.Figure 14 to Figure 21 is in different abundance of organic matter difference HI indexes
Under the conditions of the relational graph of maturity of organic matter and expulsive efficiency, it can be seen from the figure that when abundance of organic matter and HI indexes control
When a relatively small range, expulsive efficiency increases with the increase of maturity.4), storage configuration relation in source influences
Source storage configuration relation refers to hydrocarbon source rock with being distributed the integrated mode of sandstone therein, in general individual layer mud stone it is thinner,
The interaction of sand mud is more frequent, is more conducive to the discharge of hydro carbons, expulsive efficiency is higher.The storage configuration of Song-liao basin Qingshankou group hydrocarbon source rock source
Relationship mainly has 4 kinds of forms (being shown in Table 4), such as argillite, sandstone nested, finger-like interactive and mud stone nested.
Store up configuration relation in 4 hydrocarbon source rock source of table
Note:Lm- individual layer mud stone thickness, m;Ls1- upper strata the sandstone contacted with mud stone, m;Ls2- the lower floor contacted with mud stone
Sandstone, m;
To four kinds, the rock core of not homologous storage configuration carries out close sampling, and make corresponding geochemical analysis, and then the row of being obtained
Hydrocarbon efficiency, influence of the not homologous storage configuration relation of analysis to expulsive efficiency (see Figure 22 to Figure 25).
Primary Migration of Oil And Gas needs hydrocarbon source rock, and there are overpressure gradients with the external world.The hydrocarbon source rock of not homologous storage configuration relation
Pressure is distributed and row's hydrocarbon feature is all different.Mud stone nested has unified smaller Fluid pressure with finger-like interactive hydrocarbon source rock
Gradient constantly enhances with compaction, and mud stone particle is in close contact quickly, and hydro carbons can be to fully discharge, expulsive efficiency will up and down
More than sandstone nested and argillite.
From individual well section from Jin86Jing with 10 well of English, all there are expulsive efficiencies in the middle part of argillite to be less than edge and sand
The mud stone of lithofacies neighbour, sand and mud interstratification expulsive efficiency is 46.8% between 1900-1910 meters in golden 86 wells, and sandstone nesting is
Sand and mud interstratification expulsive efficiency 62.7%, mud stone nesting expulsive efficiency 67.1%, sandstone are nested between 30.7%, 1945-1950 meters
Expulsive efficiency 56.5%, mud stone nesting expulsive efficiency 71.5% both can be seen that expulsive efficiency mud stone nesting from Jin86Jing>Sand mud
Alternating layers>The edge for closing on sandstone in the middle part of sandstone nesting and argillite expulsive efficiency than edge is low, and Figure 26 is not homologous storage configuration
The mud stone maturity of organic matter of relationship and the relationship of expulsive efficiency, can also obtain viewpoint as above.2260- in 10 well of English
Sand and mud interstratification expulsive efficiency 69.2%, 5m mud stone expulsive efficiency 67.3%, mud stone nesting expulsive efficiency 73.5% between 2280 meters,
Sand and mud interstratification expulsive efficiency 71.8%, mud stone nesting expulsive efficiency 73.5%, sandstone nesting expulsive efficiency between 2280-2300 meters
Mud stone nesting expulsive efficiency 67.7%, sand and mud interstratification expulsive efficiency 66.1% between 69.7%, 2350-2370 meters.Both hydrocarbon effect had been arranged
Rate mud stone is nested>Sand and mud interstratification>Sandstone is nested>Argillite, and in the middle part of argillite expulsive efficiency sandstone is closed on than edge
Edge it is low.Figure 27 is the mud stone abundance of organic matter of not homologous storage configuration relation and the relational graph of expulsive efficiency, with view of the above
Unanimously.
Both sandstone nested and shale content in argillite were higher, and sedimentary particle is thinner, and depositional environment is better, organic
Matter abundance is high, and type is good, and expulsive efficiency is high.And in sand and mud interstratification and mud stone nested, shale content is higher, illustrates that mud stone becomes
More, insufficient contact with sandstone, expulsive efficiency is low.
Breathe out in 18 wells sandstone nesting expulsive efficiency 30.3%, mud alternating layers expulsive efficiency 56.3%, mud between 2025-2045 meters
Rock nesting expulsive efficiency 52%, both expulsive efficiency sand and mud interstratification>Sandstone is nested;1870-1885 meters of sand and mud interstratification row's hydrocarbon effects of 6 well suddenly
Rate 65.4%, mud stone nesting expulsive efficiency 73.6%, expulsive efficiency mud stone are nested>Sand and mud interstratification;Jin86Jing this it appears that
Expulsive efficiency is less than the expulsive efficiency of the edge mud stone close to sandstone in the middle part of argillite.
(4), single geologic(al) factor and expulsive efficiency evaluation model are established:Single geologic(al) factor and expulsive efficiency evaluation model are main
Expulsive efficiency and each single geologic(al) factor mathematical relationship are to determine, according to analysis is determined in step 3) abundance of organic matter, organic
The geologic(al) factors of matter type, maturity of organic matter and source storage four kinds of configuration relation influence expulsive efficiency, establish single geologic(al) factor with
The evaluation model of expulsive efficiency, quantitatively characterizing go out the logarithmic relationship evaluation model of abundance of organic matter and expulsive efficiency, organic matter class
The exponential relationship evaluation model of maturity and expulsive efficiency under type constraint, source store up the maturity of organic matter under configuration relation constraint
With the polynomial relation evaluation model of expulsive efficiency;
The abundance of organic matter that the application determines and expulsive efficiency single factor evaluation model formation (4-1) (Figure 28 to Figure 29)
For:
P=26.69 × ln (TOC)+29.45 (4-1)
Ro and expulsive efficiency single factor evaluation modular form (4-2) under the different organic matter types constraint that the application determines
For:
P=0.558 × exp (6.1 × RoKT)-30.85 (4-2)
The lower Ro of not homologous storage configuration relation constraint that the application determines and with expulsive efficiency single factor evaluation model (formula 4-
3) (Figure 30 and table 4) is:
P=-2258 × RoYCPZ×RoYCPZ+4660.68×RoYCPZ-2321 (4-3)
P represents hydrocarbon source rock expulsive efficiency in formula;TOC refers to abundance of organic matter;Ro(T)Refer to different kerogen type constraints
Under Ro and expulsive efficiency relationship in Ro, RoYCPZRefer in the Ro and expulsive efficiency relationship under not homologous storage configuration control
Ro。
The expulsive efficiency evaluation model of the not homologous storage configuration relation of table 5
(5), the mathematical model of more geologic(al) factors and expulsive efficiency is established:According to each single geologic(al) factor determined in step 4)
The data relationship of model, it is ensured that each geologic(al) factor contributes form, establishes the evaluation of more geologic(al) factors and hydrocarbon source rock expulsive efficiency
Model realizes more geologic(al) factor quantitative assessment expulsive efficiencies, and base is established to evaluate destination layer position hydrocarbon source rock three-dimensional expulsive efficiency
Plinth;
According to the data relationship of each single geologic(al) factor model determined in step 4), it is ensured that each geologic(al) factor contributes form
Accuracy, establish the evaluation model (formula 5-1) of more geologic(al) factors and hydrocarbon source rock expulsive efficiency, realize that more geologic(al) factors are quantitatively commented
Valency expulsive efficiency lays the foundation to evaluate destination layer position hydrocarbon source rock three-dimensional expulsive efficiency;A variety of geologic(al) factor evaluation row hydrocarbon effects
Rate mathematical model is:
P=PNY×PWY
=0.93 × (1.92 × ln (TOC)+28.13 × exp (RoK, T)-61.72)
×(-5.6×RoYCPZ×RoYCPZ-0.895×RoYCPZ+ 8.03) formula (5-1)
In formula:P represents expulsive efficiency, PNYRepresent expulsive efficiency influnecing factor, PWYRepresent expulsive efficiency external action
Factor;TOC refers to abundance of organic matter;(RoK,T) refer to the relationship of Ro and expulsive efficiency under different kerogen type constraints;
IDYCPZRefer to the relationship of the Ro and expulsive efficiency under not homologous storage configuration constraint;
Table geologic(al) factor more than 6 and hydrocarbon source rock expulsive efficiency relationship statistical form
(6), research area destination layer position hydrocarbon source rock three-dimensional expulsive efficiency is evaluated:The net of 5km × 5km is established in research area
Lattice are selected in each grid and represent well flatly, establish organic anisotropism Logging estimation model, obtain longitudinal continuity from above
TOC;Simultaneously according to hydrocarbon source rock sedimentary facies distribution, different type hydrocarbon source rock is determined;Determine hydrocarbon source rock maturation evolution condition and source
Store up syntagmatic;According to the more geologic(al) factor expulsive efficiency evaluation models determined in step 5), research area's geology extrapolation, knot are carried out
The high-resolution expulsive efficiency in longitudinal direction of multiple wells (Figure 31) is closed, establishes out research area three-dimensional expulsive efficiency geologic body, establishment row
Hydrocarbon efficiency plane figure (Figure 32), prediction unconventionaloil pool Favorable Areas.
Expulsive efficiency is all most important for conventional and unconventional oil-gas exploration, for conventional gas and oil exploration, hydrocarbon
The oil gas of source rock generation can just contribute to the Gas Accumulation and Cheng Zang in later stage after only discharging;Shale oil gas is come
It says, the oil gas only remained in shale is more than enough could to form shale oil-gas reservoir.Thus, research hydrocarbon source rock expulsive efficiency has non-
Often big value.
Embodiment 3:A kind of more geologic(al) factor quantitative assessment hydrocarbon source rock expulsive efficiency methods, include the following steps:
1) data, is compiled:Geochemical data, log data, well-log information and the geologic information in collection research area;
Wherein, geochemical data includes rock pyrolysis analysis test data, chloroform bitumen " A " analyzing test data, organic carbon analysis
Test data, kerogen microscopy;Well-log information includes natural gamma, interval transit time, microelectrode, micronormal, deep lateral and shallow side
To grade logs;Log data includes landwaste and log data;Geologic information includes deposition phase-plane diagram;
2) a kind of hydrocarbon source rock expulsive efficiency evaluation method, is established:Rely on component hydrocarbon-generating dynamics, PYGC data, the world
Popular PetroMod2014 editions hydrocarbon model sample component data and thermal simulation experiment data establish a kind of based on lighter hydrocarbons recovery
With the expulsive efficiency evaluation method of life residence thermal simulation experiment data, the expulsive efficiency data evaluated with reference to hydrocarbon potentiality method and
Expulsive efficiency measured data, three kinds of method overall merits go out destination layer position hydrocarbon source rock expulsive efficiency;
However the expulsive efficiency only row's hydrocarbon situation at the next well point of geological conditions, it represents research area and integrally arranges hydrocarbon effect
Rate there is some difference property, and study and find that expulsive efficiency is influenced by a variety of geologic(al) factors, thus it is necessary to establish geologic(al) factor
With the quantitative assessment relationship of expulsive efficiency, the evaluation model of more geologic(al) factors and expulsive efficiency is finally established out, to study area three
Dimension expulsive efficiency evaluation lays the foundation;
3) influence factor of expulsive efficiency, is filtered out:The hydrocarbon expulsion process of hydrocarbon source rock is that various complicated geological combined factors are made
As a result, be a complicated geological process, many because being known as of expulsive efficiency are influenced, the internal factor including hydrocarbon source rock,
Such as organic matter type, abundance of organic matter, maturity of organic matter;Also include some external factor simultaneously, such as hydrocarbon source rock inner pore, split
Seam, rock texture, internal pressure, formation temperature, interfacial tension, capillary pressure, specific surface etc.;Both factors are to hydrocarbon source
The expulsive efficiency of rock suffers from great influence.
The application considers the internal factor and external factor of expulsive efficiency, deeply dissects sedimentary facies and the difference side of burying
For persistently burying type, it is ripe to be divided into abundance of organic matter, organic matter type, organic matter by formula for the influence factor of expulsive efficiency
Degree, source storage four key parameters of configuration relation consider that abundance of organic matter, organic matter type, maturity of organic matter, source storage are matched respectively
Influence of the relationship single-factor variable to expulsive efficiency is put, to establish single factor evaluation model, a variety of geologic(al) factors evaluation row's hydrocarbon effect
Rate model provides basis;
Using organic anisotropism logging evaluation technology, with reference to resistivity, acoustic travel time logging curve and actual measurement TOC numbers
According to establishing organic anisotropism Logging estimation model;The upper high score in longitudinal direction is predicted according to resistivity and interval transit time log
The TOC data of resolution (0.125m), in addition, row's hydrocarbon effect such as the type determined according to field data, maturity, source storage configuration relation
The influence of rate;
4) single geologic(al) factor and expulsive efficiency evaluation model, are established:Single geologic(al) factor and expulsive efficiency evaluation model are main
Expulsive efficiency and each single geologic(al) factor mathematical relationship are to determine, according to analysis is determined in step 3) abundance of organic matter, organic
The geologic(al) factors of matter type, maturity of organic matter and source storage four kinds of configuration relation influence expulsive efficiency, establish single geologic(al) factor with
The evaluation model of expulsive efficiency, quantitatively characterizing go out the logarithmic relationship evaluation model of abundance of organic matter and expulsive efficiency, organic matter class
The exponential relationship evaluation model of maturity and expulsive efficiency under type constraint, source store up the maturity of organic matter under configuration relation constraint
With the polynomial relation evaluation model of expulsive efficiency;
5) mathematical model of more geologic(al) factors and expulsive efficiency, is established:According to each single geologic(al) factor determined in step 4)
The data relationship of model, it is ensured that each geologic(al) factor contributes form, establishes the evaluation of more geologic(al) factors and hydrocarbon source rock expulsive efficiency
Model realizes more geologic(al) factor quantitative assessment expulsive efficiencies, and base is established to evaluate destination layer position hydrocarbon source rock three-dimensional expulsive efficiency
Plinth;
6) research area destination layer position hydrocarbon source rock three-dimensional expulsive efficiency, is evaluated:The grid of 5km × 5km is established in research area,
It is selected in each grid and represents well flatly, establish organic anisotropism Logging estimation model, obtain the TOC of longitudinal continuity from above;
Simultaneously according to hydrocarbon source rock sedimentary facies distribution, different type hydrocarbon source rock is determined;Determine hydrocarbon source rock maturation evolution condition and source storage group
Conjunction relationship;According to the more geologic(al) factors evaluation expulsive efficiency model determined in step 5), the well screened is arranged
Hydrocarbon efficiency rating geology is extrapolated, the high-resolution expulsive efficiency in longitudinal direction based on multiple wells, establishes out research area three-dimensional row's hydrocarbon effect
Rate geologic body works out expulsive efficiency plan view, prediction and conventional unconventionaloil pool Favorable Areas.
The application based on component hydrocarbon-generating dynamics, PYGC data, international popular hydrocarbon model, thermal simulation experiment data and
Pyrolysis Experiment data, using expulsive efficiency evaluation method, the hydrocarbon potentiality method restored based on lighter hydrocarbons with life residence thermal simulation experiment
With the 3 aspect expulsive efficiency data such as life residence measured data, hydrocarbon source rock expulsive efficiency of accurately grading out;Consider to influence hydrocarbon source rock
The internal factor and external factor of expulsive efficiency, analyse in depth sedimentary facies and deposition buries method, filter out abundance of organic matter, have
Machine matter type, maturity of organic matter and source storage configuration relation four key parameters are established expulsive efficiency and are determined with list geologic(al) factor
Measure evaluation model;By means of expulsive efficiency and the mathematical relationship of each single factor test, i.e., contribution of each single geologic(al) factor to expulsive efficiency
Form establishes a variety of geologic(al) factor evaluation expulsive efficiency models, realizes a variety of geologic(al) factor quantitative assessment expulsive efficiencies.
A kind of expulsive efficiency evaluation method restored based on lighter hydrocarbons with life residence thermal simulation experiment is established in the step 2),
Expulsive efficiency 4 steps of evaluation of programme point, specific steps (Figure 33) are as follows:
1), thermal simulation experiment designs:Acquisition research area destination layer position source rock sample (TOC>0.5%, maturity Ro<
0.5%) rock direct press type thermal simulation experiment, is designed;
2), expulsive efficiency evaluation model:Based on rock direct press type thermal simulation experiment data, expulsive efficiency P is evaluated.Due to
Light hydrocarbon component C in extractive process6-14Loss, the expulsive efficiency P that experimental data determines is than practical expulsive efficiency P0(i.e. handle bigger than normal
Loss amount is calculated as a part for discharge rate), thus it is necessary to lighter hydrocarbons part is restored;
3), lighter hydrocarbons restoration evaluation model:Based on 33 pieces of the hydrocarbon model sample number of components of international popular PetroMod2014 editions
According to reference to domestic 50 pieces of experimental datas of PY-GC thermal simulations hydrocarbon sample, data mode is C14+、C6-14、C5-1Three kinds of component shapes
Formula establishes lighter hydrocarbons recovery coefficient evaluation of programme, evaluates lighter hydrocarbons correction coefficient KLighter hydrocarbons recovery coefficient;It corrects out in extractive process and loses
Light hydrocarbon component C6-14, evaluate expulsive efficiency P0;
4) a kind of expulsive efficiency evaluation method, is established:Lighter hydrocarbons recovery coefficient based on expulsive efficiency in step 3)
KLighter hydrocarbons recovery coefficient, have determined expulsive efficiency P with reference to step 2), evaluate hydrocarbon source rock expulsive efficiency P0。
The expulsive efficiency correction coefficient K of different type organic matter is found by the applicationJZWith maturity and Kerogen type
It is related, increase with maturity with increased rule after first reducing;By I types, II1Type, II2Recovery coefficient when type, type III variation
KJZGradually increase (Figure 34).
The evaluation principle of expulsive efficiency model is as follows:
This method includes the expulsive efficiency model established according to direct press type thermal simulation experiment data and international popular
The lighter hydrocarbons that 33 pieces of component data of PetroMod2014 editions hydrocarbon model samples and domestic 50 pieces of PY-GC thermal simulation hydrocarbons data are established
Recovery coefficient model.Wherein, when extracting residual hydrocarbons during direct press type thermal simulation experiment, C6-14Lighter hydrocarbons partial loss, causes
The expulsive efficiency directly gone out using direct press type thermal simulation experiment data evaluation is higher, using PetroMod2014 editions lifes of international popular
33 pieces of component data of hydrocarbon model sample and domestic 50 pieces of PY-GC thermal simulation hydrocarbon data establish C6-14Lighter hydrocarbons recovery coefficient evaluation side
Case has obtained I type, II1Type, II2The lighter hydrocarbons recovery coefficient of type, III type expulsive efficiency establishes different type row's hydrocarbon of complete set
Efficiency model.
1), expulsive efficiency evaluation model is established according to direct press type thermal simulation experiment data
According to direct press type thermal simulation experiment data (discharge oil, oil residues, discharge gas and residue gas), establish a kind of using straight
The judgement schematics of the semi-open semiclosed thermal simulation experiment data evaluation expulsive efficiency P of pressure type.
Expulsive efficiency P evaluation models, it is as follows:
Formula (2-1) has ignored the loss of lighter hydrocarbons in residual hydrocarbons extractive process, thus, it is necessary to take into account residual hydrocarbons extractive process
The light hydrocarbon component C6-14 of middle loss is established and is met theoretical expulsive efficiency evaluation model P0.
Expulsive efficiency P0 evaluation models are:
In formula (2-2), Q1For discharge oil;Q2For oil residues;Q3To discharge gas;Q4For residue gas;Expulsive efficiency P is vertical compression
Formula thermal simulation experiment data directly evaluate the expulsive efficiency of acquisition;KJZLighter hydrocarbons recovery coefficient for expulsive efficiency P;Expulsive efficiency P0
For the expulsive efficiency after correction.
Experimental defects:When measuring residual hydrocarbons, light hydrocarbon component C6-13Loss.The application uses international popular PetroMod2014
Version 33 pieces of component data of hydrocarbon model sample and the 50 pieces of PY-GC thermal simulation hydrocarbon data (C in the country1-5、C6-13、C14+), to vertical compression
The light hydrocarbon component lost in formula thermal simulation experiment is corrected, so as to achieve the purpose that correct expulsive efficiency.
2) the lighter hydrocarbons calibration model of four kinds of Types of hydrocarbon source rock, is established
However KJZIt is generally difficult to obtain during the experiment, PetroMod2014 editions hydrocarbons of international popular is based in this research
33 pieces of component data of model sample with reference to domestic 50 pieces of PY-GC thermal simulations hydrocarbon sample, establish I type, II1Type, II2Type, III
(approximation replaces K to the lighter hydrocarbons recovery coefficient of type expulsive efficiencyJZ), judgement schematics (2-3) are
Formula (2-3) is brought into formula (2-2), obtains formula (2-4).
In practical expulsive efficiency evaluation, combinatorial formula (2-2) and (2-3) obtain expulsive efficiency POJudgement schematics (2-4),
Complete expulsive efficiency appraisal.
In the step 2), a variety of expulsive efficiency evaluation methods establish out accurate expulsive efficiency, specific as follows:
With 1976.99 meter II of neat family's Cologne recess J88 wells1For type mud stone direct press type thermal simulation experiment.Sample it is specific
Geochemical Parameters are shown in Table 7, and thermal simulation hydrocarbon experimental data is shown in Table 8.
The Basic Geological Geochemical Characteristics of 7 simulated experiment used sample of table
The northern golden 88 well Qingshankou group Dark grey mud stone direct press type thermal simulation experiment results of 8 Song-liao basin of table
J88 well 1976.99m II are directly evaluated using direct press type thermal simulation experiment data1The expulsive efficiency of type mud stone,
The loss of lighter hydrocarbons when having ignored extracting residual hydrocarbons so that the expulsive efficiency evaluated is bigger than normal.Thus, using lighter hydrocarbons recovery coefficient figure
II in version1Type recovery coefficient is corrected, the expulsive efficiency P after being corrected0。
Expulsive efficiency correction considers direct press type thermal simulation experiment condition, corrects out the lighter hydrocarbons lost during extracting residual hydrocarbons
Part evaluates the expulsive efficiency for being more in line with practical geological conditions.Result after correction is than directly using direct press type thermal simulation
Quality evaluation of the experimental data is more in line with geological knowledge, and difference reaches 20% before and after expulsive efficiency correction.Consider hydrocarbon potentiality
Method and measured data data, evidence thermal simulation experiment method evaluate the accuracy of hydrocarbon source rock expulsive efficiency.On this basis, it provides
The final expulsive efficiency of Qingshankou group hydrocarbon source rock.
In the step 4), single geologic(al) factor and expulsive efficiency evaluation model are established, obtains single geologic(al) factor and row's hydrocarbon effect
Rate mathematical relationship, it is specific as follows:
Using organic anisotropism logging evaluation technology, joint resistance rate log, acoustic travel time logging curve and reality
TOC data are surveyed, evaluate the TOC data points of the upper high resolution (0.125) in longitudinal direction, it is determined that abundance of organic matter and expulsive efficiency
Logarithmic relationship evaluation model (formula 4-1):
P=a × ln (TOC)+b formulas (4-1)
The abundance of organic matter that the application determines is with expulsive efficiency single factor evaluation model formation (4-2):
+ 29.45 formulas (4-2) of P=26.69 × ln (TOC)
The exponential relationship evaluation model formula (4-3) for establishing Ro and expulsive efficiency under the constraint of different organic matter types is,
P=a × exp (b × RoKT)-c formulas (4-3)
Ro and expulsive efficiency single factor evaluation modular form (4-4) under the different organic matter types constraint that the application determines
For:
P=0.558 × exp (6.1 × RoKT) -30.85 formulas (4-4)
Establish the exponential relationship evaluation model (formula 4-5) of the Ro and expulsive efficiency under not homologous storage configuration relation constraint
For,
P=a × RoYCPZ+b×RoYCPZ+ c formulas (4-5)
The lower Ro of not homologous storage configuration relation constraint that the application determines and with expulsive efficiency single factor evaluation model (formula 4-
6) (table 9) is:
P=-2258 × RoYCPZ×RoYCPZ+4660.68×RoYCPZ- 2321 formulas (4-6)
P represents hydrocarbon source rock expulsive efficiency in formula;TOC refers to abundance of organic matter;Ro(T)Refer to different kerogen type constraints
Under Ro and expulsive efficiency relationship in Ro, RoYCPZRefer in the Ro and expulsive efficiency relationship under not homologous storage configuration control
Ro。
The expulsive efficiency evaluation model of the not homologous storage configuration relation of table 9
In the step 5), a variety of geologic(al) factors and expulsive efficiency mathematics appraisal are established, it is specific as follows:
Considering influences the internal factor and external factor of hydrocarbon source rock expulsive efficiency, is determined in support step 2) organic
The logarithmic relationship of matter abundance and expulsive efficiency, the exponential relationship of the maturity under organic matter type constraint and expulsive efficiency, source are stored up
The polynomial relation of maturity of organic matter and expulsive efficiency under configuration relation constraint;Establish a variety of geologic(al) factors and expulsive efficiency
Evaluation model (formula 5-1), realize a variety of geologic(al) factor quantitative assessment hydrocarbon source rock expulsive efficiencies;
P=PNY×PWY
=(f (TOC)+f (RoKT×f(RoYCPZ) formula (5-1)
In formula:P represents expulsive efficiency, PNYRepresent expulsive efficiency influnecing factor, PWYRepresent expulsive efficiency external action
Factor;
Table geologic(al) factor more than 10 and hydrocarbon source rock expulsive efficiency relationship statistical form
A variety of geologic(al) factors evaluate expulsive efficiency mathematical model:
P=PNY×PWY
=0.93 × (1.92 × ln (TOC)+28.13 × exp (RoKT)-61.72)
×(-5.6×RoYCPZ×RoYCPZ-0.895×RoYCPZ+ 8.03) formula (5-2)
In formula:P represents expulsive efficiency, PNYRepresent expulsive efficiency influnecing factor, PWYRepresent expulsive efficiency external action
Factor;TOC refers to abundance of organic matter, and (Ro, T) refers to the Ro, ID under different kerogen type constraintsYCPZRefer to that not homologous storage is matched
Put the relationship of the Ro and expulsive efficiency under constraint;
According to the data relationship of each single geologic(al) factor model determined in step 3), it is ensured that each geologic(al) factor contributes form
Accuracy, establish the evaluation model (formula 5-2) of more geologic(al) factors and hydrocarbon source rock expulsive efficiency, realize that more geologic(al) factors are quantitatively commented
Valency expulsive efficiency lays the foundation to evaluate destination layer position hydrocarbon source rock three-dimensional expulsive efficiency.
As described above, the embodiment of the present invention is explained in detail, as long as but essentially without this hair of disengaging
Bright inventive point and effect can have many deformations, this will be readily apparent to persons skilled in the art.Therefore, this
The variation of sample is also integrally incorporated within protection scope of the present invention.