CN105243204A

CN105243204A - Method for multi-geological factor quantitative evaluation of hydrocarbon expulsion efficiency

Info

Publication number: CN105243204A
Application number: CN201510626815.5A
Authority: CN
Inventors: 王文广; 王民; 郑民; 卢双舫; 薛海涛; 田善思
Original assignee: Individual
Current assignee: China University of Petroleum East China
Priority date: 2015-09-28
Filing date: 2015-09-28
Publication date: 2016-01-13
Anticipated expiration: 2035-09-28
Also published as: CN105243204B

Abstract

Provided is a method for multi-geological factor quantitative evaluation of hydrocarbon expulsion efficiency, which belongs to the technical field of evaluation and analysis of oil and gas resources. The method comprises: establishing a light hydrocarbon recovery factor model, so as to reduce light hydrocarbon loss in a hydrocarbon generation and expulsion thermal simulation test; in addition, accurately evaluating hydrocarbon expulsion efficiency of typical wells in combination with a hydrocarbon generation potential method and a practically measured value of hydrocarbon generation and expulsion; screening out factors influencing hydrocarbon expulsion efficiency: 1) comprehensively considering internal factors and external factors influencing hydrocarbon expulsion efficiency; 2) screening out four geological factors: organic matter abundance, an organic matter type, organic matter maturity and a source-reservoir configuration relationship; 3) establishing a model relationship between a single geological factor and hydrocarbon expulsion efficiency, and a model relationship between multiple geological factors and hydrocarbon expulsion efficiency; and 4) popularizing and applying an evaluation model for multi-geological factor quantitative evaluation of hydrocarbon expulsion efficiency on the plane, so as to obtain a plane distribution diagram of hydrocarbon expulsion efficiency of hydrocarbon source rocks by evaluation, explain distribution characteristics of conventional and unconventional oil and gas, and point out conventional and unconventional oil and gas enrichment regions.

Description

A kind of many geologic agents quantitative evaluation expulsive efficiency method

Technical field

The present invention relates to a kind of many geologic agents quantitative evaluation expulsive efficiency method, belong to oil and gas resource evaluation analysis technical field.

Background technology

Oil gas will be gathered into conventional gas and oil and hide, and first will migrate out from hydrocarbon source rock, the primary migration of oil gas be the first step of whole oil-gas migration.The meaning of expulsive efficiency be exactly the migration efficiency of oil gas in hydrocarbon source rock and from hydrocarbon source rock to the efficiency of delivery layer, reservoir migration.The hydrocarbon expulsion process of hydrocarbon source rock is the result of various complicated geological combined factors effect, it is a complicated geological process, affect a lot of because have of expulsive efficiency, comprise the internal factor of hydrocarbon source rock, as organic matter type, abundance of organic matter, maturity of organic matter, also comprise some external factor, as hydrocarbon source rock inner pore, crack, rock texture, internal pressure, formation temperature, interfacial tension, capillary pressure, specific surface etc. simultaneously.The expulsive efficiency of these two kinds of factors on hydrocarbon source rock has great impact.

About hydrocarbon source rock expulsive efficiency, forefathers have carried out comparatively deep research to expulsive efficiency, put it briefly and comprise following 8 kinds of methods: residual hydrocarbons amount method, multi-phase porous flow theory method, hydrocarbon saturation method, geologic analogy method, original raw hydrocarbon potentiality restoring method, evolution trend face minusing, raw hydrocarbon potentiality method, material balance method.But various method has its respective shortcoming, the shortcoming as residual hydrocarbons amount method is exactly main still empirically for the linear relationship slope K e value between residual hydrocarbons and Hydrocarbon yield; As long as and think just there is the existence having residual hydrocarbons corresponding discharge, and do not consider whether reach critical hydrocarbon exhaust condition etc.; The shortcoming of multi-phase porous flow theory method is that the minimum critical saturation (S) of hydrocarbon is generally all greater than 20%, and therefore in the case, it is just very difficult etc. to discharge hydrocarbon in a large number; Hydrocarbon saturation method mainly supposes that in hydrocarbon source rock displacement fluids, hydrocarbon saturation is identical with the hydrocarbon saturation of fluid in hydrocarbon source rock, but this hypothesis has no basis; Geologic analogy method hypothesis Hydrocarbon yield is geologic reserve, but much less than actual discharge rate of resource evaluation geologic reserve out; Raw hydrocarbon thermal simulation experiment method needs to carry out simulating hydrocarbons expulsion experiment, measures the residual hydrocarbons of analog sample and discharges hydrocarbon amount, but row's hydrocarbon mechanism is different from actual geology, and lighter hydrocarbons loss is not considered; Raw hydrocarbon potentiality method needs to adopt actual measurement hydrocarbon source rock geochemistry data, but the nonuniformity of hydrocarbon source rock is strong, and measuring sample will have certain specific aim, meet and distribute just very much, and oil gas cannot separate; Material balance method mainly utilizes chemical dynemics (or thermal simulation experiment method) to calculate the raw hydrocarbon amount of hydrocarbon source rock, the residual hydrocarbons amount of hydrocarbon source rock is obtained again by the method that geochemical logging, logging evaluation, sample analysis combine, Hydrocarbon yield is obtained by the difference of raw hydrocarbon amount and residual hydrocarbon amount, namely Hydrocarbon yield obtains expulsive efficiency than upper raw hydrocarbon amount, the advantage of the method is that of avoiding and directly describes the hydrocarbon expulsion process of complexity, shortcoming is that evaluation procedure is too complicated, in evaluation procedure, any one walks out of existing error, all can affect expulsive efficiency; Evolution trend face minusing is difficult to determine whether hydrocarbon source rock does not arrange hydrocarbon.By contrast, needed for original raw hydrocarbon potentiality restoring method, raw hydrocarbon potentiality method and these 3 kinds of methods of material balance method, basic data easily obtains, and can avoid complicated hydrocarbon expulsion process, is also the method for the calculating expulsive efficiency that we commonly use.

Generally speaking, above-mentioned 8 kinds of methods all need the defect of great many of experiments analyzing test data or experimentation cycle of operation length, virtually add scientific research cost and the scientific research cycle of operation, and do not consider that hydrocarbon source rock expulsive efficiency affects by multiple geologic agent, as abundance of organic matter, type, degree of ripeness, source rock thickness, source storage configuration relation, sedimentary facies and tectonic evolution pattern, and there is certain error in the expulsive efficiency under experimental data and geologic condition.

And deepen along with the degree of prospecting in ripe prospect pit district, current expulsive efficiency evaluation method can not meet the demand of current exploration intensity, needs badly to explore a kind ofly to facilitate feasible, quickness and high efficiency, expulsive efficiency evaluation method easy to utilize.

Summary of the invention

In order to overcome the deficiencies in the prior art, thus, the present invention proposes a kind of many geologic agents quantitative evaluation expulsive efficiency method, convenient and swift, can plane apply, current exploration knowledge and available data can be utilized, quantitative evaluation goes out every mouthful of well destination layer position hydrocarbon source rock longitudinally high continuous print expulsive efficiency, in conjunction with many mouthfuls of drilling datas in plane, set up out the hydrocarbon source rock expulsive efficiency said three-dimensional body meeting accuracy requirement.

A kind of many geologic agents quantitative evaluation expulsive efficiency method, containing following steps;

Step 1), set up a kind of expulsive efficiency evaluation method based on life residence thermal simulation experiment, set up lighter hydrocarbons coefficient of restitution evaluation model simultaneously, solve the lighter hydrocarbons lost in life residence thermal simulation experiment; In addition, the expulsive efficiency evaluated in conjunction with raw hydrocarbon potentiality method and life residence measured value, evaluate the expulsive efficiency of typical well exactly;

Step 2), filter out the influence factor of expulsive efficiency: consider the internal factor and external factor that affect expulsive efficiency; Hydrocarbon source rock influnecing factor, considers organic matter type, abundance of organic matter, maturity of organic matter, hydrocarbon source rock external factor, considers hydrocarbon source rock inner pore, crack, rock texture, internal pressure, formation temperature, interfacial tension, capillary pressure, specific surface; Comprehensive sedimentary facies and bury mode, filters out abundance of organic matter, organic matter type, maturity of organic matter and source storage configuration relation 4 kinds of factors;

Step 3), set up single geologic agent of expulsive efficiency and the relationship model of expulsive efficiency: consider the internal factor and external factor that affect hydrocarbon source rock expulsive efficiency, filter out organic matter type, abundance of organic matter, maturity of organic matter and source storage configuration relation four key parameters, pass through abundance of organic matter, organic matter type, configuration relation factor is stored up in maturity of organic matter and source and expulsive efficiency mathematical relation is analyzed, determine the logarithmic relationship of abundance of organic matter and expulsive efficiency, degree of ripeness under organic matter type constraint and the exponential relationship of expulsive efficiency, maturity of organic matter under the constraint of source storage configuration relation and the polynomial relation of expulsive efficiency,

Step 4), set up the evaluation model of many geologic agents and expulsive efficiency: determine the logarithmic relationship of abundance of organic matter and expulsive efficiency, organic matter type retrain under degree of ripeness and the exponential relationship of expulsive efficiency, source store up configuration relation retrain under maturity of organic matter and the polynomial relation of expulsive efficiency, namely this single geologic agent is to the contribution rate of expulsive efficiency; Adopt curve fitting software, set up out based on single factor evaluation model, meet geological knowledge, many geologic agents quantitative evaluation expulsive efficiency evaluation model of meeting geologic rule;

Step 5), adopt many geologic agents quantitative evaluation expulsive efficiency evaluation model to apply in the plane, evaluate hydrocarbon source rock expulsive efficiency flat distribution map, set forth distribution characteristics that is conventional and unconventionaloil pool, point out conventional and unconventionaloil pool enrichment region.

Advantage of the present invention is:

Advantage of the present invention takes full advantage of available data, overcome evaluation expulsive efficiency in the past and need unconfined experiment drawback, plan defines a kind of many geologic agents quantitative evaluation expulsive efficiency method, the evaluation of realize target layer position hydrocarbon source rock expulsive efficiency said three-dimensional body, conventional with the preferred evaluation method of unconventionaloil pool favo(u)rable target in having enriched In Oil Field Exploration And Development perfect, obtain the accreditation of field operations personnel.

Accompanying drawing explanation

When considered in conjunction with the accompanying drawings, by referring to detailed description below, more completely can understand the present invention better and easily learn wherein many adjoint advantages, but accompanying drawing described herein is used to provide a further understanding of the present invention, form a part of the present invention, schematic description and description of the present invention, for explaining the present invention, does not form inappropriate limitation of the present invention, as schemed wherein:

Fig. 1 is structural representation of the present invention;

Fig. 2 is three kinds of Data Source comprehensive evaluation J88 wells, 1976.99 meters of mud stone expulsive efficiency figure.

Fig. 3 is one of Song-liao basin northern Qingshankou group TOC logging evaluation model;

Fig. 4 is two models of Song-liao basin northern Qingshankou group TOC logging evaluation;

Fig. 5 is northern Qingshankou group TOC histogram (golden 88 well overall efficiency figure-modeling figure) of Song-liao basin;

Fig. 6 is northern Qingshankou group TOC histogram (golden 87 well resultant effect figure-proof diagrams) of Song-liao basin;

Fig. 7 is that one of TOC and expulsive efficiency relation scheme;

Fig. 8 is two figure of TOC and expulsive efficiency relation;

Fig. 9 is three figure of TOC and expulsive efficiency relation;

Figure 10 is four figure of TOC and expulsive efficiency relation;

Figure 11 is five figure of TOC and expulsive efficiency relation;

Figure 12 is six figure of TOC and expulsive efficiency relation;

Figure 13 is hydrocarbon source rock maturity of organic matter and expulsive efficiency graph of a relation;

Figure 14 is different abundance of organic matter, one of maturity of organic matter and expulsive efficiency relation are schemed under different HI index conditions;

Figure 15 is two figure of maturity of organic matter and expulsive efficiency relation under different abundance of organic matter, different HI index conditions;

Figure 16 is three figure of maturity of organic matter and expulsive efficiency relation under different abundance of organic matter, different HI index conditions;

Figure 17 is four figure of maturity of organic matter and expulsive efficiency relation under different abundance of organic matter, different HI index conditions;

Figure 18 is five figure of maturity of organic matter and expulsive efficiency relation under different abundance of organic matter, different HI index conditions;

Figure 19 is six figure of maturity of organic matter and expulsive efficiency relation under different abundance of organic matter, different HI index conditions;

Figure 20 is seven figure of maturity of organic matter and expulsive efficiency relation under different abundance of organic matter, different HI index conditions;

Figure 21 is eight figure of maturity of organic matter and expulsive efficiency relation under different abundance of organic matter, different HI index conditions;

Figure 22 is one of source storage configuration relation sampling design figure;

Figure 23 is two figure of source storage configuration relation sampling design;

Figure 24 is three figure of source storage configuration relation sampling design;

Figure 25 is four figure of source storage configuration relation sampling design;

Figure 26 is mud stone maturity of organic matter and the expulsive efficiency graph of a relation of not homology storage configuration relation;

Figure 27 is mud stone abundance of organic matter and the expulsive efficiency graph of a relation of not homology 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 homology storage configuration relation

Figure 31 be in study area expulsive efficiency extrapolation select well flat distribution map;

Figure 32 is expulsive efficiency flat distribution map in study area;

Figure 33 is that expulsive efficiency evaluation of programme divides 4 block diagram;

Figure 34 is dissimilar hydrocarbon source rock expulsive efficiency correction coefficient K _jZ.

Below in conjunction with drawings and Examples, the present invention is further described.

Embodiment

Obviously, the many modifications and variations that those skilled in the art do based on aim of the present invention belong to protection scope of the present invention.

Embodiment 1: as shown in Figure 1, Figure 2, shown in Fig. 3, Fig. 4, Fig. 5, Fig. 6, Fig. 7, Fig. 8, Fig. 9, Figure 10, Figure 11, Figure 12, Figure 13, Figure 14, 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 29, Figure 30, Figure 31, Figure 32, Figure 33, Figure 34

A kind of many geologic agents quantitative evaluation hydrocarbon source rock expulsive efficiency method, comprises the following steps:

A, compile data: the geochemical data in collection research district, log data, well-log information and geologic information; Wherein, geochemical data comprises rock pyrolysis analysis test data, chloroform bitumen " A " analyzing test data, organic carbon analysis test data, kerogen microscopy; Well-log information comprises natural gamma, interval transit time, microelectrode, micronormal, the dark logging trace such as side direction and shallow side direction; Log data comprises landwaste and log data; Geologic information comprises sedimentary facies planimetric map;

B, set up a kind of hydrocarbon source rock expulsive efficiency evaluation method: rely on component hydrocarbon-generating dynamics, PYGC data, the raw hydrocarbon model sample component data of international popular PetroMod2014 version and thermal simulation experiment data, establish and a kind ofly to recover and the expulsive efficiency evaluation method of life residence thermal simulation experiment data based on lighter hydrocarbons, the expulsive efficiency evaluated in conjunction with raw hydrocarbon potentiality method and expulsive efficiency measured data, three kinds of method comprehensive evaluations go out destination layer position hydrocarbon source rock expulsive efficiency;

But row's hydrocarbon situation at this expulsive efficiency only next well point place of geologic condition, represent the overall expulsive efficiency in study area there is some difference property, and research finds that expulsive efficiency affects by multiple geologic agent, thus the quantitative evaluation relation setting up geologic agent and expulsive efficiency is necessary, the final evaluation model setting up out many geologic agents and expulsive efficiency, for the three-dimensional expulsive efficiency evaluation in study area lays the foundation;

C, filter out the influence factor of expulsive efficiency: the hydrocarbon expulsion process of hydrocarbon source rock is the result of various complicated geological combined factors effect, it is a complicated geological process, affect a lot of because have of expulsive efficiency, comprise the internal factor of hydrocarbon source rock, as organic matter type, abundance of organic matter, maturity of organic matter; Also comprise some external factor, as hydrocarbon source rock inner pore, crack, rock texture, internal pressure, formation temperature, interfacial tension, capillary pressure, specific surface etc. simultaneously; The expulsive efficiency of these two kinds of factors on hydrocarbon source rock has great impact.

The application considers internal factor and the external factor of expulsive efficiency, deeply anatomy sedimentary facies and difference bury mode, to continue to bury type, the influence factor of expulsive efficiency is divided into abundance of organic matter, organic matter type, maturity of organic matter, source storage configuration relation four key parameters, consider that abundance of organic matter, organic matter type, maturity of organic matter, source storage configuration relation single-factor variable are on the impact of expulsive efficiency respectively, for setting up single geologic agent evaluation model, multiple geologic agent evaluation expulsive efficiency model provides basis;

Adopt organic nonuniformity logging evaluation technology, in conjunction with resistivity, acoustic travel time logging curve and actual measurement TOC data, set up organic nonuniformity Logging estimation model; The TOC data of longitudinally upper high resolving power (0.125m) are doped according to resistivity and interval transit time logging trace, in addition, the impact of the expulsive efficiencies such as the organic matter type determined according to field data, degree of ripeness, source storage configuration relation;

D, set up single geologic agent and expulsive efficiency evaluation model: single geologic agent and expulsive efficiency evaluation model mainly determine expulsive efficiency and each single geologic agent mathematical relation, according to step C) in analyze the abundance of organic matter determined, organic matter type, maturity of organic matter and source storage configuration relation four kinds affect the geologic agent of expulsive efficiency, set up the evaluation model of single geologic agent and expulsive efficiency, quantitatively characterizing goes out the logarithmic relationship evaluation model of abundance of organic matter and expulsive efficiency, degree of ripeness under organic matter type constraint and the exponential relationship evaluation model of expulsive efficiency, maturity of organic matter under the constraint of source storage configuration relation and the polynomial relation evaluation model of expulsive efficiency,

E, set up the mathematical model of many geologic agents and expulsive efficiency: according to step D) in the data relationship of each single geologic agent model determined, guarantee often kind of geologic agent contribution form, set up the evaluation model of many geologic agents and hydrocarbon source rock expulsive efficiency, realizing many geologic agents quantitative evaluation expulsive efficiency, laying the foundation for evaluating the three-dimensional expulsive efficiency of destination layer position hydrocarbon source rock;

F, evaluate the three-dimensional expulsive efficiency of destination layer position, study area hydrocarbon source rock: the grid setting up 5km × 5km in study area, select in each grid and represent well flatly, set up organic nonuniformity Logging estimation model, obtain the TOC of longitudinal continuity from above; Simultaneously according to hydrocarbon source rock sedimentary facies distribution, determine dissimilar hydrocarbon source rock; Determine the ripe evolution condition of hydrocarbon source rock and source storage syntagmatic; According to step e) in many geologic agents of determining evaluate expulsive efficiency models, expulsive efficiency is carried out to the well screened and evaluates geology extrapolation, the high-resolution expulsive efficiency of longitudinal direction based on many mouthfuls of wells, set up out the three-dimensional expulsive efficiency geologic body in study area, establishment expulsive efficiency planimetric map, predict conventional and unconventionaloil pool Favorable Areas.

The application is based on component hydrocarbon-generating dynamics, PYGC data, international popular PetroMod2014 version raw hydrocarbon model sample component data, thermal simulation experiment data and Pyrolysis Experiment data, adopt and recover and the expulsive efficiency evaluation method of life residence thermal simulation experiment, the raw 3 aspect expulsive efficiency data such as hydrocarbon potentiality method and life residence measured data based on lighter hydrocarbons, hydrocarbon source rock expulsive efficiency of grading out exactly; Consider the internal factor and the external factor that affect hydrocarbon source rock expulsive efficiency, in-depth analysis sedimentary facies and deposition bury method, filter out abundance of organic matter, organic matter type, maturity of organic matter and source storage configuration relation four key parameters, set up the quantitative evalution model of expulsive efficiency and single geologic agent; By means of expulsive efficiency and each monofactorial mathematical relation, namely each single geologic agent is to the contribution form of expulsive efficiency, sets up multiple geologic agent and evaluates expulsive efficiency model, realize multiple geologic agent quantitative evaluation expulsive efficiency.

Expulsive efficiency, for all most important conventional and unconventionaloil pool exploration, concerning conventional gas and oil exploration, just can be contributed to the Gas Accumulation in later stage and Cheng Zang after the oil gas of hydrocarbon source rock generation only discharges; For shale oil gas, only remain in that oil gas in shale is more than enough could form oil shale fuel gas reservoir.

Embodiment 2: for Song-liao basin northern Qingshankou group hydrocarbon source rock, with ground data, geologic information, well-log information and log data for the strong point, utilize the application's " a kind of many geologic agents quantitative evaluation expulsive efficiency method ", set up the three-dimensional expulsive efficiency geologic body of Qingshankou group hydrocarbon source rock, expulsive efficiency flat distribution map, analytic routines and unconventionaloil pool distribution characteristics is set forth for wherein certain aspect.Technology path is shown in Fig. 1, and concrete steps are:

(1), data is compiled: the geochemical data in collection research district, log data, well-log information and geologic information; Wherein, geochemical data comprises rock pyrolysis analysis test data, chloroform bitumen " A " analyzing test data, organic carbon analysis test data, kerogen microscopy; Well-log information comprises natural gamma, interval transit time, microelectrode, micronormal, the dark logging trace such as side direction and shallow side direction; Log data comprises landwaste and log data; Geologic information comprises sedimentary facies planimetric map;

Exposition geochemical data in literary composition, in table 1.Wherein, the first well-name being classified as test data, secondary series data are test sample distribution layer position; 3rd column data is the well point degree of depth of test data, and the 4th column data is TOC, and the 5th column data is pyrolysis S ₁data, the 6th column data is pyrolysis S ₂data, the 7th column data is chloroform bitumen " A " data; 8th column data is the thermal evolutionary maturity of test sample.

Table 1 Qingshankou group hydrocarbon source rock Geochemical Parameters

The well logging of 200 mouthfuls, collection research district, log data, wherein, the main sieve residue log data of log data, well-log information is mainly the logging traces such as gamma ray curve, interval transit time, micro-electric level, micronormal, shallow side direction, dark side direction.For follow-up multiple geologic agent quantitative evaluation expulsive efficiency lays the foundation.

(2), initial expulsive efficiency is set up: rely on component hydrocarbon-generating dynamics, PYGC data, the raw hydrocarbon model sample component data of international popular PetroMod2014 version and thermal simulation experiment data, set up and a kind ofly to recover and the expulsive efficiency ranking method of life residence thermal simulation experiment data based on lighter hydrocarbons, to cave in J88 well 1976.99 meter of II 1 type mud stone direct press type thermal simulation experiment for the ancient dragon of neat family.The concrete Geochemical Parameters of sample is in table 2, and the raw hydrocarbon experimental data of its thermal simulation is in table 3.

The Basic Geological Geochemical Characteristics of table 2 simulated experiment specimen in use

The northern golden 88 well Qingshankou group Dark grey mud stone direct press type thermal simulation experiment results of table 3 Song-liao basin

Direct press type thermal simulation experiment data are adopted directly to evaluate golden 88 well 1976.99mII ₁the expulsive efficiency of type mud stone, have ignored the loss of lighter hydrocarbons during extracting residual hydrocarbons, makes the expulsive efficiency that evaluates bigger than normal.

Expulsive efficiency corrects mainly considers direct press type thermal simulation experiment condition, corrects out the lighter hydrocarbons part of losing in extracting residual hydrocarbons process, evaluates the expulsive efficiency of more realistic geologic condition.Thus, adopt II1 type coefficient of restitution in lighter hydrocarbons coefficient of restitution plate to correct, obtain the expulsive efficiency P after correcting ₀(Fig. 2).Result after correction meets geological knowledge more than direct employing direct press type thermal simulation experiment data evaluation, and before and after expulsive efficiency corrects, difference reaches 20%.

Recover and the evaluation expulsive efficiency method of life residence thermal simulation experiment data based on lighter hydrocarbons; The expulsive efficiency evaluated, evaluate expulsive efficiency and expulsive efficiency measured data in conjunction with raw hydrocarbon potentiality method, three kinds of method comprehensive evaluations go out the hydrocarbon source rock expulsive efficiency of destination layer position typical case's well; Consider expulsive efficiency and measured data data that raw hydrocarbon potentiality method evaluates, evidence thermal simulation experiment method evaluates the accuracy of hydrocarbon source rock expulsive efficiency.On this basis, the final expulsive efficiency of hydrocarbon source rock of Qingshankou group typical case well is provided.

(3) influence factor of expulsive efficiency, is filtered out: the hydrocarbon expulsion process of hydrocarbon source rock is the result of various complicated geological combined factors effect, it is a complicated geological process, affect a lot of because have of expulsive efficiency, comprise the internal factor of hydrocarbon source rock, as organic matter type, abundance of organic matter, maturity of organic matter; Also comprise some external factor, as hydrocarbon source rock inner pore, crack, rock texture, internal pressure, formation temperature, interfacial tension, capillary pressure, specific surface etc. simultaneously; The expulsive efficiency of these two kinds of factors on hydrocarbon source rock has great impact.

The application considers internal factor and the external factor of expulsive efficiency, deeply anatomy sedimentary facies and difference bury mode, to continue to bury type, the influence factor of expulsive efficiency is divided into abundance of organic matter, organic matter type, maturity of organic matter, source storage configuration relation four key parameters, consider that abundance of organic matter, organic matter type, maturity of organic matter, source storage configuration relation four kinds of single geologic agents are on the impact of expulsive efficiency respectively, for setting up single geologic agent evaluation model, multiple geologic agent evaluation expulsive efficiency model provides basis;

Adopt organic nonuniformity logging evaluation technology, in conjunction with resistivity, acoustic travel time logging curve and actual measurement TOC data, set up organic nonuniformity Logging estimation model (Fig. 3, Fig. 4), evaluation analysis Qingshankou group TOC Vertical Distribution Characteristics (Fig. 5, Fig. 6); The TOC data of longitudinally upper high resolving power (0.125m) are doped according to resistivity and interval transit time logging trace, in addition, the impact of the expulsive efficiencies such as the type determined according to field data, degree of ripeness, source storage configuration relation;

Because hydrocarbon source rock expulsive efficiency influence factor is very complicated, study each influence factor more difficult, the application is through induction and conclusion, consider sedimentary facies and difference buries mode, to continue to bury type, the influence factor of expulsive efficiency is divided into abundance of organic matter, organic matter type, maturity of organic matter, storage configuration relation four aspects, source.Consider abundance of organic matter, organic matter type, maturity of organic matter respectively, source storage configuration relation list geologic agent variable on the impact of expulsive efficiency, and sets up single factor evaluation model, finally set up the evaluation model that multiple geologic agent evaluates expulsive efficiency.

1), abundance of organic matter impact

Abundance of organic matter refers to quantity organic in unit mass rock.Differentiate that abundance of organic matter index mainly contains total organic carbon (TOC), raw hydrocarbon potentiality (S ₁+ S ₂), chloroform bitumen " A " and total hydrocarbon.And the most frequently used be represent with total organic carbon (TOC, %).Due to the effect of hydrocarbon source rock row hydrocarbon, the organic carbon of discharging hydro carbons is not included in the measured value of abundance of organic matter, so the abundance of organic matter of actual measurement can lower than the original abundance of organic matter.If but when other conditions are close, content organic in hydrocarbon source rock is higher, and its hydrocarbon source rock matrix is better, and hydrocarbon generation capacity is higher, and expulsive efficiency also can be larger.

Song-liao basin northern Qingshankou group abundance of organic matter green grass or young crops one section is apparently higher than blue or green two or three sections, and blue or green one section of entirety is the source rock of high organic abundance; Blue or green two or three sections of top abundances of organic matter are low, and bottom is similar, higher with green grass or young crops one section, and entirety presents the process reduced gradually from down to up.As can be seen from the single well analysis figure of Ha18Jing, Jin88Jing, English 12 well, English 16 well, Mao206Jing, Xu11Jing, TOC and expulsive efficiency have good corresponding relation, and TOC increases, and expulsive efficiency increases thereupon, and TOC reduces, and expulsive efficiency also reduces thereupon.The rule of the northern Qingshankou group expulsive efficiency of Song-liao basin and abundance of organic matter is coincide very well, reduces gradually from top to bottom.And from Ha18Jing, Jin88Jing, English 12 well, English 16 well, the TOC of Mao206Jing, Xu11Jing and the scatter diagram of expulsive efficiency, also can find out that expulsive efficiency increases along with the increase of TOC.

AM206 well TOC and expulsive efficiency scatter diagram; BH18 well TOC and expulsive efficiency scatter diagram; CX11 well TOC and expulsive efficiency scatter diagram; DJ88 well TOC and expulsive efficiency scatter diagram; EY12 well TOC and expulsive efficiency scatter diagram; FY16 well TOC and expulsive efficiency scatter diagram; (as Fig. 7 to Figure 12)

2), organic matter type impact

Because dissimilar Source Organic Matter, composition have very big difference, different organic one-tenth hydrocarbon potentiality, become the hydrocarbon phase time, become hydrocarbon products also different.Organic matter type weighs organic product hydrocarbon ability, and also determine its product is based on oil simultaneously, or based on gas.Organic type both can be reflected by the composition characteristic of insoluble organic matter, also can be reflected by the feature of its product-Soluble Organic Matter and wherein hydro carbons.Pyrolysis data analysis more easily obtains for data ultimate analysis, kerogen maceral analysis, and can comprise most of testing site.So the application uses IH-Tmax plate to divide organic matter type, the type plate of Song-liao basin as shown.

According to the expulsive efficiency that material balance method calculates, analyze the relation of dissimilar organic matter and expulsive efficiency, as can be seen from the single well analysis figure of fish 15 well, expulsive efficiency and organic matter type have good corresponding relation, organic matter type is bad, and expulsive efficiency is lower.In addition, between English 16 well 2050-2060 rice, there is I type 55.87%-II respectively in expulsive efficiency from top to down ₁type 51.65%-II ₂type 18%-I type 56%-II ₁type 54.7%-I type 57.62%.Both organic matter type was better, and adjacent expulsive efficiency is higher, otherwise lower.Fish 15 well is between 2040-2060 rice, and the scatter diagram (Figure 13) of Ro and expulsive efficiency, as can be seen from the figure, degree of ripeness has not been the principal element of the expulsive efficiency affecting this section of mud stone, and organic type is major control factors.Figure 13 is the scatter diagram of fish 15 well Ro and expulsive efficiency, can see that type is better, and expulsive efficiency is higher when close degree of ripeness from figure clearly.

Research finds, when abundance of organic matter certain (0.5% ~ 1.0%, 1.0% ~ 2.0%, 2.0% ~ 3.0%, > 3.0%) time, under the condition of identical degree of ripeness, the more corresponding expulsive efficiency of organic matter type is higher, otherwise, lower.

3), maturity of organic matter impact

Organic in continuous buried depth maturation, itself also is constantly occurring to change, and starts to generate oil gas after certain stage of ripeness.In order to weigh the intensity of variation of itself and the organic degree transformed to oil gas, we will determine the mature indicator of being correlated with.As the index of degree of ripeness, just must can embody some Changing Patterns of its organic matter self in the ripe evolutionary process of organic matter, the Changing Pattern of its product can also be embodied simultaneously.Because the mensuration of vitrinite reflectance (Ro) is not by the impact of organic composition transfer, and there is good relationship between maturity of organic matter, measure than being easier to, result is also more accurate, and there is metastable comparability, be therefore most widely used as mature indicator with Ro.

The Song-liao basin Qingshankou group hydrocarbon source rock of the application is thicker, degree of ripeness has certain change, and the sample taken out in different depth section does Ro measuring reflectance, and in conjunction with other experimental analyses, as point TOC, pyrolysis, chloroform bitumen " A " extracting etc., research degree of ripeness is on the impact of expulsive efficiency.

The expulsive efficiency calculated according to material balance method analyzes the relation of expulsive efficiency and degree of ripeness, Figure 14 to Figure 21 is the expulsive efficiency and the graph of a relation of surveying Ro that reach 23 wells, luxuriant 206 well measured values that utilize material balance method to calculate, can significantly find out from figure, along with degree of ripeness increases, expulsive efficiency increases.Figure 14 to Figure 21 is the graph of a relation of maturity of organic matter and expulsive efficiency under the condition of the different HI index of different abundance of organic matter, as can be seen from the figure, when abundance of organic matter and HI index control when a relatively little scope, expulsive efficiency increases with the increase of degree of ripeness.4), source storage configuration relation impact

Source storage configuration relation refers to the integrated mode of hydrocarbon source rock and distribution sandstone wherein, and in general individual layer mud stone is thinner, sand mud is mutual more frequent, and be more conducive to the discharge of hydro carbons, expulsive efficiency is higher.Song-liao basin Qingshankou group hydrocarbon source rock source storage configuration relation mainly contains 4 kinds of forms (see table 4), as argillite, sandstone nested, finger-like interactive and mud stone nested.

Table 4 hydrocarbon source rock source storage configuration relation

Note: L _m-individual layer mud stone thickness, m; L _s1-upper strata the sandstone that contacts with mud stone, m; L _s2-lower floor's sandstone of contacting with mud stone, m;

Cluster sampling is carried out to four kinds of rock cores that homology storage configures, and makes corresponding geochemical analysis, and then obtain expulsive efficiency, analyze not homology and store up configuration relation to the impact (see Figure 22 to Figure 25) of expulsive efficiency.

Primary Migration of Oil And Gas needs hydrocarbon source rock and the external world to there is overpressure gradient.The hydrocarbon source rock pressure distribution of homology storage configuration relation is all not different with row's hydrocarbon feature.Mud stone nested and finger-like interactive hydrocarbon source rock have unified less FPG, constantly strengthen with compaction, and the very fast close contact of mud stone particle, hydro carbons can fully be discharged up and down, and expulsive efficiency is greater than sandstone nested and argillite.

From the individual well section of Jin86Jing and English 10 well, all there is expulsive efficiency in the middle part of argillite lower than the edge mud stone adjacent with sandstone, in golden 86 wells, between 1900-1910 rice, sand and mud interstratification expulsive efficiency is 46.8%, sandstone is nested is 30.7%, sand and mud interstratification expulsive efficiency 62.7% between 1945-1950 rice, the nested expulsive efficiency 67.1% of mud stone, the nested expulsive efficiency 56.5% of sandstone, the nested expulsive efficiency 71.5% of mud stone, both can find out that expulsive efficiency mud stone nested > sand and mud interstratification > sandstone was nested and it is low to close on the edge of sandstone than edge in the middle part of argillite expulsive efficiency from golden 86 wells, Figure 26 is that homology does not store up the mud stone maturity of organic matter of configuration relation and the relation of expulsive efficiency, also above the same viewpoint can be obtained.Sand and mud interstratification expulsive efficiency 69.2%, 5m mud stone expulsive efficiency 67.3%, the nested expulsive efficiency 73.5% of mud stone between 2260-2280 rice in English 10 well, the nested expulsive efficiency 67.7% of mud stone, sand and mud interstratification expulsive efficiency 66.1% between sand and mud interstratification expulsive efficiency 71.8%, the nested expulsive efficiency of mud stone 73.5%, sandstone nested expulsive efficiency 69.7%, 2350-2370 rice between 2280-2300 rice.Both the nested > argillite of expulsive efficiency mud stone nested > sand and mud interstratification > sandstone, and it is low to close on the edge of sandstone than edge in the middle part of argillite expulsive efficiency.Figure 27 is that homology does not store up the mud stone abundance of organic matter of configuration relation and the graph of a relation of expulsive efficiency, with identical of views above.

Both in sandstone nested and argillite, shale index was higher, and sedimentary particle is thinner, and sedimentary environment is better, and abundance of organic matter is high, and type is good, and expulsive efficiency is high.And in sand and mud interstratification and mud stone nested, shale index is higher, illustrate that mud stone becomes many, contact insufficient with sandstone, expulsive efficiency is low.

To breathe out in 18 wells the nested expulsive efficiency of sandstone 30.3%, mud alternating layers expulsive efficiency 56.3%, the nested expulsive efficiency 52% of mud stone between 2025-2045 rice, both expulsive efficiency sand and mud interstratification > sandstone was nested; 6 well 1870-1885 rice sand and mud interstratification expulsive efficiencies 65.4%, the nested expulsive efficiency 73.6% of mud stone suddenly, the nested > sand and mud interstratification of expulsive efficiency mud stone; Gold 86 wells obviously can find out that in the middle part of argillite, expulsive efficiency is less than the expulsive efficiency of the edge mud stone near sandstone.

(4), set up single geologic agent and expulsive efficiency evaluation model: single geologic agent and expulsive efficiency evaluation model mainly determine expulsive efficiency and each single geologic agent mathematical relation, according to step 3) in analyze the abundance of organic matter determined, organic matter type, maturity of organic matter and source storage configuration relation four kinds affect the geologic agent of expulsive efficiency, set up the evaluation model of single geologic agent and expulsive efficiency, quantitatively characterizing goes out the logarithmic relationship evaluation model of abundance of organic matter and expulsive efficiency, degree of ripeness under organic matter type constraint and the exponential relationship evaluation model of expulsive efficiency, maturity of organic matter under the constraint of source storage configuration relation and 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) are:

P＝26.69×ln(TOC)+29.45(4-1)

Ro under the different organic matter type constraints that the application determines and expulsive efficiency single factor evaluation modular form (4-2) are:

P＝0.558×exp(6.1×Ro _KT)-30.85(4-2)

The not homology that the application determines is stored up the Ro under configuration relation constraint and with expulsive efficiency single factor evaluation model (formula 4-3) (Figure 30 and table 4) is:

P＝-2258×Ro _YCPZ×Ro _YCPZ+4660.68×Ro _YCPZ-2321(4-3)

In formula, P represents hydrocarbon source rock expulsive efficiency; TOC refers to abundance of organic matter; Ro _(T)refer to the Ro under different kerogen type constraint and the Ro in expulsive efficiency relation, Ro _yCPZrefer to the Ro under not homology storage configuration control and the Ro in expulsive efficiency relation.

Table 5 not homology stores up the expulsive efficiency evaluation model of configuration relation

(5), set up the mathematical model of many geologic agents and expulsive efficiency: according to step 4) in the data relationship of each single geologic agent model determined, guarantee often kind of geologic agent contribution form, set up the evaluation model of many geologic agents and hydrocarbon source rock expulsive efficiency, realizing many geologic agents quantitative evaluation expulsive efficiency, laying the foundation for evaluating the three-dimensional expulsive efficiency of destination layer position hydrocarbon source rock;

According to step 4) in the data relationship of each single geologic agent model determined, guarantee the accuracy of often kind of geologic agent contribution form, set up the evaluation model (formula 5-1) of many geologic agents and hydrocarbon source rock expulsive efficiency, realizing many geologic agents quantitative evaluation expulsive efficiency, laying the foundation for evaluating the three-dimensional expulsive efficiency of destination layer position hydrocarbon source rock; Multiple geologic agent evaluates expulsive efficiency mathematical model:

P＝P _NY×P _WY

＝0.93×(1.92×ln(TOC)+28.13×exp(Ro _K，T)-61.72)

× (-5.6 × Ro _yCPZ× Ro _yCPZ-0.895 × Ro _yCPZ+ 8.03) formula (5-1)

In formula: P represents expulsive efficiency, P _nYrepresent expulsive efficiency influnecing factor, P _wYrepresent expulsive efficiency external influence factors; TOC refers to abundance of organic matter; (Ro _k,T) refer to the relation of Ro under different kerogen type constraint and expulsive efficiency; ID _yCPZrefer to the relation of Ro under not homology storage configuration constraint and expulsive efficiency;

Geologic agent more than table 6 and hydrocarbon source rock expulsive efficiency relation statistical form

(6), evaluate the three-dimensional expulsive efficiency of destination layer position, study area hydrocarbon source rock: the grid setting up 5km × 5km in study area, select in each grid and represent well flatly, set up organic nonuniformity Logging estimation model, obtain the TOC of longitudinal continuity from above; Simultaneously according to hydrocarbon source rock sedimentary facies distribution, determine dissimilar hydrocarbon source rock; Determine the ripe evolution condition of hydrocarbon source rock and source storage syntagmatic; According to step 5) in many geologic agents expulsive efficiency evaluation model of determining, carry out study area geology extrapolation, in conjunction with the high-resolution expulsive efficiency of longitudinal direction of many mouthfuls of wells (Figure 31), set up out the three-dimensional expulsive efficiency geologic body in study area, establishment expulsive efficiency planimetric map (Figure 32), prediction unconventionaloil pool Favorable Areas.

Expulsive efficiency, for all most important conventional and unconventionaloil pool exploration, concerning conventional gas and oil exploration, just can be contributed to the Gas Accumulation in later stage and Cheng Zang after the oil gas of hydrocarbon source rock generation only discharges; For shale oil gas, only remain in that oil gas in shale is more than enough could form oil shale fuel gas reservoir.Thus, study hydrocarbon source rock expulsive efficiency and there is very large value.

Embodiment 3: a kind of many geologic agents quantitative evaluation hydrocarbon source rock expulsive efficiency method, comprises the following steps:

1), data is compiled: the geochemical data in collection research district, log data, well-log information and geologic information; Wherein, geochemical data comprises rock pyrolysis analysis test data, chloroform bitumen " A " analyzing test data, organic carbon analysis test data, kerogen microscopy; Well-log information comprises natural gamma, interval transit time, microelectrode, micronormal, the dark logging trace such as side direction and shallow side direction; Log data comprises landwaste and log data; Geologic information comprises sedimentary facies planimetric map;

2), a kind of hydrocarbon source rock expulsive efficiency evaluation method is set up: rely on component hydrocarbon-generating dynamics, PYGC data, the raw hydrocarbon model sample component data of international popular PetroMod2014 version and thermal simulation experiment data, establish and a kind ofly to recover and the expulsive efficiency evaluation method of life residence thermal simulation experiment data based on lighter hydrocarbons, the expulsive efficiency data evaluated in conjunction with raw hydrocarbon potentiality method and expulsive efficiency measured data, three kinds of method comprehensive evaluations go out destination layer position hydrocarbon source rock expulsive efficiency;

3) influence factor of expulsive efficiency, is filtered out: the hydrocarbon expulsion process of hydrocarbon source rock is the result of various complicated geological combined factors effect, it is a complicated geological process, affect a lot of because have of expulsive efficiency, comprise the internal factor of hydrocarbon source rock, as organic matter type, abundance of organic matter, maturity of organic matter; Also comprise some external factor, as hydrocarbon source rock inner pore, crack, rock texture, internal pressure, formation temperature, interfacial tension, capillary pressure, specific surface etc. simultaneously; The expulsive efficiency of these two kinds of factors on hydrocarbon source rock has great impact.

The application considers internal factor and the external factor of expulsive efficiency, deeply anatomy sedimentary facies and difference bury mode, to continue to bury type, the influence factor of expulsive efficiency is divided into abundance of organic matter, organic matter type, maturity of organic matter, source storage configuration relation four key parameters, consider that abundance of organic matter, organic matter type, maturity of organic matter, source storage configuration relation single-factor variable are on the impact of expulsive efficiency respectively, for setting up single factor evaluation model, multiple geologic agent evaluation expulsive efficiency model provides basis;

Adopt organic nonuniformity logging evaluation technology, in conjunction with resistivity, acoustic travel time logging curve and actual measurement TOC data, set up organic nonuniformity Logging estimation model; The TOC data of longitudinally upper high resolving power (0.125m) are doped according to resistivity and interval transit time logging trace, in addition, the impact of the expulsive efficiencies such as the type determined according to field data, degree of ripeness, source storage configuration relation;

4), set up single geologic agent and expulsive efficiency evaluation model: single geologic agent and expulsive efficiency evaluation model mainly determine expulsive efficiency and each single geologic agent mathematical relation, according to step 3) in analyze the abundance of organic matter determined, organic matter type, maturity of organic matter and source storage configuration relation four kinds affect the geologic agent of expulsive efficiency, set up the evaluation model of single geologic agent and expulsive efficiency, quantitatively characterizing goes out the logarithmic relationship evaluation model of abundance of organic matter and expulsive efficiency, degree of ripeness under organic matter type constraint and the exponential relationship evaluation model of expulsive efficiency, maturity of organic matter under the constraint of source storage configuration relation and the polynomial relation evaluation model of expulsive efficiency,

5), set up the mathematical model of many geologic agents and expulsive efficiency: according to step 4) in the data relationship of each single geologic agent model determined, guarantee often kind of geologic agent contribution form, set up the evaluation model of many geologic agents and hydrocarbon source rock expulsive efficiency, realizing many geologic agents quantitative evaluation expulsive efficiency, laying the foundation for evaluating the three-dimensional expulsive efficiency of destination layer position hydrocarbon source rock;

6), evaluate the three-dimensional expulsive efficiency of destination layer position, study area hydrocarbon source rock: the grid setting up 5km × 5km in study area, select in each grid and represent well flatly, set up organic nonuniformity Logging estimation model, obtain the TOC of longitudinal continuity from above; Simultaneously according to hydrocarbon source rock sedimentary facies distribution, determine dissimilar hydrocarbon source rock; Determine the ripe evolution condition of hydrocarbon source rock and source storage syntagmatic; According to step 5) in many geologic agents of determining evaluate expulsive efficiency models, expulsive efficiency is carried out to the well screened and evaluates geology extrapolation, the high-resolution expulsive efficiency of longitudinal direction based on many mouthfuls of wells, set up out the three-dimensional expulsive efficiency geologic body in study area, establishment expulsive efficiency planimetric map, prediction and conventional unconventionaloil pool Favorable Areas.

The application is based on component hydrocarbon-generating dynamics, PYGC data, the raw hydrocarbon model of international popular, thermal simulation experiment data and Pyrolysis Experiment data, adopt and recover and the expulsive efficiency evaluation method of life residence thermal simulation experiment, the raw 3 aspect expulsive efficiency data such as hydrocarbon potentiality method and life residence measured data based on lighter hydrocarbons, hydrocarbon source rock expulsive efficiency of grading out exactly; Consider the internal factor and the external factor that affect hydrocarbon source rock expulsive efficiency, in-depth analysis sedimentary facies and deposition bury method, filter out abundance of organic matter, organic matter type, maturity of organic matter and source storage configuration relation four key parameters, set up the quantitative evalution model of expulsive efficiency and single geologic agent; By means of expulsive efficiency and each monofactorial mathematical relation, namely each single geologic agent is to the contribution form of expulsive efficiency, sets up multiple geologic agent and evaluates expulsive efficiency model, realize multiple geologic agent quantitative evaluation expulsive efficiency.

Described step 2) in set up and a kind ofly to recover and the expulsive efficiency evaluation method of life residence thermal simulation experiment based on lighter hydrocarbons, expulsive efficiency evaluation of programme divides 4 steps, and concrete steps (Figure 33) are as follows:

1), thermal simulation experiment design: gather destination layer position, study area source rock sample (TOC>0.5%, degree of ripeness Ro<0.5%), design rock direct press type thermal simulation experiment;

2), expulsive efficiency evaluation model: based on rock direct press type thermal simulation experiment data, evaluate expulsive efficiency P.Due to light hydrocarbon component C in extractive process _6-14loss, the expulsive efficiency P that experimental data is determined is than actual expulsive efficiency P ₀(namely loss amount being counted a part for discharge rate) bigger than normal, is thus necessary to recover lighter hydrocarbons part;

3), lighter hydrocarbons restoration evaluation model: based on the raw hydrocarbon model sample of international popular PetroMod2014 version 33 pieces of component data, with reference to the raw hydrocarbon samples of domestic PY-GC thermal simulation 50 pieces of experimental datas, its data mode is C ₁₄₊, C _6-14, C _5-1three kinds of chemical species, establish lighter hydrocarbons coefficient of restitution evaluation of programme, evaluate lighter hydrocarbons correction coefficient K _{lighter hydrocarbons coefficient of restitution}; Correct out the light hydrocarbon component C lost in extractive process _6-14, evaluate expulsive efficiency P ₀;

4), set up a kind of expulsive efficiency evaluation method: based on step 3) in the lighter hydrocarbons coefficient of restitution K of expulsive efficiency _{lighter hydrocarbons coefficient of restitution}, integrating step 2) determine expulsive efficiency P, evaluate hydrocarbon source rock expulsive efficiency P ₀.

The expulsive efficiency correction coefficient K of dissimilar organic matter is found by the application _jZrelevant with degree of ripeness and Kerogen type, there is with degree of ripeness increase the rule first reducing to increase afterwards; By I type, II ₁type, II ₂coefficient of restitution K during the change of type, type III _jZincrease (Figure 34) gradually.

The evaluation principle of expulsive efficiency model is as follows:

The method comprises the lighter hydrocarbons coefficient of restitution model of expulsive efficiency model and the raw hydrocarbon model sample 33 pieces of component data of international popular PetroMod2014 version and the raw hydrocarbon data foundation of domestic 50 pieces of PY-GC thermal simulations of setting up according to direct press type thermal simulation experiment data.Wherein, in direct press type thermal simulation experiment process during extracting residual hydrocarbons, C _6-14lighter hydrocarbons partial loss, the expulsive efficiency causing directly adopting direct press type thermal simulation experiment data evaluation to go out is higher, adopts the raw hydrocarbon model sample 33 pieces of component data of international popular PetroMod2014 version and the raw hydrocarbon data of domestic 50 pieces of PY-GC thermal simulations to set up C _6-14lighter hydrocarbons coefficient of restitution evaluation of programme, obtains I type, II ₁type, II ₂the lighter hydrocarbons coefficient of restitution of type, III type expulsive efficiency, sets up the dissimilar expulsive efficiency evaluation model of complete set.

1), expulsive efficiency evaluation model is set up according to direct press type thermal simulation experiment data

According to direct press type thermal simulation experiment data (discharging oil, oil residues, discharge gas and residue gas), set up a kind of judgement schematics adopting the semi-open semiclosed thermal simulation experiment data evaluation expulsive efficiency P of direct press type.

Expulsive efficiency P evaluation model, as follows:

P = \frac{Q_{1} + Q_{3}}{Q_{1} + Q_{3} + Q_{2} + Q_{4}} - - - (2 - 1)

Formula (2-1) have ignored the loss of lighter hydrocarbons in residual hydrocarbons extractive process, thus, is necessary the light hydrocarbon component C6-14 considering to lose in residual hydrocarbons extractive process, sets up the expulsive efficiency evaluation model P0 of coincidence theory.

Expulsive efficiency P0 evaluation model is:

P_{0} = \frac{Q_{1} + Q_{3}}{Q_{1} + Q_{3} + (Q_{2} + Q_{4}) * K_{J Z}} - - - (2 - 2)

In formula (2-2), Q ₁for discharging oil; Q ₂for oil residues; Q ₃for discharging gas; Q ₄for residue gas; Expulsive efficiency P is the expulsive efficiency that direct press type thermal simulation experiment data directly evaluate acquisition; K _jZfor the lighter hydrocarbons coefficient of restitution of expulsive efficiency P; Expulsive efficiency P ₀for the expulsive efficiency after correction.

Experimental defects: when measuring residual hydrocarbons, light hydrocarbon component C _6-13loss.The application adopts the raw hydrocarbon model sample 33 pieces of component data of international popular PetroMod2014 version and the raw hydrocarbon data of domestic 50 pieces of PY-GC thermal simulations (C _1-5, C _6-13, C ₁₄₊), the light hydrocarbon component lost in direct press type thermal simulation experiment is corrected, thus reaches the object correcting expulsive efficiency.

2) the lighter hydrocarbons calibration model of four kinds of Types of hydrocarbon source rock, is established

But K _jZusually be difficult to obtain in experimentation, based on the raw hydrocarbon model sample of international popular PetroMod2014 version 33 pieces of component data in this research, with reference to the raw hydrocarbon samples 50 pieces of domestic PY-GC thermal simulation, establish I type, II ₁type, II ₂lighter hydrocarbons coefficient of restitution (the approximate replacement K of type, III type expulsive efficiency _jZ), its judgement schematics (2-3) is

K_{J Z} = \frac{C_{14 +} + C_{6 - 14}}{C_{14 +}} - - - (2 - 3)

Formula (2-3) is brought in formula (2-2), obtains formula (2-4).

\begin{matrix} P_{0} = \frac{Q_{1} + Q_{3}}{Q_{1} + Q_{3} + (Q_{2} + Q_{4}) * K_{J Z}} \\ = \frac{Q_{1} + Q_{3}}{Q_{1} + Q_{3} + (Q_{2} + Q_{4}) * \frac{(C_{14 +} + C_{6 - 13})}{C_{14 +}}} \end{matrix} - - - (2 - 4)

During actual expulsive efficiency is evaluated, combinatorial formula (2-2) and (2-3), obtain expulsive efficiency P _ojudgement schematics (2-4), completes expulsive efficiency appraisal.

Described step 2) in, multiple expulsive efficiency evaluation method sets up out expulsive efficiency accurately, specific as follows:

With 1976.99 meter II, neat family ancient dragon depression J88 well ₁type mud stone direct press type thermal simulation experiment is example.The concrete Geochemical Parameters of sample is in table 7, and the raw hydrocarbon experimental data of its thermal simulation is in table 8.

The Basic Geological Geochemical Characteristics of table 7 simulated experiment specimen in use

The northern golden 88 well Qingshankou group Dark grey mud stone direct press type thermal simulation experiment results of table 8 Song-liao basin

Direct press type thermal simulation experiment data are adopted directly to evaluate J88 well 1976.99mII ₁the expulsive efficiency of type mud stone, have ignored the loss of lighter hydrocarbons during extracting residual hydrocarbons, makes the expulsive efficiency that evaluates bigger than normal.Thus, II in lighter hydrocarbons coefficient of restitution plate is adopted ₁type coefficient of restitution corrects, and obtains the expulsive efficiency P after correcting ₀.

Expulsive efficiency corrects considers direct press type thermal simulation experiment condition, corrects out the lighter hydrocarbons part of losing in extracting residual hydrocarbons process, evaluates the expulsive efficiency of more realistic geologic condition.Result after correction meets geological knowledge more than direct employing direct press type thermal simulation experiment data evaluation, and before and after expulsive efficiency corrects, difference reaches 20%.Consider raw hydrocarbon potentiality method and measured data data, evidence thermal simulation experiment method evaluates the accuracy of hydrocarbon source rock expulsive efficiency.On this basis, the final expulsive efficiency of Qingshankou group hydrocarbon source rock is provided.

Described step 4) in, set up single geologic agent and expulsive efficiency evaluation model, obtain single geologic agent and expulsive efficiency mathematical relation, specific as follows:

Adopt organic nonuniformity logging evaluation technology, joint resistance rate logging trace, acoustic travel time logging curve and actual measurement TOC data, evaluate the TOC data point of longitudinally upper resolution high (0.125), determine the logarithmic relationship evaluation model (formula 4-1) of abundance of organic matter and expulsive efficiency:

P=a × ln (TOC)+b formula (4-1)

The abundance of organic matter that the application determines and expulsive efficiency single factor evaluation model formation (4-2) are:

P=26.69 × ln (TOC)+29.45 formula (4-2)

Establish Ro under the constraint of different organic matter type and the exponential relationship evaluation model formula (4-3) of expulsive efficiency is,

P=a × exp (b × Ro _kT)-c formula (4-3)

Ro under the different organic matter type constraints that the application determines and expulsive efficiency single factor evaluation modular form (4-4) are:

P=0.558 × exp (6.1 × Ro _kT)-30.85 formulas (4-4)

The exponential relationship evaluation model (formula 4-5) establishing Ro under the constraint of not homology storage configuration relation and expulsive efficiency is,

P=a × Ro _yCPZ+ b × Ro _yCPZ+ c formula (4-5)

The not homology that the application determines is stored up the Ro under configuration relation constraint and with expulsive efficiency single factor evaluation model (formula 4-6) (table 9) is:

P=-2258 × Ro _yCPZ× Ro _yCPZ+ 4660.68 × Ro _yCPZ-2321 formulas (4-6)

Table 9 not homology stores up the expulsive efficiency evaluation model of configuration relation

Described step 5) in, set up multiple geologic agent and expulsive efficiency mathematics appraisal, specific as follows:

Consider the internal factor and external factor that affect hydrocarbon source rock expulsive efficiency, rely on step 2) in the logarithmic relationship of the abundance of organic matter determined and expulsive efficiency, organic matter type retrain under degree of ripeness and the exponential relationship of expulsive efficiency, source store up configuration relation retrain under maturity of organic matter and the polynomial relation of expulsive efficiency; Set up the evaluation model (formula 5-1) of multiple geologic agent and expulsive efficiency, realize multiple geologic agent quantitative evaluation hydrocarbon source rock expulsive efficiency;

P＝P _NY×P _WY

=(f (TOC)+f (Ro _kT× f (Ro _yCPZ) formula (5-1)

In formula: P represents expulsive efficiency, P _nYrepresent expulsive efficiency influnecing factor, P _wYrepresent expulsive efficiency external influence factors;

Geologic agent more than table 10 and hydrocarbon source rock expulsive efficiency relation statistical form

Multiple geologic agent evaluates expulsive efficiency mathematical model:

P＝P _NY×P _WY

＝0.93×(1.92×ln(TOC)+28.13×exp(Ro _KT)-61.72)

× (-5.6 × Ro _yCPZ× Ro _yCPZ-0.895 × Ro _yCPZ+ 8.03) formula (5-2)

In formula: P represents expulsive efficiency, P _nYrepresent expulsive efficiency influnecing factor, P _wYrepresent expulsive efficiency external influence factors; TOC refers to abundance of organic matter, and (Ro, T) refers to the Ro under different kerogen type constraint, ID _yCPZrefer to the relation of Ro under not homology storage configuration constraint and expulsive efficiency;

According to step 3) in the data relationship of each single geologic agent model determined, guarantee the accuracy of often kind of geologic agent contribution form, set up the evaluation model (formula 5-2) of many geologic agents and hydrocarbon source rock expulsive efficiency, realizing many geologic agents quantitative evaluation expulsive efficiency, laying the foundation for evaluating the three-dimensional expulsive efficiency of destination layer position hydrocarbon source rock.

As mentioned above, embodiments of the invention are explained, but as long as do not depart from inventive point of the present invention in fact and effect can have a lot of distortion, this will be readily apparent to persons skilled in the art.Therefore, such variation is also all included within protection scope of the present invention.

Claims

1. the quantitative evaluation of geologic agent more than an expulsive efficiency method, is characterized in that containing following steps;

Step 2), filter out the influence factor of expulsive efficiency: consider the internal factor and external factor that affect expulsive efficiency; Hydrocarbon source rock influnecing factor, considers organic matter type, abundance of organic matter, maturity of organic matter, hydrocarbon source rock external factor, considers hydrocarbon source rock inner pore, crack, rock texture, internal pressure, formation temperature, interfacial tension, capillary pressure, specific surface; Comprehensive sedimentary facies and bury mode, filters out abundance of organic matter, organic matter type, maturity of organic matter and source storage configuration relation 4 kinds of geologic agents;

Step 4), set up the evaluation model of many geologic agents and expulsive efficiency: determine the logarithmic relationship of abundance of organic matter and expulsive efficiency, organic matter type retrain under degree of ripeness and the exponential relationship of expulsive efficiency, source store up configuration relation retrain under maturity of organic matter and the polynomial relation of expulsive efficiency, namely this single geologic agent is to the contribution rate of expulsive efficiency; Adopt curve fitting software, set up out based on single geologic agent evaluation model, meet geological knowledge, many geologic agents quantitative evaluation expulsive efficiency evaluation model of meeting geologic rule;

2. a kind of many geologic agents quantitative evaluation expulsive efficiency method as claimed in claim 1, is characterized in that: comprise the following steps;

Step 1), compile data: the geochemical data in collection research district, log data, well-log information and geologic information; Wherein, geochemical data comprises rock pyrolysis analysis test data, chloroform bitumen " A " analyzing test data, organic carbon analysis test data, kerogen microscopy data; Well-log information comprises natural gamma, interval transit time, microelectrode, micronormal, dark side direction and shallow lateral logging curve; Log data comprises landwaste and log data; Geologic information comprises sedimentary facies planimetric map;

Step 2), set up a kind of hydrocarbon source rock expulsive efficiency evaluation method: rely on component hydrocarbon-generating dynamics, PYGC data, the raw hydrocarbon model sample component data of international popular PetroMod2014 version and thermal simulation experiment data, set up and a kind ofly to recover and the expulsive efficiency evaluation method of life residence thermal simulation experiment data based on lighter hydrocarbons, the expulsive efficiency evaluated in conjunction with raw hydrocarbon potentiality method and expulsive efficiency measured data, three kinds of method comprehensive evaluations go out the hydrocarbon source rock expulsive efficiency of destination layer position typical case's well;

Set up the quantitative evaluation relation of geologic agent and expulsive efficiency, finally set up out the evaluation model of many geologic agents and expulsive efficiency, for the three-dimensional expulsive efficiency evaluation in study area lays the foundation;

Step 3), filter out the influence factor of expulsive efficiency:

Consider internal factor and the external factor of expulsive efficiency, deeply anatomy sedimentary facies and difference bury mode, type is buried for continuing, the influence factor of expulsive efficiency is divided into abundance of organic matter, organic matter type, maturity of organic matter, source storage configuration relation four key parameters, consider that abundance of organic matter, organic matter type, maturity of organic matter, source storage configuration relation single-factor variable are on the impact of expulsive efficiency respectively, for setting up single factor evaluation model, multiple geologic agent evaluation expulsive efficiency model provides basis;

Adopt organic nonuniformity logging evaluation technology, in conjunction with resistivity, acoustic travel time logging curve and actual measurement TOC data, set up organic nonuniformity Logging estimation model; Dope the TOC data of longitudinally upper high resolving power (0.125m) according to resistivity and interval transit time logging trace, in addition, the organic matter type determined according to field data, maturity of organic matter, source storage configuration relation are on the impact of expulsive efficiency;

Step 4), set up single geologic agent and expulsive efficiency evaluation model: single geologic agent and expulsive efficiency evaluation model mainly determine expulsive efficiency and each single geologic agent mathematical relation, according to step 3) in analyze the abundance of organic matter determined, organic matter type, maturity of organic matter and source storage configuration relation four kinds affect the geologic agent of expulsive efficiency, set up the evaluation model of single geologic agent and expulsive efficiency, quantitatively characterizing goes out the logarithmic relationship evaluation model of abundance of organic matter and expulsive efficiency, degree of ripeness under organic matter type constraint and the exponential relationship evaluation model of expulsive efficiency, maturity of organic matter under the constraint of source storage configuration relation and the polynomial relation evaluation model of expulsive efficiency,

Step 5), set up the mathematical model of many geologic agents and expulsive efficiency: according to step 4) in the data relationship of each single geologic agent model determined, guarantee often kind of geologic agent contribution form, set up the evaluation model of many geologic agents and hydrocarbon source rock expulsive efficiency, realizing many geologic agents quantitative evaluation expulsive efficiency, laying the foundation for evaluating the three-dimensional expulsive efficiency of destination layer position hydrocarbon source rock;

Step 6), evaluate the three-dimensional expulsive efficiency of destination layer position, study area hydrocarbon source rock: the grid setting up 5km × 5km in study area, select in each grid and represent well flatly, set up organic nonuniformity Logging estimation model, obtain the TOC of longitudinal continuity from above; Simultaneously according to hydrocarbon source rock sedimentary facies distribution, determine dissimilar hydrocarbon source rock; Determine the ripe evolution condition of hydrocarbon source rock and source storage syntagmatic; According to step 5) in many geologic agents of determining evaluate expulsive efficiency models, expulsive efficiency is carried out to the well screened and evaluates geology extrapolation, the high-resolution expulsive efficiency of longitudinal direction based on many mouthfuls of wells, set up out the three-dimensional expulsive efficiency geologic body in study area, establishment expulsive efficiency planimetric map, prediction and conventional unconventionaloil pool Favorable Areas.

3. a kind of many geologic agents quantitative evaluation expulsive efficiency method as claimed in claim 2, it is characterized in that: described step 2) in set up and a kind ofly to recover and the expulsive efficiency evaluation method of life residence thermal simulation experiment based on lighter hydrocarbons, expulsive efficiency evaluation of programme divides 4 steps, and concrete steps are as follows:

Step 1, thermal simulation experiment design: gather destination layer position, study area source rock sample (TOC>0.5%, degree of ripeness Ro<0.5%), design rock direct press type thermal simulation experiment;

Step 2, expulsive efficiency evaluation model: based on rock direct press type thermal simulation experiment data, evaluate expulsive efficiency P; Due to light hydrocarbon component C in extractive process _6-14loss, the expulsive efficiency P that experimental data is determined is than actual expulsive efficiency P ₀(namely loss amount being counted a part for discharge rate) bigger than normal, is thus necessary to recover lighter hydrocarbons part;

Step 3, lighter hydrocarbons restoration evaluation model: based on the raw hydrocarbon model sample of international popular PetroMod2014 version 33 pieces of component data, with reference to the raw hydrocarbon samples of domestic PY-GC thermal simulation 50 pieces of experimental datas, its data mode is C ₁₄₊, C _6-14, C _5-1three kinds of chemical species, establish lighter hydrocarbons coefficient of restitution evaluation of programme, evaluate lighter hydrocarbons correction coefficient K _{lighter hydrocarbons coefficient of restitution}; Correct out the light hydrocarbon component C lost in extractive process _6-14, evaluate expulsive efficiency P ₀;

Step 4, set up a kind of expulsive efficiency evaluation method: based on the lighter hydrocarbons coefficient of restitution K of expulsive efficiency in step 3 _{lighter hydrocarbons restorer} _number, integrating step 2 determines expulsive efficiency P, evaluates hydrocarbon source rock expulsive efficiency P ₀;

The expulsive efficiency correction coefficient K of dissimilar organic matter _jZrelevant with degree of ripeness and Kerogen type, there is with degree of ripeness increase the rule first reducing to increase afterwards; By I type, II ₁type, II ₂coefficient of restitution K during the change of type, type III _jZincrease gradually;

The lighter hydrocarbons coefficient of restitution model of the expulsive efficiency model set up according to direct press type thermal simulation experiment data and the raw hydrocarbon model sample 33 pieces of component data of international popular PetroMod2014 version and the 50 pieces of experimental datas foundation of the raw hydrocarbon samples of domestic PY-GC thermal simulation; Wherein, in direct press type thermal simulation experiment process during extracting residual hydrocarbons, C _6-14lighter hydrocarbons partial loss, the expulsive efficiency causing directly adopting direct press type thermal simulation experiment data evaluation to go out is higher, adopts the raw hydrocarbon model sample 33 pieces of component data of international popular PetroMod2014 version and the raw hydrocarbon samples of domestic PY-GC thermal simulation 50 pieces of experimental datas to set up C _6-14lighter hydrocarbons coefficient of restitution evaluation of programme, obtains I type, II ₁type, II ₂the lighter hydrocarbons coefficient of restitution of type, III type expulsive efficiency, sets up the dissimilar expulsive efficiency evaluation model of complete set;

According to direct press type thermal simulation experiment data (discharging oil, oil residues, discharge gas and residue gas), set up a kind of judgement schematics adopting the semi-open semiclosed thermal simulation experiment data evaluation expulsive efficiency P of direct press type;

Expulsive efficiency P evaluation model, as follows:

P = \frac{Q_{1} + Q_{3}}{Q_{1} + Q_{3} + Q_{2} + Q_{4}} - - - (2 - 1)

Formula (2-1) have ignored the loss of lighter hydrocarbons in residual hydrocarbons extractive process, thus, is necessary the light hydrocarbon component C considering to lose in residual hydrocarbons extractive process _6-14, set up the expulsive efficiency evaluation model P of coincidence theory ₀;

Expulsive efficiency P ₀evaluation model is:

P_{0} = \frac{Q_{1} + Q_{3}}{Q_{1} + Q_{3} + (Q_{2} + Q_{4}) * K_{J Z}} - - - (2 - 2)

In formula (2-1) and formula (2-2), Q ₁for discharging oil; Q ₂for oil residues; Q ₃for discharging gas; Q ₄for residue gas; Expulsive efficiency P is the expulsive efficiency that direct press type thermal simulation experiment data directly evaluate acquisition; K _jZfor the lighter hydrocarbons coefficient of restitution of expulsive efficiency P; Expulsive efficiency P ₀for the expulsive efficiency after correction;

Based on the raw hydrocarbon model sample of international popular PetroMod2014 version 33 pieces of component data, with reference to the raw hydrocarbon samples 50 pieces of domestic PY-GC thermal simulation, establish I type, II ₁type, II ₂lighter hydrocarbons coefficient of restitution (the approximate replacement K of type, III type expulsive efficiency _jZ), its judgement schematics (2-3) is

K_{J Z} = \frac{C_{14 +} + C_{6 - 14}}{C_{14 +}} - - - (2 - 3)

Formula (2-3) is brought in formula (2-2), obtains formula (2-4);

\begin{matrix} P_{0} = \frac{Q_{1} + Q_{3}}{Q_{1} + Q_{3} + (Q_{2} + Q_{4}) * K_{J Z}} \\ = \frac{Q_{1} + Q_{3}}{Q_{1} + Q_{3} + (Q_{2} + Q_{4}) * \frac{(C_{14 +} + C_{6 - 13})}{C_{14 +}}} \end{matrix} - - - (2 - 4)

In formula (2-1) and formula (2-2), Q ₁for discharging oil; Q ₂for oil residues; Q ₃for discharging gas; Q ₄for residue gas; Expulsive efficiency P is the expulsive efficiency that direct press type thermal simulation experiment data directly evaluate acquisition; K _jZfor the lighter hydrocarbons coefficient of restitution of expulsive efficiency P; Expulsive efficiency P ₀for the expulsive efficiency after correction; C _6-13for C6 to C13 lighter hydrocarbons loss part in oil, C ₁₄₊for more than C14 heavy component in oil;

During actual expulsive efficiency is evaluated, combinatorial formula (2-2) and formula (2-3), obtain expulsive efficiency P _ojudgement schematics (2-4), completes expulsive efficiency appraisal.

4. a kind of many geologic agents quantitative evaluation expulsive efficiency method as claimed in claim 2, is characterized in that: described step 2) in, multiple expulsive efficiency evaluation method sets up out expulsive efficiency accurately, specific as follows:

Direct press type thermal simulation experiment data are adopted directly to evaluate J88 well 1976.99mII ₁the expulsive efficiency of type mud stone, have ignored the loss of lighter hydrocarbons during extracting residual hydrocarbons, makes the expulsive efficiency that evaluates bigger than normal; Thus, II is adopted ₁type coefficient of restitution corrects, and obtains the expulsive efficiency P after correcting ₀;

Expulsive efficiency corrects considers direct press type thermal simulation experiment condition, corrects out the lighter hydrocarbons part of losing in extracting residual hydrocarbons process, evaluates the expulsive efficiency of more realistic geologic condition; Result after correction meets geological knowledge more than direct employing direct press type thermal simulation experiment data evaluation, and before and after expulsive efficiency corrects, difference reaches 20%; Consider hydrocarbon source rock expulsive efficiency and the measured data data of the evaluation of raw hydrocarbon potentiality method, evidence thermal simulation experiment method evaluates the accuracy of hydrocarbon source rock expulsive efficiency; On this basis, the Qingshankou group hydrocarbon source rock expulsive efficiency having more practical significance is provided.

5. a kind of many geologic agents quantitative evaluation expulsive efficiency method as claimed in claim 2, is characterized in that: described step 4) in, set up single geologic agent and expulsive efficiency evaluation model, obtain single geologic agent and expulsive efficiency mathematical relation, specific as follows:

P=a × ln (TOC)+b formula (4-1)

The abundance of organic matter determined and expulsive efficiency single factor evaluation model formation (4-2) are:

P=26.69 × ln (TOC)+29.45 formula (4-2)

P=a × exp (b × Ro _kT)-c formula (4-3)

Ro under the different organic matter type constraints determined and expulsive efficiency single factor evaluation modular form (4-4) are:

P=0.558 × exp (6.1 × Ro _kT)-30.85 formulas (4-4)

P=a × Ro _yCPZ× Ro _yCPZ+ b × Ro _yCPZ+ c formula (4-5)

The not homology determined is stored up the Ro under configuration relation constraint and with expulsive efficiency single factor evaluation model (formula 4-6) is:

P=-2258 × Ro _yCPZ× Ro _yCPZ+ 4660.68 × Ro _yCPZ-2321 formulas (4-6);

In formula: P represents hydrocarbon source rock expulsive efficiency; TOC refers to abundance of organic matter; Ro _(T)refer to the Ro under different kerogen type constraint and the Ro in expulsive efficiency relation, Ro _yCPZrefer to the Ro under not homology storage configuration control and the Ro in expulsive efficiency relation.

6. a kind of many geologic agents quantitative evaluation expulsive efficiency method as claimed in claim 2, is characterized in that: described step 5) in, set up multiple geologic agent and expulsive efficiency mathematics appraisal, specific as follows:

Consider the internal factor and external factor that affect hydrocarbon source rock expulsive efficiency, rely on step 4) in the logarithmic relationship of the abundance of organic matter determined and expulsive efficiency, organic matter type retrain under degree of ripeness and the exponential relationship of expulsive efficiency, source store up configuration relation retrain under maturity of organic matter and the polynomial relation of expulsive efficiency; Set up the evaluation model (formula 5-1) of multiple geologic agent and expulsive efficiency, realize multiple geologic agent quantitative evaluation hydrocarbon source rock expulsive efficiency;

P＝P _NY×P _WY

=(f (TOC)+f (Ro _kT) × f (Ro _yCPZ) formula (5-1)

The multiple geologic agent determined evaluates expulsive efficiency mathematical model:

P＝P _NY×P _WY

＝0.93×(1.92×ln(TOC)+28.13×exp(Ro _KT)-61.72)

× (-5.6 × Ro _yCPZ× Ro _yCPZ-0.895 × Ro _yCPZ+ 8.03) formula (5-2)

In formula: P represents expulsive efficiency, P _nYrepresent expulsive efficiency influnecing factor, P _wYrepresent expulsive efficiency external influence factors; TOC refers to abundance of organic matter, (Ro _kT) refer to the relation of Ro under different kerogen type constraint and expulsive efficiency, Ro _yCPZrefer to the relation of Ro under not homology storage configuration constraint and expulsive efficiency;

According to step 4) in the data relationship of each single geologic agent model determined, guarantee the accuracy of often kind of geologic agent contribution form, set up the evaluation model (formula 5-2) of many geologic agents and hydrocarbon source rock expulsive efficiency, realizing many geologic agents quantitative evaluation expulsive efficiency, laying the foundation for evaluating the three-dimensional expulsive efficiency of destination layer position hydrocarbon source rock.