CN109184677A - Reservoir evaluation methods for heterogeneous alternating layers sand body - Google Patents
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Abstract
本发明公开了用于非均质互层砂体的储层评价方法，通过本方法得到每个小层的综合评价指数CEI，从而得到各小层储层分类评价结果。本方法相较于现有技术计算过程简单方便，普通地质研究人员均可实现，解决了现有的储层定量评价需要复杂的数学理论为基础的问题，使得对于非均质互层砂体储层的综合定量评价能够真正走出科研院校与高级实验室，深入到油气开发基层设计人员，为非均质护层砂体的评估与开发提供有效的地质指导，能够有效减少开发前期的误判，实现理论研究与实际开发的充分结合。
The invention discloses a reservoir evaluation method for heterogeneous interbedded sand bodies. Through the method, the comprehensive evaluation index CEI of each sublayer is obtained, thereby obtaining the classification evaluation results of each sublayer. Compared with the prior art, the calculation process of the method is simple and convenient, and can be implemented by ordinary geological researchers. The comprehensive quantitative evaluation of layers can truly go out of scientific research institutions and advanced laboratories, and go deep into the basic-level designers of oil and gas development, providing effective geological guidance for the evaluation and development of heterogeneous protective layer sand bodies, and can effectively reduce misjudgments in the early stage of development. , to achieve the full combination of theoretical research and practical development.
Description
Technical field
The present invention relates to oil and gas development fields, and in particular to the reservoir evaluation methods for heterogeneous alternating layers sand body.
Background technique
Reservoir heterogeneity refers to the inhomogeneities of the parameter of characterization reservoir spatially, is the universal feature of reservoir.?
It develops in evaluating reservoir, the heterogeneity of reservoir refers to that reservoir has dual heterogeneity, i.e., the rock of preservation fluid is non-
The fluid properties of preservation and the heterogeneity of occurrence in homogenieity and rock space.Reservoir heterogeneity had both included reservoir macroscopic view hair
Feature heterogeneity is educated, also includes micropore structure heterogeneity etc..The content of reservoir Journal of Sex Research is varied, main
Will include reservoir heterogeneity classification, evaluation, genetic analysis, the influence to reservoir property and fluid properties, to oil-gas field development
Influence etc..Reservoir thickness, reservoir properties and heterogeneity analysis shows, reservoir plane difference is big, heterogeneous strong, in conjunction with plane
In upper different zones gas well liquid loading feature show the heterogeneity in this plane of reservoir be influence gas well deliverability it is important because
Element.
For heterogeneous alternating layers sand body, existing Comprehensive evaluation of reservoir is more, mainly include qualitative evaluation and
Quantitative assessment two major classes.Qualitative evaluating method is applied to a long time ago, mainly according to reservoir porosity, the height of permeability
It is low, reservoir is divided into, in, poor three ranks, in combination with the textural maturity of rock, diagenesis, micro throat feature
Deng the storage and collection performance of evaluation reservoir.This qualitative evaluation is affected by human factors larger, the research people with different operating experience
For member to the same evaluation goal, evaluation result may have larger difference.This qualitative evaluating method by rule of thumb, artificially,
It there may come a time when that the evaluation to make mistake can be done.Therefore, Quantitative Evaluation of Reservoirs method is development trend in recent years.Quantitative Evaluation of Reservoirs
Method includes grey system theory, Principal Component Analysis, clustering methodology, analytic hierarchy process (AHP), neural network, fractal theory
Method etc..The introducing of these modern mathematics geological methods promotes the raising of evaluating reservoir research level.Gray system theory is first
Taught by Huazhong University of Science and Technology Deng Julong and put forward first in 1987, be sought by grey correlation analysis in system it is each because
The prevailing relationship of element finds out an important factor for influencing every evaluation index, to grasp the main feature of things, that is, passes through transformation
Auxiliary sequence and subsequence calculate maximum value, the minimum value of the absolute difference between each sub- factor and female factor, to obtain each son
The incidence coefficient of factor and female factor, finally obtains the weight coefficient of each evaluation parameter.Principal Component Analysis is a kind of multivariable
Analysis method the more variable of number is made into linear combination to achieve the purpose that analysis is simplified, be merged into several main new
Variable-principal component represents the main information of Geological Variable variation in this way with fewer number of principal component.Greatly simplify compression
Data, and reproduced the correlativity of initial data part and its genetic relationship of inherence.Analytic hierarchy process (AHP) is exactly to complexity
Essence, influence factor and its internal relation of decision problem etc. analysed in depth on the basis of, utilize less quantitative letter
Breath makes the thought process mathematicization of decision, to provide letter for multiple target, multiple criteria or complicated decision-making problems without architectural characteristic
Just decision-making technique.It is particularly suitable for the occasion for being difficult to directly accurately measure to the result of decision.It is solved with analytic hierarchy process (AHP) practical
Problem, it is important to according to specifically study a question by a complicated system decomposition be several levels or subsystem, establish level
Structure, Judgement Matricies, and then determine the relative importance of each factor in system.Clustering methodology is a kind of multivariate statistics number
Classification method is learned, by clustering to sample, i.e., by the close and distant relation in property or the origin cause of formation, quantitative classification is carried out to sample.
Each object constitutes a class by itself when cluster starts, then using certain indicate the amount of object close and distant relation as classification foundation, each other it
Between the most intimate object aggregation of relationship merge and sort out, continue to merge further according to the close and distant degree between class, until whole objects are poly-
For one kind.Neural network is by constantly to the study of example, obtaining network weight coefficient.The applications such as Ran Qiquan, virgin filial piety China are fuzzy
The fuzzy neural network of knowledge is sentenced in neural network method, the reservoir well logging established using log data.But it is above-mentioned quantitative
Evaluation method is difficult to accurately grasp and apply based on complicated mathematical theory, for general geological research personnel,
Therefore heterogeneous alternating layers Sandbody Reservoirs comprehensive quantitative evaluation in the prior art only resides in the theory of research institutions, so far
It is not yet widely used in daily oil-gas field development real work.
Summary of the invention
The purpose of the present invention is to provide the reservoir evaluation methods for heterogeneous alternating layers sand body, are existed with solving the prior art
It is difficult to the problem of quantitative assessment is carried out to heterogeneous alternating layers Sandbody Reservoirs in real work, is embodied as general geology researcher and mentions
For the purpose of the heterogeneous reservoir quantitative evaluation method with operability.
The present invention is achieved through the following technical solutions:
Reservoir evaluation methods for heterogeneous alternating layers sand body, comprising the following steps:
(a) well-log information, seismic data, rock core information, Production development data, reservoir heterogeneity research data are combined,
Carry out that reservoir evaluation parameter is preferred, the preferred reservoir evaluation parameter of institute is the N kind in following parameter: lithology, rock texture, diagenesis
Effect, cementation type, supporting way, sedimentary micro, reservoir effective thickness, porosity, permeability, layer intrinsic permeability variation lines
Number, coefficient of advancing by leaps and bounds, differential, be averaged pore throat radius, wherein N >=3；
(b) in all substratums, using extremum method to preferred every kind of reservoir evaluation parameter be normalized, make
For its value between 0~1, normalized value is denoted as Si；It is determined according to variation degree of the every kind of reservoir evaluation parameter in different substratums
The weight coefficient W of each parameter in different substratumsi；
(c) it according to the normalized result and weight coefficient to every kind of reservoir evaluation parameter, is obtained using comprehensive function method
To the comprehensive evaluation index CEI of each substratum,Obtain each substratum reservoir classification and evaluation result: if CEI >=
0.5, then it is I class reservoir；If 0.2 CEI≤0.5 <, for II class reservoir；If CEI < 0.2, for III class reservoir or dried layer.
Aiming at the problem that being difficult to carry out quantitative assessment to heterogeneous alternating layers Sandbody Reservoirs in the prior art in actual operation,
The present invention proposes the reservoir evaluation methods for being used for heterogeneous alternating layers sand body, in this method first with well-log information, seismic data,
Data possessed by the oil gas fields early developments such as rock core information, Production development data, reservoir heterogeneity research data, selection storage
Layer evaluation parameter.Reservoir evaluation parameter is from lithology, rock texture, diagenesis, cementation type, supporting way, sedimentary micro, storage
Layer effective thickness, porosity, permeability, the layer intrinsic permeability coefficient of variation, coefficient of advancing by leaps and bounds, differential, being averaged in pore throat radius selects
At least three kinds, the selection of reservoir evaluation parameter follows following three principles: 1. parameter to reservoir quality have accurately, can quantitatively
Description；2. having relative independentability between each parameter；3. being easy the parameter obtained by conventional means.Those skilled in the art can
To be selected according to the accuracy evaluation of oil field actual conditions, each parameter of acquisition situation and each oil field of existing data,
Selection is at least three kinds any, it is not limited here.After reservoir evaluation parameter chooses, extracts each reservoir evaluation parameter and exist
Value in each substratum, wherein the substratum in this programme refers to Sandbody Reservoirs.Selected parameters have different dimensions, Wu Fazhi
It is connected together and carries out operation, so to be standardized, make them that there is comparability.Specific method is, all small
In layer, using extremum method to preferred every kind of reservoir evaluation parameter be normalized, make its value between 0~1, normalizing
Change value is denoted as Si；It is that its value in all substratums is normalized for each reservoir evaluation parameter,
Obtain corresponding Si.And it is determined in different substratums each according to every kind of reservoir evaluation parameter in the variation degree in different substratums
The weight coefficient W of parameteri；It is to acquire its weight system in each substratum respectively for every kind of reservoir evaluation parameter
Number, to indicate in different substratums, the weight of different reservoir evaluation parameter.The last normalizing according to every kind of reservoir evaluation parameter
Change processing result and the weight coefficient in each substratum, the comprehensive evaluation index of each substratum is obtained using comprehensive function method
CEI,Obtain each substratum reservoir classification and evaluation result: if CEI >=0.5, for I class reservoir；If 0.2 <
CEI≤0.5 is then II class reservoir；If CEI < 0.2, for III class reservoir or dried layer.Wherein CEI >=0.5 is I class reservoir, table
Bright evaluation highest, reservoir properties are best.0.2 CEI≤0.5 < is II class reservoir, is evaluated secondly, reservoir properties are preferable.CEI <
0.2, then it is III class reservoir or dried layer, evaluation is bad, and reservoir properties are bad.
Further, further include step (d): utilizing three-dimensional geological model, each substratum reservoir classification and evaluation result is carried out
Numeralization description, obtains the spatial distribution state of each substratum.By the reservoir classification and evaluation result and three to each substratum in this programme
Dimension geological model combines, and obtains spatial distribution state, more intuitive can provide for oil field development person to reservoir distribution
Spatial cognition.
Preferably, the preferred reservoir evaluation parameter of institute is reservoir effective thickness, in porosity, permeability, layer in step (a)
Permeability grade.The geologic parameter of reflection reservoir quality mainly includes that Lithology Characteristics parameter, sedimentary micro, reservoir have
Imitate thickness, porosity, permeability, in-layer heterogeneity, micro throat structure etc..Causality is carried out to each parameter, definition is closed
System and equivalence relation analysis.Lithology Characteristics parameter is such as diagenetic strong and weak, cementing from microcosmic upper reflection reservoir quality
The type of object determines that micro throat feature, i.e. Lithology Characteristics and micro throat feature have causality；Difference is heavy
Product its reservoir thickness of microfacies, in-layer heterogeneity have differences, i.e. sedimentary micro and reservoir thickness, heterogeneity (infiltration in layer
The rate coefficient of variation, the coefficient and differential of advancing by leaps and bounds) for causality；Pore throat character be determine porosity, permeability size it is main micro-
Sight factor.And Lithology Characteristics above-mentioned, sedimentary micro can not be stated with quantitative parameter, and pore throat character parameter only takes
Heart well is likely to obtain.In conclusion choosing reservoir effective thickness, porosity, permeability, differential four parameters of layer intrinsic permeability
For reservoir evaluation parameter, causality, definition relationship and equivalence relation between each parameter have been fully considered, pass through this four parameters
Can effecting reaction go out the geological condition of reservoir.In addition, this programme not only limit only choose reservoir effective thickness, porosity,
The case where permeability, layer intrinsic permeability differential this four parameters, also joins comprising other evaluating reservoirs other than this four parameters
Several selections should also obtain the protection of the application.
Preferably, normalized value Si=Pi/Pmax, wherein PiFor actual value of the reservoir evaluation parameter in specified substratum, Pmax
For maximum value of the reservoir evaluation parameter in all substratums.It is given in this programme and meter is normalized for reservoir evaluation parameter
The specific method of calculation, i.e., by some reservoir evaluation parameter in the actual value in some substratum divided by its maximum in all substratums
Value makes them have comparability to be standardized to all reservoir evaluation parameters.
Preferably, sampling point sequence is carried out to each reservoir evaluation parameter in all substratums, access is worth maximum 10%
The average value of sampling point is as Pmax.This programme is the normalization influenced in order to avoid a certain abnormal maximum to reservoir evaluation parameter
Precision chooses the average value of maximum 10% sampling point of numerical value as P for some reservoir evaluation parametermax, gram
Take the interference of abnormal maximum, it is ensured that normalization precision.
Preferably, the weight coefficient W of each reservoir evaluation parameteriCalculation method are as follows: first pass through VC Method and calculate
Coefficient of variation V of each reservoir evaluation parameter in each substratumi, each reservoir evaluation parameter corresponding weight coefficient in each substratum
Wi=Vi/Vtotal, wherein VtotalIt is summation of the corresponding reservoir evaluation parameter in all substratums.Consider parameters to reservoir
The variation degree of various parameter values is different when the influence degree of quality is different or reservoir quality changes, it is therefore desirable to determine
The weight coefficient of different parameters is to ensure computational accuracy.VC Method can reflect a certain parameter in the reservoir of different quality
The case where middle variation, changes more violent (i.e. susceptibility is stronger), and the coefficient of variation is bigger, then its weight is also bigger.
It further, include following substratum divided method: 1. with index bed in the foundation of the three-dimensional geological model
For control layer position, sedimentary sand bodies in short range continuous-stable, well log curve form is similar, similar in formation thickness
Layer of sand is divided into same substratum；2. well log curve is presented natural potential amplitude and becomes smaller or become sand body thinning or pinching suddenly
Straight, the similar layer of sand of density curve characteristic morphology is divided into same substratum；3. well log curve is shown that sand body is stacked, is in box-like
Two phase layers of sand of distribution are divided into same substratum.Dimensional Modeling Technology when traditional oil and gas development, is mostly to be with seismic wave
Basis is with reference to progress with geologic information acquired in prospect pit, and this modeling pattern haves the defects that accuracy is not high.This programme
In carried out based on the well-log information in early development producing well, pass through three substratum divided methods and compare each well logging song simultaneously
Line can significantly improve geology and build to carry out the fine Division and contrast of substratum to interval of interest stratum based on detail correlation of reservoir bed method
The precision and accuracy of mould.
Preferably, sedimentary micro described in step (a) include deposition paleocurrent direction, Sediment Source direction, rock to construction,
Sedimentary structure.Sedimentary micro includes that range is huge and general, to its risk management, calculation amount is excessive, runs counter to this Shen
The original intention that general geology researcher please be facilitate to use, therefore preferably it has been carried out preferably.Wherein, deposit is logical
Cross deposition paleocurrent carrier and carry and be unloaded at crystallizing field, the spread mode of synchronous deposits again by the transformation of crystallizing field paleocurrent and
Resedimentation influences, and the judgement of paleocurrent direction can be research area's target zone extension of sedimentary facies belts and sandbody distribution advantage side
To determine provide important evidence.After determining deposition paleocurrent direction, sedimentary facies research need to further determine that Sediment Source
Direction, to further determine that the predominant direction of sandbody distribution or extension, therefore Sediment Source direction be also can not in sedimentary micro
The research parameter obtained.Lithofacies and sedimentary structure type are the objective records of deposition process, are to reflect that sedimentary facies is most in area
Mainly and most directly indicate.Divided by deposition paleocurrent direction, Sediment Source direction, rock to the synthesis of construction, sedimentary structure
Analysis, can obtain the most accurately recognizing sedimentary micro, those skilled in the art by least calculating and data processing
Can by its reasonable parametrization to as reservoir evaluation parameter carry out using.
Preferably, the deposition paleocurrent direction is explained jointly and is obtained by FMI imaging logging and dipmeter log.
The information that FMI imaging logging and dipmeter log are reflected is the synthesis of structure dip and depositional bedding inclination angle, is utilizing this
When a little data determine deposition paleocurrent direction, structure dip need to be removed, so that depositional bedding when obtaining sandstone deposition is true
Real occurrence situation.
Preferably, the Sediment Source direction passes through the research of deposition ancient landform, heavy mineral research, grain size of sediment analytic approach
One of or various ways obtain.Other than data provided in this programme, it is used for Sediment Source direction in the prior art
Method further include deposition ancient landform research, heavy mineral research, grain size of sediment analysis etc., those skilled in the art can adopt
With.
Compared with prior art, the present invention having the following advantages and benefits:
The present invention is used for the reservoir evaluation methods of heterogeneous alternating layers sand body, obtains the comprehensive evaluation index CEI of each substratum,
To obtain each substratum reservoir classification and evaluation result: if CEI >=0.5, for I class reservoir；If 0.2 CEI≤0.5 < is II
Class reservoir；If CEI < 0.2, for III class reservoir or dried layer.Wherein CEI >=0.5 is I class reservoir, shows to evaluate highest, reservoir
Physical property is best.0.2 CEI≤0.5 < is II class reservoir, is evaluated secondly, reservoir properties are preferable.CEI < 0.2 is then III class reservoir
Or dried layer, evaluation is bad, and reservoir properties are bad.Calculating process is simple and convenient compared to the prior art for this method, and general geology is ground
Studying carefully personnel can be achieved, and solve the problems, such as that existing Quantitative Evaluation of Reservoirs needs complicated mathematical theory for basis, so that right
Research institutions and Advanced Concepts Laboratory can be really walked out in the comprehensive quantitative evaluation of heterogeneous alternating layers Sandbody Reservoirs, are deep into oil gas
Base designer is developed, effective geological control is provided for the assessment and exploitation of heterogeneous sheath sand body, can effectively reduce
Develop the erroneous judgement of early period, the abundant combination of realization theory research and actual development.
Detailed description of the invention
Attached drawing described herein is used to provide to further understand the embodiment of the present invention, constitutes one of the application
Point, do not constitute the restriction to the embodiment of the present invention.In the accompanying drawings:
Fig. 1 is the flow diagram of the specific embodiment of the invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below with reference to embodiment and attached drawing, to this
Invention is described in further detail, and exemplary embodiment of the invention and its explanation for explaining only the invention, are not made
For limitation of the invention.
Embodiment 1:
Reservoir evaluation methods for heterogeneous alternating layers sand body as shown in Figure 1, comprising the following steps: (a) combines well logging
It is excellent to carry out reservoir evaluation parameter for data, seismic data, rock core information, Production development data, reservoir heterogeneity research data
Choosing, the preferred reservoir evaluation parameter of institute are the N kind in following parameter: lithology, rock texture, diagenesis, cementation type, support
It is mode, sedimentary micro, reservoir effective thickness, porosity, permeability, the layer intrinsic permeability coefficient of variation, coefficient of advancing by leaps and bounds, differential, flat
Equal pore throat radius, wherein N >=3；(b) in all substratums, using extremum method to preferred every kind of reservoir evaluation parameter carry out
Normalized makes its value between 0~1, and normalized value is denoted as Si；According to every kind of reservoir evaluation parameter in different substratums
Variation degree determines the weight coefficient W of each parameter in different substratumsi；(c) according to the normalization to every kind of reservoir evaluation parameter
Processing result and weight coefficient obtain the comprehensive evaluation index CEI of each substratum using comprehensive function method,
Obtain each substratum reservoir classification and evaluation result: if CEI >=0.5, for I class reservoir；If 0.2 CEI≤0.5 <, for the storage of II class
Layer；If CEI < 0.2, for III class reservoir or dried layer.
Embodiment 2:
Reservoir evaluation methods for heterogeneous alternating layers sand body as shown in Figure 1 further include on the basis of embodiment 1
Step (d): three-dimensional geological model is utilized, numeralization description is carried out to each substratum reservoir classification and evaluation result, obtains each substratum
Spatial distribution state.The preferred reservoir evaluation parameter of institute is reservoir effective thickness, seeps in porosity, permeability, layer in step (a)
Saturating rate is differential.Normalized value Si=Pi/Pmax, wherein PiFor actual value of the reservoir evaluation parameter in specified substratum, PmaxFor reservoir
Maximum value of the evaluation parameter in all substratums.Sampling point sequence, access are carried out to each reservoir evaluation parameter in all substratums
It is worth the average value of maximum 10% sampling point as Pmax.The weight coefficient W of each reservoir evaluation parameteriCalculation method are as follows: first lead to
It crosses VC Method and calculates coefficient of variation V of each reservoir evaluation parameter in each substratumi, each reservoir evaluation parameter is each small
Corresponding weight coefficient W in layeri=Vi/Vtotal, wherein VtotalIt is summation of the corresponding reservoir evaluation parameter in all substratums.
It include following substratum divided method in the foundation of the three-dimensional geological model: 1. using index bed as control layer position, deposition
Sand body in short range continuous-stable, well log curve form is similar, layer of sand similar in formation thickness be divided into it is same small
Layer；2. well log curve is presented natural potential amplitude and becomes smaller or become straight, density curve feature sand body thinning or pinching suddenly
The similar layer of sand of form is divided into same substratum；3. well log curve is shown that sand body is stacked, draws in two phase layers of sand of box-like distribution
It is divided into same substratum.Sedimentary micro described in step (a) includes deposition paleocurrent direction, Sediment Source direction, rock to construction, heavy
Product construction.The deposition paleocurrent direction is explained jointly and is obtained by FMI imaging logging and dipmeter log.The deposit
Source direction is obtained by one of the research of deposition ancient landform, heavy mineral research, grain size of sediment analytic approach or various ways.
Table 1 is the knot for carrying out the calculating of reservoir evaluation parameter normalized value in the present embodiment to certain oil field block group reservoir
Fruit:
Table 1
Table 2 is the Comprehensive Evaluation of Reservoir parameters weighting coefficient table that is calculated according to table 1:
Table 2
| Parameter | Effective thickness | Porosity | Permeability | Permeability grade |
| The coefficient of variation | 1.232 | 0.326 | 1.285 | 0.474 |
| Weight coefficient | 0.371 | 0.099 | 0.387 | 0.143 |
From the weight coefficient for the different parameters being calculated it is found that permeability weight is maximum in this block, show it to storage
The influence degree of layer quality is also maximum；Secondly differential for effective thickness and layer intrinsic permeability, their influence phases to reservoir quality
It is moderate strength when (weight is respectively 0.371,0.387)；Reservoir quality is influenced the smallest to be porosity, weight is only
0.099。
On the basis of above-mentioned calculated result, continues to use this method and substratum each in the present embodiment is evaluated, obtain
Result as shown in table 3:
Table 3
From upper table it can be concluded that, for certain oil field in this present embodiment, for XXA block, Kh 7-1,2, Kh 3-1
Each substratum reservoir is based on I class High-quality Reservoir；Though 5 substratum subaqueous distributary channel of Kh is developed, by reservoir porosity and permeability
The relatively poor influence of physical property, the part substratum reservoir is based on II class reservoir；Kh 2,1 each substratum of sand group be multiple to educate between tributary
Gulf, subaqueous distributary channel sand agensis, and hole-infiltration physical property is relatively poor, therefore these substratum reservoirs are based on II, Group III reservoir,
Reservoir type is relatively poor.For XXB block, Kh 5, Kh 3-1 substratum are multiple to educate subaqueous distributary channel microfacies, underwater branch river
Road sand has a very wide distribution, sand body porosity, permeability physical property are relatively preferable, mostly based on I class reservoir；Remaining each substratum is because multiple
Educating gulf between tributary, subaqueous distributary channel sand agensis, and reservoir hole, to seep physical property relatively poor, therefore based on II, Group III reservoir.
Above-described specific embodiment has carried out further the purpose of the present invention, technical scheme and beneficial effects
It is described in detail, it should be understood that being not intended to limit the present invention the foregoing is merely a specific embodiment of the invention
Protection scope, all within the spirits and principles of the present invention, any modification, equivalent substitution, improvement and etc. done should all include
Within protection scope of the present invention.
Claims (10)
1. being used for the reservoir evaluation methods of heterogeneous alternating layers sand body, which comprises the following steps:
(a) well-log information, seismic data, rock core information, Production development data, reservoir heterogeneity research data are combined, is carried out
Reservoir evaluation parameter is preferred, preferred reservoir evaluation parameter be N kind in following parameter: lithology, rock texture, diagenesis are made
With, cementation type, supporting way, sedimentary micro, reservoir effective thickness, porosity, permeability, the layer intrinsic permeability coefficient of variation,
It advances by leaps and bounds coefficient, differential, average pore throat radius, wherein N >=3；
(b) in all substratums, using extremum method to preferred every kind of reservoir evaluation parameter be normalized, make its value
Between 0~1, normalized value is denoted as Si；It is determined according to variation degree of the every kind of reservoir evaluation parameter in different substratums different
The weight coefficient W of each parameter in substratumi；
(c) it according to the normalized result and weight coefficient to every kind of reservoir evaluation parameter, is obtained often using comprehensive function method
The comprehensive evaluation index CEI of a substratum,Obtain each substratum reservoir classification and evaluation result: if CEI >=0.5,
It is then I class reservoir；If 0.2 CEI≤0.5 <, for II class reservoir；If CEI < 0.2, for III class reservoir or dried layer.
2. the reservoir evaluation methods according to claim 1 for heterogeneous alternating layers sand body, which is characterized in that further include step
Suddenly (d): utilizing three-dimensional geological model, numeralization description is carried out to each substratum reservoir classification and evaluation result, obtains the sky of each substratum
Between distribution situation.
3. the reservoir evaluation methods according to claim 1 for heterogeneous alternating layers sand body, which is characterized in that step (a)
Middle preferred reservoir evaluation parameter is that reservoir effective thickness, porosity, permeability, layer intrinsic permeability are differential.
4. the reservoir evaluation methods according to claim 1 for heterogeneous alternating layers sand body, which is characterized in that normalized value
Si=Pi/Pmax, wherein PiFor actual value of the reservoir evaluation parameter in specified substratum, PmaxIt is reservoir evaluation parameter all small
Maximum value in layer.
5. the reservoir evaluation methods according to claim 4 for heterogeneous alternating layers sand body, which is characterized in that all small
Each reservoir evaluation parameter in layer carries out sampling point sequence, and access is worth the average value of maximum 10% sampling point as Pmax。
6. the reservoir evaluation methods according to claim 1 for heterogeneous alternating layers sand body, which is characterized in that each reservoir is commented
The weight coefficient W of valence parameteriCalculation method are as follows: first pass through VC Method and calculate each reservoir evaluation parameter in each substratum
Coefficient of variation Vi, each reservoir evaluation parameter corresponding weight coefficient W in each substratumi=Vi/Vtotal, wherein VtotalIt is pair
Summation of the reservoir evaluation parameter answered in all substratums.
7. the reservoir evaluation methods according to claim 2 for heterogeneous alternating layers sand body, which is characterized in that the three-dimensional
It include following substratum divided method in the foundation of geological model: 1. using index bed as control layer position, sedimentary sand bodies close
In distance range continuous-stable, well log curve form is similar, layer of sand similar in formation thickness is divided into same substratum；2. sand
Body thinning or pinching suddenly, well log curve are presented natural potential amplitude and become smaller or become straight, and density curve characteristic morphology is similar
Layer of sand be divided into same substratum；3. well log curve is shown that sand body is stacked, it is same to be divided into the two phase layers of sand that box-like is distributed
Substratum.
8. the reservoir evaluation methods according to claim 1 for heterogeneous alternating layers sand body, which is characterized in that step (a)
Described in sedimentary micro include deposition paleocurrent direction, Sediment Source direction, rock to construction, sedimentary structure.
9. the reservoir evaluation methods according to claim 8 for heterogeneous alternating layers sand body, which is characterized in that the deposition
Paleocurrent direction is explained jointly and is obtained by FMI imaging logging and dipmeter log.
10. the reservoir evaluation methods according to claim 8 for heterogeneous alternating layers sand body, which is characterized in that described heavy
Product source direction is obtained by one of the research of deposition ancient landform, heavy mineral research, grain size of sediment analytic approach or various ways
It arrives.
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