CN109388827A - The non-homogeneous Geological Modeling of small scale and system of shale oil and gas reservoir - Google Patents
The non-homogeneous Geological Modeling of small scale and system of shale oil and gas reservoir Download PDFInfo
- Publication number
- CN109388827A CN109388827A CN201710676748.7A CN201710676748A CN109388827A CN 109388827 A CN109388827 A CN 109388827A CN 201710676748 A CN201710676748 A CN 201710676748A CN 109388827 A CN109388827 A CN 109388827A
- Authority
- CN
- China
- Prior art keywords
- cell type
- type
- small scale
- probability
- happening
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Investigation Of Foundation Soil And Reinforcement Of Foundation Soil By Compacting Or Drainage (AREA)
Abstract
Disclose the non-homogeneous Geological Modeling of small scale and system of a kind of shale oil and gas reservoir.This method may include: the analysis according to core sample as a result, determining the content of mineral type and each mineral type；According to mineral type, the scale of determination unit type and each unit, and then establish the corresponding small-scale model of each mineral type；According to the content of mineral type, transition probability matrix is obtained；According to the analysis of core sample as a result, determining the cell type and distribution pattern in different depth section；According to cell type and distribution pattern, the thickness of determination unit type, and then obtain small scale geological model.The present invention is directed to the microcosmic complexity of three hole of shale oil and gas reservoir, and stratiform, lamellar construction feature, Markov Chain method based on stochastic simulation realizes the small scale Geologic modeling of shale reservoir, the fine-grained sediment feature and three pore characters of meticulous depiction shale reservoir.
Description
Technical field
The present invention relates to Review of geologic model building techniques fields in oil-gas exploration, more particularly, to a kind of shale oil and gas reservoir
The non-homogeneous Geological Modeling of small scale and system.
Background technique
Establish the concrete embodiment that GEOLOGICAL MODELS OF PETROLEUM RESERVOIR is reservoir description and reservoir characterization end result, and current oil gas storage
The core content and leading edge of layer geology research.The heterogeneity of subsurface reservoir is that one of progress reservoir modeling is not easily overcome
Difficulty mainly simulates reservoir property using various Method of Stochastic both at home and abroad, such as Sequential Indicator Simulation, sequential height in recent years
This simulation, indicator principal component simulation, Bayesian model, Boolean simulation, simulated annealing, estimation add error simulation, alternative manner etc.
Deng.The central idea of stochastic modeling is to achieve the purpose that reservoir characterization by the geological statistics feature of " reproduction " reservoir property, with
Random function is theory, generates optional, equiprobable, high-precision GEOLOGICAL MODELS OF PETROLEUM RESERVOIR, simulation by some random algorithms
It is identical as known statistical nature information to make it for a certain property distribution of geologic body, thus reach simulation each parameter value of reservoir, these
The heterogeneity of method describing reservoir mainly uses variogram or covariance function.However, the variation based on geostatistics
Function model cannot preferably characterize the continuity of complex space, main reason is that its ratio that cannot integrate geological type,
The geological statistics information such as the migration trend converted mutually and average length.And just based on markovian geostatistical model
In contrast, based on the Reservoir Stochastic Modeling of Markov chain model using conditional probability, that is, the concept of transition probability.
For variogram, transition probability is easier to do geologic relevant explanation, which can more accurately describe respectively
The spatial of kind geologic body.Liu Zhenfeng et al. (2003,2005) has carried out the stochastic simulation of Reservoir Lithofacies spatial distribution, with
Walther phase rule is foundation, and the transition probability square of lateral lithofacies is estimated by the transfer count matrix between vertical different lithofacies
Battle array, obtains preferable analog result.But for shale reservoir, in addition to there is different types of lithofacies, there are also the heavy of layer and lamina
Product feature and complicated pore structure.Therefore, it is necessary to develop a kind of non-homogeneous Geologic modeling of small scale of shale oil and gas reservoir
Method and system.
The information for being disclosed in background of invention part is merely intended to deepen the reason to general background technique of the invention
Solution, and it is known to those skilled in the art existing to be not construed as recognizing or imply that the information is constituted in any form
Technology.
Summary of the invention
The invention proposes the non-homogeneous Geological Modelings of small scale and system of a kind of shale oil and gas reservoir, are directed to page
Microcosmic complexity and stratiform, the lamellar construction feature of three hole of shale oil gas reservoir, the Markov Chain based on stochastic simulation
Method realizes the small scale Geologic modeling of shale reservoir, the fine-grained sediment feature and three pore characters of meticulous depiction shale reservoir.
According to an aspect of the invention, it is proposed that the non-homogeneous Geological Modeling of small scale of shale oil and gas reservoir a kind of.
The method may include: according to the analysis of core sample as a result, determining the content of mineral type and each mineral type；According to
The mineral type, the scale of determination unit type and each unit, and then establish the corresponding small scale mould of each mineral type
Type；According to the content of the mineral type, transition probability matrix is obtained；According to the analysis of the core sample as a result, determining not
With the cell type and distribution pattern of depth intervals；According to the cell type and the distribution pattern, the unit class is determined
The thickness of type, and then obtain small scale geological model.
Preferably, if the cell type in the section is layer, the probability of happening based on this layer that spatial position is calculated
With bottom probability of happening, the small scale geological model in the section is assembled by layer.
Preferably, if the cell type in the section is lamina, the generation based on the lamina that spatial position is calculated
Probability and bottom probability of happening, the small scale geological model in the section is assembled by lamina.
Preferably, the probability of happening are as follows:
Wherein, Zi,jThe cell type of representation space position (i, j), SlIndicate the cell type of definition,It indicates longitudinal to turn
The element in probability matrix at (m, k) is moved,Indicate the element in horizontal transfer probability matrix at (l, k),It represents separate
Right side boundary at known to cell type, Zi-1,jIt is the known cell type of adjacent left side neighborhood, Zi,j-1It is its upper layer
Known cell type,Represent (Nx- i) power side.
Preferably, the bottom probability of happening are as follows:
Wherein, Zi,jThe cell type of representation space position (i, j), SlIndicate the cell type of definition,It indicates longitudinal to turn
The element in probability matrix at (m, k) is moved,Indicate the element in horizontal transfer probability matrix at (l, k),It represents remote
From right side boundary at known to cell type, Zi-1,jIt is the known cell type of adjacent left side neighborhood, Zi,j-1It is thereon
The known cell type of layer,Represent (Nx- i) power side.
According to another aspect of the invention, it is proposed that a kind of non-homogeneous Geologic modeling system of the small scale of shale oil and gas reservoir
System, may include: memory, is stored with computer executable instructions；Processor, the processor are run in the memory
Computer executable instructions execute following steps: according to the analysis of core sample as a result, determining mineral type and each mineral substance
The content of type；According to the mineral type, the scale of determination unit type and each unit, and then establish each mineral type pair
The small-scale model answered；According to the content of the mineral type, transition probability matrix is obtained；According to the analysis of the core sample
As a result, determining the cell type and distribution pattern in different depth section；According to the cell type and the distribution pattern, determine
The thickness of the cell type, and then small scale geological model.
Preferably, if the cell type in the section is layer, the probability of happening based on this layer that spatial position is calculated
With bottom probability of happening, the small scale geological model in the section is assembled by layer.
Preferably, if the cell type in the section is lamina, the generation based on the lamina that spatial position is calculated
Probability and bottom probability of happening, the small scale geological model in the section is assembled by lamina.
Preferably, the probability of happening are as follows:
Wherein, Zi,jThe cell type of representation space position (i, j), SlIndicate the cell type of definition,It indicates longitudinal to turn
The element in probability matrix at (m, k) is moved,Indicate the element in horizontal transfer probability matrix at (l, k),It represents remote
From right side boundary at known to cell type, Zi-1,jIt is the known cell type of adjacent left side neighborhood, Zi,j-1It is thereon
The known cell type of layer,Represent (Nx- i) power side.
Preferably, the bottom probability of happening are as follows:
Wherein, Zi,jThe cell type of representation space position (i, j), SlIndicate the cell type of definition,It indicates longitudinal to turn
The element in probability matrix at (m, k) is moved,Indicate the element in horizontal transfer probability matrix at (l, k),It represents remote
From right side boundary at known to cell type, Zi-1,jIt is the known cell type of adjacent left side neighborhood, Zi,j-1It is thereon
The known cell type of layer,Represent (Nx- i) power side.
The beneficial effects of the present invention are: on the basis of lithofacies modeling, it is contemplated that stratiform, the lamellar structure of shale,
And organic matter, hole and crack, the reservoir model comprising hole, crack, organic hole generated in this way can more really reflect
The truth of underground keeps description to shale reservoir heterogeneity and understanding more reasonable, can be in later period reservoir exploitation
Oil-gas reservoir engineering numerical establishes solid foundation.
Methods and apparatus of the present invention has other characteristics and advantages, these characteristics and advantages are attached from what is be incorporated herein
It will be apparent in figure and subsequent specific embodiment, or will be in the attached drawing being incorporated herein and subsequent specific reality
It applies in mode and is stated in detail, the drawings and the detailed description together serve to explain specific principles of the invention.
Detailed description of the invention
Exemplary embodiment of the present is described in more detail in conjunction with the accompanying drawings, of the invention is above-mentioned and other
Purpose, feature and advantage will be apparent, wherein in exemplary embodiments of the present invention, identical reference label is usual
Represent same parts.
Fig. 1 shows the stream of the step of small scale non-homogeneous Geological Modeling of shale oil and gas reservoir according to the present invention
Cheng Tu.
Fig. 2 shows the schematic diagrames of shale core according to an embodiment of the invention.
Fig. 3 shows the schematic diagram of small scale geological model according to an embodiment of the invention.
Fig. 4 shows the signal for the geological model that lamina proportion according to an embodiment of the invention is 10%
Figure.
Fig. 5 shows the signal for the geological model that lamina proportion according to an embodiment of the invention is 30%
Figure.
Fig. 6 shows the signal for the geological model that lamina proportion according to an embodiment of the invention is 50%
Figure.
Fig. 7 shows the porosity distribution for the geological model that porosity according to an embodiment of the invention is 5.0%
The schematic diagram of figure.
Fig. 8 shows the porosity distribution for the geological model that porosity according to an embodiment of the invention is 10.0%
The schematic diagram of figure.
Specific embodiment
The present invention will be described in more detail below with reference to accompanying drawings.Although showing the preferred embodiment of the present invention in attached drawing,
However, it is to be appreciated that may be realized in various forms the present invention and should not be limited by the embodiments set forth herein.On the contrary, providing
These embodiments are of the invention more thorough and complete in order to make, and can will fully convey the scope of the invention to ability
The technical staff in domain.
Fig. 1 shows the stream of the step of small scale non-homogeneous Geological Modeling of shale oil and gas reservoir according to the present invention
Cheng Tu.
In this embodiment, the non-homogeneous Geological Modeling of small scale of shale oil and gas reservoir according to the present invention can wrap
It includes:
Step 101, according to the analysis of core sample as a result, determining the content of mineral type and each mineral type.
Step 102, according to mineral type, the scale of determination unit type and each unit, and then each mineral substance is established
The corresponding small-scale model of type；In one example, if the cell type in section is layer, the hair of this layer is calculated based on spatial position
Raw probability and bottom probability of happening, the small scale geological model in the section is assembled by layer；In one example, if the unit in section
Type is lamina, and probability of happening and bottom probability of happening based on the lamina that spatial position is calculated assemble this by lamina
The small scale geological model in section.
In one example, probability of happening are as follows:
Wherein, Zi,jThe cell type of representation space position (i, j), SlIndicate the cell type of definition,Indicate longitudinal
Element in transition probability matrix at (m, k),Indicate the element in horizontal transfer probability matrix at (l, k),It represents remote
From right side boundary at known to cell type, Zi-1,jIt is the known cell type of adjacent left side neighborhood, Zi,j-1It is thereon
The known cell type of layer,Represent (Nx- i) power side.
In one example, bottom probability of happening are as follows:
Wherein, Zi,jThe cell type of representation space position (i, j), SlIndicate the cell type of definition,Indicate longitudinal
Element in transition probability matrix at (m, k),Indicate the element in horizontal transfer probability matrix at (l, k),It represents remote
From right side boundary at known to cell type, Zi-1,jIt is the known cell type of adjacent left side neighborhood, Zi,j-1It is thereon
The known cell type of layer,Represent (Nx- i) power side.
Step 103, according to the content of mineral type, transition probability matrix is obtained.
Step 104, according to the analysis of core sample as a result, determining the cell type and distribution pattern in different depth section；
Step 105, according to cell type and distribution pattern, the thickness of determination unit type, and then small scale geology is obtained
Model.
Fig. 2 shows the schematic diagrames of shale core according to an embodiment of the invention.
Specifically, the key that shale reservoir is different from conventional reservoir research is its " non-homogeneous ", as shown in Fig. 2, numerical value is built
Mould should embody this main feature, cannot pass through " duplication " core sample and obtain large-scale model, it is necessary to from sedimentation with
Machine process is set out.But core sample is the key that the foundation for obtaining this random process governing factor.From " uniform " to " non-
Petrophysical model will uniformly " be made too many variation occur, " non-homogeneous " there will be different performances under different scale, therefore model
In will catch shale reservoir key factor heterogeneous: laminated texture, layer structure, shale minerals component, point of hole and crack
Cloth feature.The non-homogeneous of geological model is typical fractal structure, can infinitely be segmented under different scale.For shale reservoir
Geologic feature, main feature will be caught in modeling, determination unit type is " layer " and " lamina ", by the scale of vertical " layer "
It is defined on " decimetre " magnitude, the scale of " lamina " is defined on " millimeter " magnitude, and laterally scale heterogeneous is defined on " 10
Rice " magnitude.Mineral constituent mainly considers several main components, for existing sample, the component of use are as follows: clay, calcite, stone
English and organic matter.
Small-scale model is generated using two-dimentional Markov chain model.For this purpose, by with " layer " and " lamina " of certain length
For unit, and each " layer " and " lamina " can be made of different lithofacies, and " layer " or " lamina " of different type lithofacies is singly
Member constitutes the basic unit of composition model；Geological model is indicated with model (i, j), certain corresponding class lithofacies of model (i, j)
" layer " or " lamina " unit.In each two-dimensional spatial location (i, j), is combined by vertical and horizontal transition probability matrix and determine difference
The probability of happening of new events (basic units of i.e. all kinds of different lithofacies), these probability sequences is arranged, forming a length is 1
Number axis；Random number is generated using computer, random number falls in that section of number axis, is exactly that generate that class substantially single at this
Member calculates probability of happening according to formula (1).
It the case where horizontal transfer probability matrix cannot be provided clearly to majority, can be with by pair in vertical transfer probability matrix
Angle element amplifies certain multiple and carrys out approximately transversely transition probability matrix, this multiple size reflects laterally uniform journey just
Degree.To there is no borehole restraint situation, to complete two dimension modeling, need to first using one-dimensional Markov chain model generate model (i, j) and
model(Nx, j), define model (i, j)=model (Nx,j)；Model (i, j) generates SkProbability be
For complete two dimension modeling, also need to bottom initialize, that is, determine bottom lithofacies sequence (its stratification type with most it is left and
Right side is consistent)；This is also needed using one-dimensional Markov chain model, and model (i, j) generates SkProbability, as bottom occurs general
Rate is formula (2).
It theoretically, is that can guarantee total rock when the time-histories long enough of random process if transition probability matrix is given accurate
It mutually constitutes consistent with measurement.In real work, due to the limitation of core amount and observation, it is based on statistical method or empirical vertical
It is always approximate to transition probability matrix, to guarantee that it is consistent with measurement that the lithofacies for generating model are constituted, it is being based on Markov Chain
When random process generates geological model, it will be constituted according to the lithofacies for having generated model, modify the probability of happening of different basic units,
Guarantee that its lithofacies of the whole geological model of output are constituted to coincide with given value.Specific implementation method is: being based on probability of happening
Generate a layer model, i.e. model (i, j) (j=1, Nx) after, the basic unit content ratio for having generated model is calculated, with the ratio
Example value is compared with the ratio value that observation obtains, and is obtained the opposite variation of various basic unit contents, is modified with this by Markov
The P that chain model obtainsr, new one layer of model is generated with this.
It discusses based on the above principles, following modeling procedure can be established: analyzing known core sample, define different lithofacies classes
" layer " or " lamina " basic unit of type；Transition probability matrix is estimated, to generate heterogeneous, wavelength dimension shale model.
By typical core sample analysis as a result, determining the content of calcite, clay, quartz, organic matter.Determine " layer " and
" lamina " basic unit and its ingredient, it is assumed that by taking certain mouthful of shale oil/gas well as an example, determine that " layer " of 3 kinds of different lithofacies is substantially single
Member: layer containing argillaceous limestone, argillaceous limestone layer, grey matter shale layer, scale are defined as 0.1 × 10m；Determine 2 kinds of different lithofacies
" lamina " unit: grey matter lamina, shale lamina, scale are defined as 0.001 × 10m；The scale of " although layer " unit be 0.1 ×
10m, but this unit is actually made of 100 × 10000 discrete points in geological model, the mineral according to unit
Ingredient, these discrete points will respectively correspond calcite, clay or the these types of essential mineral of quartz；Similarly, " lamina " unit is by 1
What × 10000 discrete points were constituted, these discrete points will respectively correspond calcite, clay or the these types of essential mineral of quartz.This
Sample can produce the small-scale model of 0.001 × 0.001m resolution ratio.
It determines transition probability matrix, the mineralogical composition of core sample statistical result and model will be comprehensively considered during this
Content；For core analysis as a result, determining the ratio and distribution pattern of different depth section " layer " and " lamina "；According to " layer " and
The distribution pattern of " lamina " determines and generates " layer " still " lamina " and its thickness in model generating process；If the section generates
" layer " is assembled to obtain the geology in this section based on the probability of happening that spatial position (i, j) is calculated by " layer " basic unit
Model；If the section generates " lamina ", based on the probability of happening that spatial position (i, j) is calculated, by " lamina " basic unit
It assembles to obtain the geological model in this section, generates " background " geological model that resolution ratio is 0.001 × 0.001m, it is each discrete
Point respectively corresponds calcite, clay or quartz；Currently, also not including organic matter, hole and crack in model.
Inserting for organic matter (TOC) is discussed first, will only consider mature organic matter, retouched with the voidage in organic matter
State the presence in organic hole.The organic matter total amount that according to the content of organic matter, will determine that the model has, when addition, will use organic matter
Original in " point " substitution " background " geological model to answer calcite, clay or quartz, the principle of substitution is to complete organic matter addition
The content of calcite in model, clay, quartz and organic matter is exactly equal to measurement result afterwards.
Point three parts are carried out when the addition of TOC, 1) be the random distribution in overall model, the ratio of this general part compared with
It is few；2) be that will determine probability of happening according to its shale content size in " layer " part, random aggregation distribution, space it is random
Property with computer generate two random numbers determine；It 3) will be determined according to the aggregation situation of " lamina " in " lamina " part
TOC content number, organic matter will be distributed along layer, and the content at different transverse direction positions is by Gaussian Profile variation.
The addition of hole is by the different layers position counted according to core sample, the porosity of different lithofacies, in model
Discrete point be assigned to hole, to the discrete point of organic matter, hole corresponds to organic hole.
Interlayer seam and vertical lap seam is further added at random in a model.The crack number of crack total amount is obtained by statistics is close
Degree determines.The direction of vertical lap seam will be controlled by principal direction of stress, will be realized this target by generating two random numbers simultaneously: be used
One random number determines direction, by judge another random number be determine that the crack whether there is in some section, and this
One section is determined by direction, and closer to principal direction of stress, the section is bigger in direction.
In this way, the small scale geology that the resolution ratio comprising hole, crack, organic hole is 0.001 × 0.001m can be obtained
Model, the essential mineral of the corresponding 0.001 × 0.001m of each discrete point of the model, this mineral side of being approximately respectively
Xie Shi, clay, quartz or organic matter.
Fig. 3 shows the schematic diagram of small scale geological model according to an embodiment of the invention.
Complete the above process, so that it may which obtaining the resolution ratio comprising hole, crack, organic hole is the ground of 0.001 × 0.001m
The small scale geological model of wavelength dimension is shaken, (" layer " and " lamina " was tied as shown in figure 3, the model had both considered design feature
Structure), it is also considered that mineral component ratio (clay, calcite, quartz and TOC) further comprises crack and hole.
This method is on the basis of lithofacies model, it is contemplated that the stratiform of shale, lamellar structure and organic matter, hole
And crack, the reservoir model comprising hole, crack, organic hole generated in this way can more really reflect the truth of underground,
Keep description to shale reservoir heterogeneity and understanding more reasonable, can be the oil-gas reservoir engineering Numerical-Mode in later period reservoir exploitation
It is quasi- to establish solid foundation.
Using example
A concrete application example is given below in the scheme and its effect of the embodiment of the present invention for ease of understanding.This field
It should be understood to the one skilled in the art that the example is only for the purposes of understanding the present invention, any detail is not intended to be limited in any way
The system present invention.
It is basic template with certain shale reservoir, changes for the variation of lamina and layer ratio, porosity, mineral content becomes
Change, establishes small scale (1mm × 1mm) geological model of the long scale of seismic wave.
Certain shale reservoir is mainly made of layer containing argillaceous limestone, argillaceous limestone layer and grey matter shale layer three classes lithofacies, three classes
The accounting of lithofacies is 28.6%, 38.2% and 33.2%；When mineral component changes, three classes lithofacies composition is also therewith
Variation；Three classes lithofacies will be respectively formed layer structure and lamellar structure, control laminated texture by respective lamina ratio
How much.It keeps containing argillaceous limestone, argillaceous limestone, the constant rate of three kinds of lithofacies of grey matter mud stone in a model, and keeps every kind of rock
Mineral constituent in phase is constant, only changes ratio of the lamina in every kind of lithofacies, the ratio of lamina is identical in three kinds of lithofacies
And change simultaneously, 50% is progressively increased to from 10%, increases by 10% every time.Accounting, the mine of the three classes lithofacies of each reservoir model
Object component, the parameters such as porosity of three holes are shown in Table 1, and lamina proportion is from 10% to 50%.
Table 1
Fig. 4 shows the signal for the geological model that lamina proportion according to an embodiment of the invention is 10%
Figure, can be observed lamina and layer construction, and tiny laminated structure accounting is less.Fig. 5 shows an implementation according to the present invention
Lamina and layer construction, tiny laminated structure can be observed in the schematic diagram for the geological model that the lamina proportion of example is 30%
Increase compared with Fig. 4.Fig. 6 shows the signal for the geological model that lamina proportion according to an embodiment of the invention is 50%
Figure, can be observed lamina and layer construction, and tiny laminated structure increases many compared with Fig. 4.
During porosity variation, as porosity proportion gradually increases, calcite, quartz, shared by clay
Reduction more corresponding than regular meeting, the amount of reduction and their shared ratios in a model are directly proportional.Since TOC content is to reservoir elasticity
Parameter has larger impact, in order to correctly reflect the relationship between porosity and reservoir elastic parameter as far as possible, changes in porosity
During, the TOC content in model remains unchanged.The accounting of the three classes lithofacies of each reservoir model, mineral constituent, crack are close
The parameters such as degree are shown in Table 2, and lamina proportion is 39.2%, porosity 2.5%, 5.0%, 7.5%, 10.0%,
12.5% equal five kinds of situations.
Table 2
Fig. 7 shows the porosity distribution for the geological model that porosity according to an embodiment of the invention is 5.0%
The schematic diagram of figure, Fig. 8 show the porosity for the geological model that porosity according to an embodiment of the invention is 10.0%
The schematic diagram of distribution map, the porosity of visible model is not equally distributed in figure.
In conclusion the present invention is on the basis of lithofacies model, it is contemplated that stratiform, the lamellar structure of shale, Yi Jiyou
Machine matter, hole and crack, the reservoir model comprising hole, crack, organic hole generated in this way can more really reflect underground
Truth keeps description to shale reservoir heterogeneity and understanding more reasonable, can be the oil-gas reservoir in later period reservoir exploitation
Engineering numerical establishes solid foundation.
It will be understood by those skilled in the art that above to the purpose of the description of the embodiment of the present invention only for illustratively saying
The beneficial effect of bright the embodiment of the present invention is not intended to limit embodiments of the invention to given any example.
According to an embodiment of the invention, a kind of non-homogeneous geology modeling of the small scale for providing shale oil and gas reservoir,
It may include: memory, be stored with computer executable instructions；Processor, the computer in processor run memory can be held
Row instruction, executes following steps: according to the analysis of core sample as a result, determining the content of mineral type and each mineral type；
According to mineral type, the scale of determination unit type and each unit, and then establish the corresponding small scale mould of each mineral type
Type；According to the content of mineral type, transition probability matrix is obtained；According to the analysis of core sample as a result, determining different depth area
Between cell type and distribution pattern；According to cell type and distribution pattern, the thickness of determination unit type, and then small scale
Matter model.
In one example, if the cell type in section is layer, the generation of this layer being calculated based on spatial position is general
Rate and bottom probability of happening, the small scale geological model in the section is assembled by layer.
In one example, if the cell type in section is lamina, the hair based on the lamina that spatial position is calculated
Raw probability and bottom probability of happening, the small scale geological model in the section is assembled by lamina.
In one example, probability of happening are as follows:
Wherein, Zi,jThe cell type of representation space position (i, j), SlIndicate the cell type of definition,Indicate longitudinal
Element in transition probability matrix at (m, k),Indicate the element in horizontal transfer probability matrix at (l, k),It represents
Cell type known at separate right side boundary, Zi-1,jIt is the known cell type of adjacent left side neighborhood, Zi,j-1It is it
The known cell type on upper layer,Represent (Nx- i) power side.
In one example, bottom probability of happening are as follows:
Wherein, Zi,jThe cell type of representation space position (i, j), SlIndicate the cell type of definition,Indicate longitudinal
Element in transition probability matrix at (m, k),Indicate the element in horizontal transfer probability matrix at (l, k),It represents
Cell type known at separate right side boundary, Zi-1,jIt is the known cell type of adjacent left side neighborhood, Zi,j-1It is it
The known cell type on upper layer,Represent (Nx- i) power side.
The present invention is on the basis of lithofacies model, it is contemplated that the stratiform of shale, lamellar structure and organic matter, hole
And crack, the reservoir model comprising hole, crack, organic hole generated in this way can more really reflect the truth of underground,
Keep description to shale reservoir heterogeneity and understanding more reasonable, can be the oil-gas reservoir engineering Numerical-Mode in later period reservoir exploitation
It is quasi- to establish solid foundation.
It will be understood by those skilled in the art that above to the purpose of the description of the embodiment of the present invention only for illustratively saying
The beneficial effect of bright the embodiment of the present invention is not intended to limit embodiments of the invention to given any example.
Various embodiments of the present invention are described above, above description is exemplary, and non-exclusive, and
It is not limited to disclosed each embodiment.Without departing from the scope and spirit of illustrated each embodiment, for this skill
Many modifications and changes are obvious for the those of ordinary skill in art field.
Claims (10)
1. a kind of non-homogeneous Geological Modeling of small scale of shale oil and gas reservoir, comprising:
According to the analysis of core sample as a result, determining the content of mineral type and each mineral type；
According to the mineral type, the scale of determination unit type and each unit, and then it is corresponding to establish each mineral type
Small-scale model；
According to the content of the mineral type, transition probability matrix is obtained；
According to the analysis of the core sample as a result, determining the cell type and distribution pattern in different depth section；
According to the cell type and the distribution pattern, the thickness of the cell type is determined, and then obtain small scale geology
Model.
2. the non-homogeneous Geological Modeling of small scale of shale oil and gas reservoir according to claim 1, wherein if the area
Between cell type be layer, the probability of happening and bottom probability of happening of this layer being calculated based on spatial position are assembled by layer
The small scale geological model in the section.
3. the non-homogeneous Geological Modeling of small scale of shale oil and gas reservoir according to claim 1, wherein if the area
Between cell type be lamina, the probability of happening and bottom probability of happening of the lamina being calculated based on spatial position, by line
Layer assembles the small scale geological model in the section.
4. the non-homogeneous Geological Modeling of small scale of shale oil and gas reservoir according to claim 2 or 3, wherein described
Probability of happening are as follows:
Wherein, Zi,jThe cell type of representation space position (i, j), SlIndicate the cell type of definition,Indicate that vertical transfer is general
Element in rate matrix at (m, k),Indicate the element in horizontal transfer probability matrix at (l, k),Represent the separate right side
Cell type known at lateral boundaries, Zi-1,jIt is the known cell type of adjacent left side neighborhood, Zi,j-1Be its upper layer
The cell type known,Represent (Nx- i) power side.
5. the non-homogeneous Geological Modeling of small scale of shale oil and gas reservoir according to claim 2 or 3, wherein described
Bottom probability of happening are as follows:
Wherein, Zi,jThe cell type of representation space position (i, j), SlIndicate the cell type of definition,Indicate that vertical transfer is general
Element in rate matrix at (m, k),Indicate the element in horizontal transfer probability matrix at (l, k),It represents separate
Cell type known at right side boundary, Zi-1,jIt is the known cell type of adjacent left side neighborhood, Zi,j-1It is its upper layer
Known cell type,Represent (Nx- i) power side.
6. a kind of non-homogeneous geology modeling of the small scale of shale oil and gas reservoir, which is characterized in that the system includes:
Memory is stored with computer executable instructions；
Processor, the processor run the computer executable instructions in the memory, execute following steps:
According to the analysis of core sample as a result, determining the content of mineral type and each mineral type；
According to the mineral type, the scale of determination unit type and each unit, and then it is corresponding to establish each mineral type
Small-scale model；
According to the content of the mineral type, transition probability matrix is obtained；
According to the analysis of the core sample as a result, determining the cell type and distribution pattern in different depth section；
According to the cell type and the distribution pattern, the thickness of the cell type, and then small scale geological model are determined.
7. the non-homogeneous geology modeling of the small scale of shale oil and gas reservoir according to claim 6, wherein if the area
Between cell type be layer, the probability of happening and bottom probability of happening of this layer being calculated based on spatial position are assembled by layer
The small scale geological model in the section.
8. the non-homogeneous geology modeling of the small scale of shale oil and gas reservoir according to claim 6, wherein if the area
Between cell type be lamina, the probability of happening and bottom probability of happening of the lamina being calculated based on spatial position, by line
Layer assembles the small scale geological model in the section.
9. the non-homogeneous geology modeling of the small scale of shale oil and gas reservoir according to claim 7 or 8, wherein described
Probability of happening are as follows:
Wherein, Zi,jThe cell type of representation space position (i, j), SlIndicate the cell type of definition,Indicate that vertical transfer is general
Element in rate matrix at (m, k),Indicate the element in horizontal transfer probability matrix at (l, k),It represents separate
Cell type known at right side boundary, Zi-1,jIt is the known cell type of adjacent left side neighborhood, Zi,j-1It is its upper layer
Known cell type,Represent (Nx- i) power side.
10. the non-homogeneous geology modeling of the small scale of shale oil and gas reservoir according to claim 7 or 8, wherein described
Bottom probability of happening are as follows:
Wherein, Zi,jThe cell type of representation space position (i, j), SlIndicate the cell type of definition,Indicate that vertical transfer is general
Element in rate matrix at (m, k),Indicate the element in horizontal transfer probability matrix at (l, k),Represent the separate right side
Cell type known at lateral boundaries, Zi-1,jIt is the known cell type of adjacent left side neighborhood, Zi,j-1Be its upper layer
The cell type known,Represent (Nx- i) power side.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710676748.7A CN109388827A (en) | 2017-08-09 | 2017-08-09 | The non-homogeneous Geological Modeling of small scale and system of shale oil and gas reservoir |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710676748.7A CN109388827A (en) | 2017-08-09 | 2017-08-09 | The non-homogeneous Geological Modeling of small scale and system of shale oil and gas reservoir |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109388827A true CN109388827A (en) | 2019-02-26 |
Family
ID=65414961
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710676748.7A Pending CN109388827A (en) | 2017-08-09 | 2017-08-09 | The non-homogeneous Geological Modeling of small scale and system of shale oil and gas reservoir |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109388827A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112033866A (en) * | 2020-08-20 | 2020-12-04 | 中国地质调查局油气资源调查中心 | Shale classification method and application thereof and shale lithofacies distribution construction system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130297274A1 (en) * | 2011-01-27 | 2013-11-07 | Landmark Graphics Corporation | Methods and systems regarding models of underground formations |
| CN105651966A (en) * | 2016-01-18 | 2016-06-08 | 山东科技大学 | Shale oil and gas high-quality reservoir stratum evaluation method and parameter determination method |
| CN106127816A (en) * | 2016-03-08 | 2016-11-16 | 中国石油大学(华东) | A kind of shale matrix reservoirs interstitial space characterizing method |
-
2017
- 2017-08-09 CN CN201710676748.7A patent/CN109388827A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130297274A1 (en) * | 2011-01-27 | 2013-11-07 | Landmark Graphics Corporation | Methods and systems regarding models of underground formations |
| CN105651966A (en) * | 2016-01-18 | 2016-06-08 | 山东科技大学 | Shale oil and gas high-quality reservoir stratum evaluation method and parameter determination method |
| CN106127816A (en) * | 2016-03-08 | 2016-11-16 | 中国石油大学(华东) | A kind of shale matrix reservoirs interstitial space characterizing method |
Non-Patent Citations (5)
| Title |
|---|
| AMRO ELFEKI 等: "A Markov Chain Model for Subsurface Characterization: Theory and Applications", 《MATHEMATICAL GEOLOGY》 * |
| 刘喜武 等: "基于波场模拟的页岩油气层地震计算岩石物理方法", 《2015油气田勘探与开发国际会议论文集》 * |
| 刘喜武 等: "页岩油气层地震岩石物理计算方法研究", 《石油物探》 * |
| 哈傅 等: "地质过程的计算机模拟", 《地质过程的计算机模拟》 * |
| 霍志周 等: "基于计算岩石物理方法的页岩储层弹性参数提取", 《地球物理学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112033866A (en) * | 2020-08-20 | 2020-12-04 | 中国地质调查局油气资源调查中心 | Shale classification method and application thereof and shale lithofacies distribution construction system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110286421B (en) | Method for modeling natural fractures of tight sandstone reservoir | |
| Zhang | Incorporating geological conceptual models and interpretations into reservoir modeling using multiple-point geostatistics | |
| Hassanpour et al. | Improved geostatistical models of inclined heterolithic strata for McMurray Formation, Alberta, Canada | |
| CN104866653A (en) | Method for acquiring underground three-dimensional density structure | |
| CN106875471A (en) | Coal measures contains or water barrier Visualization Modeling method | |
| Fachri et al. | Fluid flow in relay zones revisited: Towards an improved representation of small-scale structural heterogeneities in flow models | |
| Shekhar et al. | Modelling and simulation of a Jurassic carbonate ramp outcrop, Amellago, High Atlas Mountains, Morocco | |
| Al-Mudhafar et al. | Reservoir sensitivity analysis for heterogeneity and anisotropy effects quantification through the cyclic CO2-Assisted Gravity Drainage EOR process–A case study from South Rumaila oil field | |
| CN105701319A (en) | Sedimentary microfacies modeling method under horizontal well rule development well net | |
| Du et al. | Generalization of dual-porosity-system representation and reservoir simulation of hydraulic fracturing-stimulated shale gas reservoirs | |
| US20110208499A1 (en) | Method for history matching of a geological model comprising a sub-seismic fault network | |
| CN107609265A (en) | A kind of formation stress field Finite Element Method and system based on ant tracking | |
| Conde et al. | Building a 3D geomodel for water resources management: case study in the Regional Park of the lower courses of Manzanares and Jarama Rivers (Madrid, Spain) | |
| Méndez et al. | Rock type prediction and 3D modeling of clastic paleokarst fillings in deeply-buried carbonates using the Democratic Neural Networks Association technique | |
| Doughty et al. | Hydrologic characterization of heterogeneous geologic media with an inverse method based on iterated function systems | |
| Jha et al. | Parameterization of training images for aquifer 3‐D facies modeling integrating geological interpretations and statistical inference | |
| CN109388827A (en) | The non-homogeneous Geological Modeling of small scale and system of shale oil and gas reservoir | |
| Skalinski et al. | Rock type definition and pore type classification of a carbonate platform, Tengiz Field, Republic of Kazakhstan | |
| Doligez et al. | Advanced workflows for joint modelling of sedimentary facies and diagenetic overprint, impact on reservoir quality | |
| CN114153002B (en) | Three-dimensional geological modeling method and device for natural fracture of reservoir, electronic equipment and medium | |
| Sisinni et al. | Facies modeling described by probabilistic patterns using Multi-point statistics an application to the k-field, Libya | |
| Yünsel | Simulation of cement raw material deposits using plurigaussian technique | |
| Quadros et al. | Numerical geological modeling of the karst system from Lajedo Arapuá, Jandaíra Formation, Potiguar Basin | |
| CN110568149B (en) | Fine and rapid quantitative simulation method for hydrocarbon generation and discharge history of sedimentary basin hydrocarbon source rock | |
| CN106646663A (en) | Method for quantitative representation of leakage risk of oil-gas cap rock due to faulting effect |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190226 |
|
| RJ01 | Rejection of invention patent application after publication |