CN107917865A - A kind of tight sandstone reservoir multi-parameter Permeability Prediction method - Google Patents
A kind of tight sandstone reservoir multi-parameter Permeability Prediction method Download PDFInfo
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Abstract
The present invention relates to fine and close heterogeneous sandstone reservoir detailed predicting evaluation field, a kind of tight sandstone reservoir permeability multiparameter prediction method is disclosed.Including：(1) the geology Dominated Factors of permeability in tight sandstone reservoir are determined, geology Dominated Factors include porosity, granularity and development degree of micro cracks in oil；(2) porosity, the logging prediction model and earthquake prediction model of granularity are established；(3) the geology Dominated Factors of development degree of micro cracks in oil are determined；(4) the geology Dominated Factors obtained according to step (3) establish fracture development exponential model；(5) the multi-parameter permeability Comprehensive Model of Seismology and Geology constraint is established.The method of the present invention realizes the individual well of tight sandstone reservoir permeability and the Accurate Prediction of plane under Seismology and Geology MULTIPLE PARAMETERS CONSTRAINT.
Description
Technical field
The present invention relates to fine and close heterogeneous sandstone reservoir detailed predicting evaluation field, especially for complex pore structure,
The evaluating reservoir of porosity correlation difference.A kind of in particular it relates to tight sandstone reservoir multi-parameter Permeability Prediction method.
Background technology
In common reservoir classification and evaluation, generally determine effective reservoir simultaneously as primary evaluation index using porosity
Evaluation of classification is carried out to reservoir.Pore structure is relatively easy, porosity correlation is preferably regional, evaluation result and actual production
Situation has preferable matching.But for the reservoir of complex pore structure, porosity correlation difference, based on porosity
Evaluation result usually has larger difference with actual production situation.It is poly- therefore, it is necessary to be oozed, transported using the storage for being capable of concentrated expression reservoir
Permeability with output capacity carries out the tight sandstone reservoir fine evaluation based on permeability as Basic Evaluation index.Wherein,
The Accurate Prediction of permeability is most important.
Forefathers have established a variety of Permeability Prediction methods and model for fine and close heterogeneous sandstone.Song Ning is (single based on flowing
The heterogeneous sandstone reservoir Permeability Prediction of member classification, 2013) core analysis test and well-log information are integrated, it is new to Song-liao basin
The oil field D404 blocks Putaohua reservoir of standing carries out flow unit division, low hole in foundation, in hypotonic heterogeneous sandstone permeability
Prediction model；Meng Wanbin etc. (2013) oozes quantitative analysis according to the different type sandstone hole based on sandstone petrology feature and oozes
Saturating rate prediction model, studies Chuan Xi Xinchang regions lower chromatic number JS2 Gas Reservoir permeabilities, uses different type respectively
The hole of reservoir oozes quantitative relationship Permeability Prediction model and calculates permeability, improves permeability and asks for precision.Lin Jinglong etc. (is based on dividing
Shape theoretical prediction sandstone reservoir permeability, 2004) blowhole divides shape knot according to the Study on Basic Theoretical of fractal geometry
The definite method of structure and Pore fractal dimension, improves Kozeny-Carman equations, adjusts particle radius and active porosity radius extremely
Suitable for the resolution-scale of power conductive process, so as to establish the fractal model of permeability.Tan (is based on high water cut into thousand
Reservoir permeability interpretation model research, 2001) propose a kind of reservoir permeability means of interpretation based on high water cut,
On the basis of characterizing all kinds of high water cuts, the permeability interpretation model of all kinds of high water cuts is established.Baziar Sadegh
(Prediction of permeability in a tight gas reservoir by using three soft
Computing approaches, 2014) utilize multilayer perceptron neutral net, same period neural fuzzy inference system and support to
The technological prediction of amount machine is located at the permeability of the Mesaverde compacted gas-bearing sandstones in U.S. Mashakie basins, the results showed that, institute
Some methods all have an acceptable performance in terms of permeability is predicted, but same period Neural Net Fuzzy Logic System and support to
Amount machine is more accurate than multilayer perceptron prediction permeability.
At present, it is based primarily upon flow unit point for the Forecasting Methodology and model of fine and close heterogeneous sandstone reservoir permeability
Class, the classification of sandstone group structure, fractal theory and neural network theory etc..These methods are mainly from petrophysical parameter (porosity
F, permeability k, reservoir quality index RQI etc.) set out, by analyzing the typical well log response characteristic of these parameters, using difference
Statistical method establish the Permeability Prediction models of more log parameters.The problem of these methods are primarily present three aspects：1) do not have
There are the geology Dominated Factors of analysis and Control permeability, when there is no obvious correlation between petrophysical parameter and log, then
It is difficult to set up reliable Permeability Prediction model；2) microfissure can be obviously improved the permeability of tight sandstone reservoir.It is but micro-
Crack is since usually without typical well logging, seismic response features, it is always the difficult point in reservoir study to cause FRACTURE PREDICTION；
3) these methods generally only have individual well (point) permeability predictability, do not possess plane predictability mainly for individual well, and
The plane Accurate Prediction of permeability is but exactly tight sandstone reservoir detailed predicting, the key of evaluation.
The content of the invention
The purpose of the invention is to overcome drawbacks described above of the prior art, there is provided a kind of tight sandstone reservoir multi-parameter
Permeability Prediction method.
Specifically, the present invention provides a kind of tight sandstone reservoir multi-parameter Permeability Prediction method, and this method includes：
(1) the geology Dominated Factors of permeability in tight sandstone reservoir are determined, geology Dominated Factors include porosity, granularity
And development degree of micro cracks in oil；
(2) porosity, the logging prediction model and earthquake prediction model of granularity are established；
(3) the geology Dominated Factors of development degree of micro cracks in oil are determined；
(4) the geology Dominated Factors obtained according to step (3) establish fracture development exponential model；
(5) the multi-parameter permeability Comprehensive Model of earthquake-geological constraining is established.
The multi-parameter permeability Comprehensive Prediction Method of the earthquake-geological constraining formed by the method for the present invention, Ke Yishi
The plane Accurate Prediction of existing permeability, the fine evaluation for the heterogeneous tight sandstone reservoir based on permeability lay the foundation, push away
The development of discipline construction has been moved, there is stronger directiveness.
Other features and advantages of the present invention will be described in detail in subsequent specific embodiment part.
Brief description of the drawings
Attached drawing is for providing a further understanding of the present invention, and a part for constitution instruction, with following tool
Body embodiment is used to explain the present invention together, but is not construed as limiting the invention.In the accompanying drawings：
Fig. 1 is the flow chart of Permeability Prediction method in tight sandstone reservoir of the invention.
Embodiment
The embodiment of the present invention is described in detail below.It is it should be appreciated that described herein specific
Embodiment is merely to illustrate and explain the present invention, and is not intended to limit the invention.
The endpoint of disclosed scope and any value are not limited to the accurate scope or value herein, these scopes or
Value should be understood to comprising the value close to these scopes or value.For number range, between the endpoint value of each scope, respectively
It can be combined with each other between the endpoint value of a scope and single point value, and individually between point value and obtain one or more
New number range, these number ranges should be considered as specific open herein.
The present invention provides a kind of tight sandstone reservoir multi-parameter Permeability Prediction method, this method includes：
(1) the geology Dominated Factors of permeability in tight sandstone reservoir are determined, geology Dominated Factors include porosity, granularity
And development degree of micro cracks in oil；
(2) porosity, the logging prediction model and earthquake prediction model of granularity are established；
(3) the geology Dominated Factors of development degree of micro cracks in oil are determined；
(4) the geology Dominated Factors obtained according to step (3) establish fracture development exponential model；
(5) the multi-parameter permeability Comprehensive Model of earthquake-geological constraining is established.
The tight sandstone reservoir of the present invention can be various tight sandstone reservoirs, such as can be Western Sichuan Zhong Jiang gas fields
Jurassic system tight sand, West Sichuan Depression Upper Triassic Xujiahe Formation and Jurassic sandstones, Upper Paleozoic in Ordos Basin sandstone,
One kind in the Jurassic sandstones of Tarim Basin.
Wherein, West Sichuan Depression Zhong Jiang gas fields Type of Fractures In The Jurassic Tight Sandstone belongs to low hole, Low permeability and competent sand reservoir, reservoir
The development of middle microfissure and there is very strong anisotropism, cause the hole of sandstone, to ooze correlation poor.Usually used porosity-
The permeability precision of permeability dependent equation prediction is relatively low, cannot also explain well present in research area's exploration and development practice
" low-porosity, poor reservoir, also can high yield " problem, it is difficult to gas field exploration Development Practice demand in river in adaptation.
Method according to the present invention, it is preferable that in step (1), determine the geology Dominated Factors of the permeability
Method includes：The different tight sandstone reservoir sample of the identical permeability of porosity is subjected to geologic(al) factor comparative analysis, to determine
Influence the geology Dominated Factors of permeability；Those skilled in the art knows that the geologic(al) factor can include the fine and close sand
Porosity, Petrographic Features and the microcrack development degree of rock reservoir samples, wherein, the Petrographic Features preferably include to cause
Rock constituents parameter, rock grain size, psephicity and the sorting of close sandstone reservoir sample, it is highly preferred that the petrofabric parameter
Including clay mineral content and granularity.In the present invention, when carrying out geologic(al) factor comparative analysis, for can quantify geology because
Element, then measure the geologic(al) factor using conventional method, and counts the different tight sandstone reservoir sample of the identical permeability of porosity
In have which quantitative geologic(al) factor different, quantitatively to determine geology Dominated Factors；For can not quantify geologic(al) factor, then
Using the difference of the qualitative geologic(al) factor of the different reservoir samples of the identical permeability of method observation porosity of qualitative observation, with true
Fixed qualitative geology Dominated Factors.In above-mentioned preferably geologic(al) factor, clay mineral content, porosity and rock grain size are quantitative geology
Factor, and psephicity and sorting are qualitative geologic(al) factor.In the present invention, psephicity refers to rock or mineral grain in handling process
It is middle to roll through washing away, hit, corner angle are by the degree of rounding；What sorting represented is the homogeneity of particle.
In the present invention, in step (1), definite geology Dominated Factors can include porosity, granularity and fracture development
Degree.Wherein, granularity can be reflected by median grain diameter.Specifically, the calculating of median grain diameter is referring to following formula (2) or formula
(4)。
Method according to the present invention, the method for establishing the logging prediction model is preferably multiple linear regression method；
Specific step preferably includes：Based on surveying the porosity of sample, granularity, pass through multiple regression procedure, analysis actual measurement hole
Porosity, granularity include the correlation of AC, GR, CNL, DEN and RD with log parameter, wherein, CNL is neutron well logging value, and DEN is close
Log value is spent, RD is resistivity logging value, so as to obtain porosity, the logging prediction model such as formula (1) of granularity and formula (2) institute
Show：
Porosity=0.4853*AC-26.725 formulas (1)
Median grain diameter=2.7943* △ GR+1.7207 formulas (2)
Wherein, AC is acoustic logging value, and unit is μ s/ft, and median grain diameter is granule content on probability cumulative grain size curves
Corresponding particle size values, unit are at 50%GR is gamma logging value, unit API；Wherein, △ GR=(GR-GRmin)/(GR-
GRMax)。
In the present invention, above-mentioned log parameter AC, GR can be obtained according to the logging method of this area routine.In the present invention,
Particle diameter can be represented by the length of the granular fragment major axis of laboratory microscope measure.* in the present invention represents product
Relation.
Method according to the present invention, the method for establishing the earthquake prediction model is preferably multiple linear regression method；
Preferably, shown in the earthquake prediction model such as formula (3) and formula (4) obtained in step (2)：
+ 30.4138 formula (3) of porosity=- 0.0020* wave impedance value
Median grain diameter=- 1.1*10-4*+3.096 formula of wave impedance value (4)
Wave impedance value unit is g/cc*m/s；Porosity units is %, and median grain diameter is probability cumulative grain size curves on
Corresponding particle size values at grain content 50%, unit are
In the present invention, wave impedance value can be obtained by seismic exploration technique, and wave impedance value is that seismic wave passes in rock
The speed broadcast is multiplied by the density of rock.
Method according to the present invention, since microcrack is without typical well logging, seismic response features, causes crack
Prediction is always the difficult point in reservoir study.The present inventor has found that the crack of Zhong Jiang gas fields Jurassic system is sent out under study for action
Degree is educated mainly by sand body configuration, the control away from tomography distance and relevant, curvature etc..Therefore, the present inventor carries under study for action
Having gone out one can be with the parameter of comprehensive characterization development degree of micro cracks in oil, i.e. fracture development index.With reference to seismic multi-attribute FRACTURE PREDICTION
As a result, on the basis of completion sand body configuration, away from data normalizations such as tomography distance, relevant, curvature and earthquake prediction results,
Using multiple linear regression analysis method, the weight coefficient of each parameter is determined, establish the computation model formula (5) of fracture development index, and
Formula according to formula (5) completes the prediction model of development degree of micro cracks in oil.
Fracture development index (FDI)=- 35.219+0.0747* sand bodies configuration -0.010353* away from tomography distance+
36.7045* is concerned with+380.245* curvature formula (5).
Wherein, it is km away from tomography parasang, sand body configuration is divided into homogeneous, heterogeneity, and (1 represents homogeneous, and 2 represent uneven
One), no unit, is concerned with and curvature value is without unit.It is km away from tomography parasang, but when in the formula that substituted into (5) only
Numerical value is substituted into, therefore, the fracture development index (FDI) being calculated is without unit.
In the present invention, the vertical range of prediction sampling point and the tomography of its nearest neighbours is referred to away from tomography distance, is concerned with and bent
Rate is all to calculate to get by the 3D data volume of seismic acquisition, is concerned with and represents sampling point and the correlation of ambient data, phase
Dry values are smaller, and crack is more developed；Curvature is to represent the degree that geologic body changes in subsurface occurrence, and curvature is bigger, and crack is more developed.
Specifically, relevant computational methods can be calculated according to the various conventional methods in this area, such as can use based on multiple
The coherent body technique of seismic channel obtains, and coherent body technique is to describe stratum, rock etc. using the change of seismic signal coherence value
Lateral heterogeneity, and then the spatial distribution of study of fault, micro-fracture, the overall space war cloth of geological structure exception and lithology
Feature.Curvature is the degree of crook according to the seismic reflection lineups of fine and close brittle rock come Prediction of fracture degree.Curvature
It can mathematically be represented by the derivative at inclination angle and inclination angle.
Method according to the present invention, in step (5), permeability integrated forecasting mould is established by multi-parameter fitting method
Shown in type such as formula (6)：
K=e(1.9412+0.25645* porosity -4.11463* median grain diameter+2.50071* fracture developments index)Formula (6)
Wherein, K is permeability, and unit mD, porosity units %, median grain diameter is probability cumulative grain size curves on
Corresponding particle diameter at grain content 50%, unit areWherein, mD refers to millidarcy.
In the present invention, the method for obtaining permeability Comprehensive Model can be the various conventional methods in this area, such as
Can be various conventional multi-parameter fitting methods.
In the present invention, when having Drilling Control (drilling well has log data), data that formula (1) and (2) are calculated with
And the fracture development index that formula (5) obtains is substituted into formula (6) to calculate permeability, when no Drilling Control or has Drilling Control
But during without individual well log data, fracture development index that data and formula (5) that formula (3) and (4) are calculated obtain
Substitute into formula (6) to calculate permeability, so as to achieve the purpose that to predict plane permeability.
The present invention will be described in detail by way of examples below.
The measure of porosity and permeability is to be carried out in the lab by conventional instrument, be fritter core or
Landwaste.Wave impedance value can be obtained by seismic exploration technique, and wave impedance value is that the speed that seismic wave is propagated in rock is multiplied by
The density of rock.AC is sonic log, is time difference Δ t of the slide wave by earth-layer propagation, unit is μ s/ft.Particle diameter is
Measured by laboratory microscope, be subject to granular fragment major axis, unit mm.
Embodiment
The present embodiment is used for the Forecasting Methodology for illustrating permeability in tight sandstone reservoir.
(1) permeability and porosity of Western Sichuan Zhong Jiang gas fields Jurassic system tight sandstone reservoir each sample are measured, by hole
The different tight sandstone reservoir sample of the identical permeability of porosity carries out geologic(al) factor comparative analysis, wherein, geologic(al) factor includes rock
Stone component parameter (including clay mineral content), rock grain size, psephicity, sorting, porosity, microcrack development degree etc. because
Element, it is final to determine that it is blowhole to influence Western Sichuan Zhong Jiang gas fields Jurassic system tight sandstone reservoir permeability geology Dominated Factors
Degree, granularity and microcrack development degree, wherein, granularity can reflect that the calculating of median grain diameter is under by median grain diameter
Formula (2) or formula (4)；
(2) establishing permeability by multiple linear regression method influences the logging prediction model of geology Dominated Factors, specific side
Method is：Based on surveying the porosity of sample, granularity, pass through multiple regression procedure, analysis actual measurement porosity, granularity and well logging
Parameter includes the correlation of AC, GR, CNL, DEN and RD, so that porosity, granularity content logging prediction model are obtained, foundation
Logging prediction model is：
Porosity=0.4853*AC-26.725 formulas (1)
Median grain diameter=2.7943* △ GR+1.7207 formulas (2)
Wherein, AC is acoustic logging value, and unit is μ s/ft, and median grain diameter is granule content on probability cumulative grain size curves
Corresponding particle size values, unit are at 50%GR is gamma logging value, unit API；Wherein, △ GR=(GR-GRmin)/(GR-
GRMax)；
The method for establishing earthquake prediction model is multiple linear regression method；Obtained earthquake prediction model such as formula (3) and formula
(4) shown in：
+ 30.4138 formula (3) of porosity=- 0.0020* wave impedance value
Median grain diameter=- 1.1*10-4*+3.096 formula of wave impedance value (4)
Wave impedance value unit is g/cc*m/s；Porosity units is %, and median grain diameter is probability cumulative grain size curves on
Corresponding particle size values at grain content 50%, unit are
(3) the geology Dominated Factors for determining development degree of micro cracks in oil are sand body configuration, away from tomography distance, relevant and curvature；
(4) measure or calculate sand body configuration in the tight sandstone reservoir sample, away from tomography distance, seismic coherence category
Property and curvature, using multiple linear regression analysis method, determine sand body configuration, away from tomography distance, relevant and curvature weight coefficient, build
Vertical fracture development exponential model, as shown in formula (5),
Fracture development index (FDI)=- 35.219+0.0747* sand bodies configuration -0.010353* away from tomography distance+
36.7045* is concerned with+380.245* curvature formula (5)
Wherein, it is km away from tomography parasang, sand body configuration is divided into homogeneous, heterogeneity, and (1 represents homogeneous, and 2 represent uneven
One), no unit, is concerned with and curvature value is without unit, is km away from tomography parasang, but when in the formula that substituted into (5) only
Numerical value is substituted into, therefore, the fracture development index (FDI) being calculated is without unit；
(5) established by multi-parameter fitting method shown in permeability Comprehensive Model such as formula (6)：
K=e(1.9412+0.25645* porosity -4.11463* median grain diameter+2.50071* fracture developments index)Formula (6)
Wherein, K is permeability, and unit mD, porosity units %, median grain diameter is probability cumulative grain size curves on
Corresponding particle diameter at grain content 50%, unit are
(6) when drilling well has log data, crack that data and formula (5) that formula (1) and (2) are calculated obtain
Developmental index is substituted into formula (6) to calculate permeability, when no Drilling Control or has Drilling Control still without individual well well logging number
According to when, the fracture development index that data and formula (5) that formula (3) and (4) are calculated obtain is substituted into formula (6) in terms of
Permeability is calculated, so that achieve the purpose that to predict plane permeability, wherein, table 1 shows two of the method prediction of the present embodiment
The permeability of sample and the value of the permeability surveyed using existing method and the permeability predicted using one-parameter model,
Table 2 shows the permeability that existing method one-parameter model predicted and the permeability that the present embodiment is predicted and measured value
Between related coefficient comparison.
Table 1
Table 2
Can be seen that the permeability Comprehensive Model established using the present invention by the data of upper table 1 and 2 can be right
The permeability of tight sandstone reservoir is predicted, and the permeability predicted and actual measurement permeability value are closer, and related coefficient reaches
0.88, and be only using the permeability of single parameter Permeability Prediction model prediction and the dependency relation of actual measurement permeability value
0.68, therefore, prediction model of the invention is more accurate compared with prediction of the one-parameter model to tight sandstone reservoir permeability.
The preferred embodiment of the present invention described in detail above, still, during present invention is not limited to the embodiments described above
Detail, in the range of the technology design of the present invention, a variety of simple variants can be carried out to technical scheme, this
A little simple variants belong to protection scope of the present invention.
It is further to note that each particular technique feature described in above-mentioned embodiment, in not lance
In the case of shield, can be combined by any suitable means, in order to avoid unnecessary repetition, the present invention to it is various can
The combination of energy no longer separately illustrates.
In addition, various embodiments of the present invention can be combined randomly, as long as it is without prejudice to originally
The thought of invention, it should equally be considered as content disclosed in this invention.
Claims (7)
- A kind of 1. tight sandstone reservoir multi-parameter Permeability Prediction method, it is characterised in that this method includes：(1) the geology Dominated Factors of permeability in tight sandstone reservoir are determined, geology Dominated Factors include porosity, granularity and split Stitch development degree；(2) porosity, the logging prediction model and earthquake prediction model of granularity are established；(3) the geology Dominated Factors of development degree of micro cracks in oil are determined；(4) the geology Dominated Factors obtained according to step (3) establish fracture development exponential model；(5) the multi-parameter permeability Comprehensive Model of earthquake-geological constraining is established.
- 2. according to the method described in claim 1, wherein, in step (1), determine the geology master of permeability in tight sandstone reservoir The method of control factor includes：The different tight sandstone reservoir sample of the identical permeability of porosity is subjected to geologic(al) factor to score Analysis, to determine to influence the geology Dominated Factors of permeability.
- 3. according to the method described in claim 1, wherein, the method for establishing the logging prediction model is multiple linear regression Method；Preferably, shown in the logging prediction model such as formula (1) and formula (2) obtained in step (2)：Porosity=0.4853*AC-26.725 formulas (1)Median grain diameter=2.7943* △ GR+1.7207 formulas (2)Wherein, AC is acoustic logging value, and unit is μ s/ft, and median grain diameter is granule content 50% on probability cumulative grain size curves Locate corresponding particle size values, unit isGR is gamma logging value, unit API；Wherein, △ GR=(GR-GRmin)/(GR- GRMax)。
- 4. according to the method described in claim 1, wherein, the method for establishing the earthquake prediction model is multiple linear regression Method；Preferably, shown in the earthquake prediction model such as formula (3) and formula (4) obtained in step (2)：+ 30.4138 formula (3) of porosity=- 0.0020* wave impedance valueMedian grain diameter=- 1.1*10-4*+3.096 formula of wave impedance value (4)Wave impedance value unit is g/cc*m/s；Porosity units is %, and median grain diameter is that particle contains on probability cumulative grain size curves Measuring corresponding particle size values, unit at 50% is
- 5. according to the method described in claim 1, wherein, in step (3), the geology Dominated Factors of definite development degree of micro cracks in oil Including：Sand body configuration in the tight sandstone reservoir sample, away from tomography distance, relevant and curvature.
- 6. according to the method described in claim 5, wherein, in step (4), using multiple linear regression analysis method, determine sand body structure Type, away from tomography distance, relevant and curvature weight coefficient, establish fracture development exponential model, as shown in formula (5),Fracture development index (FDI)=- 35.219+0.0747* sand bodies configuration -0.010353* is away from tomography distance+36.7045* phases Dry+380.245* curvature formula (5).
- 7. according to the method described in claim 6, wherein, in step (5), permeability is established by multi-parameter fitting method and is integrated Shown in prediction model such as formula (6)：K=e(1.9412+0.25645* porosity -4.11463* median grain diameter+2.50071* fracture developments index)Formula (6)Wherein, K is permeability, and unit mD, porosity units %, median grain diameter is that particle contains on probability cumulative grain size curves Measuring corresponding particle diameter, unit at 50% is
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Citations (30)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3416376A (en) * | 1966-11-30 | 1968-12-17 | Fuller Co | Surface area measurement of variable length sample of finely divided solids |
| WO1993015389A1 (en) * | 1992-01-24 | 1993-08-05 | Abb Strömberg Drives Oy | Method and apparatus for determination of refiner mechanical pulp properties |
| CN1103165A (en) * | 1993-11-20 | 1995-05-31 | 大庆石油管理局勘探开发研究院 | Automatic measuring instrument for permeability of rock core |
| US5668306A (en) * | 1995-04-28 | 1997-09-16 | Doherty; David L. | Soil analysis method including separate analyses of core sample strata |
| WO2004104560A3 (en) * | 2003-05-21 | 2005-03-24 | Baker Hughes Inc | Formation-based interpretation of nmr data for carbonate reservoirs |
| US7430931B2 (en) * | 2003-08-08 | 2008-10-07 | Konstandinos Zamfes | Microgranulometry and methods of applications |
| US20090055098A1 (en) * | 2007-08-23 | 2009-02-26 | Mese Ali I | Determination of point of sand production initiation in wellbores using residual deformation characteristics and real time monitoring of sand protection |
| CN101937108A (en) * | 2009-07-03 | 2011-01-05 | 中国石油天然气股份有限公司 | Method for determining reserves of hypotonic clastic rock oil and gas reservoir |
| CN102175832A (en) * | 2011-01-10 | 2011-09-07 | 中国石油天然气股份有限公司 | Method for determining optimal saturation calculation model of typical reservoir |
| CN102175529A (en) * | 2011-01-26 | 2011-09-07 | 徐州师范大学 | Creep permeation full-distance coupling test system for broken rock sample |
| CN102507412A (en) * | 2011-11-07 | 2012-06-20 | 中国石油集团川庆钻探工程有限公司 | Crack-matrix permeability grade difference judging method for carbonate reservoir equivalent model |
| CN102608015A (en) * | 2012-03-08 | 2012-07-25 | 长沙理工大学 | Rock mass anisotropy permeability coefficient in-situ test method and device thereof |
| CN103163057A (en) * | 2013-03-18 | 2013-06-19 | 河海大学 | Testing device and measuring and calculating method for gas permeability of compact rock material |
| CN103257081A (en) * | 2013-04-28 | 2013-08-21 | 北京大学 | Method and device for recovering oil and gas reservoir rock mechanics underground in-situ model |
| CN103558358A (en) * | 2013-09-04 | 2014-02-05 | 中国石油天然气股份有限公司 | Method and system for detecting interlayer crack effect of intrastratal heterogeneous model |
| CN103792574A (en) * | 2012-10-30 | 2014-05-14 | 中国石油化工股份有限公司 | Method for detecting frequency-variable gas in storage layer. |
| CN104133040A (en) * | 2014-07-31 | 2014-11-05 | 中国石油大学(北京) | Method and device for predicting favorable distribution and growth range of conventional tight sandstone gas reservoir |
| CN104169714A (en) * | 2012-01-13 | 2014-11-26 | 领英股份有限公司 | Method of determining reservoir properties and quality with multiple energy X-ray imaging |
| CN104614439A (en) * | 2015-02-03 | 2015-05-13 | 中国石油化工股份有限公司胜利油田分公司技术检测中心 | Nondestructive detection device and method based on electric-field fingerprinting method |
| CN104655540A (en) * | 2013-11-19 | 2015-05-27 | 中国石油大学(北京) | Method for determining ancient porosity of compact sandstone in pool-forming period |
| CN104863560A (en) * | 2015-03-09 | 2015-08-26 | 东方宝麟科技发展(北京)有限公司 | Wide-net fracturing method for shale gas exploitation |
| CN104965979A (en) * | 2015-06-16 | 2015-10-07 | 中国石油化工股份有限公司 | Tight sandstone effective reservoir identifying method |
| CN104977196A (en) * | 2014-04-14 | 2015-10-14 | 中国石油化工股份有限公司 | Standard substance used in measurement of permeability, preparation method and application thereof |
| CN104989360A (en) * | 2015-07-10 | 2015-10-21 | 中国石油天然气股份有限公司 | Characterization method of low-permeability reservoir dynamic fracture |
| CN105182424A (en) * | 2015-08-03 | 2015-12-23 | 中国石油天然气股份有限公司 | Method and device for quantitatively predicting reservoir porosity based on patch saturation model |
| CN105372166A (en) * | 2014-08-26 | 2016-03-02 | 中国石油天然气股份有限公司 | Method and device for obtaining permeability of argillaceous sandstone |
| CN105403497A (en) * | 2015-12-08 | 2016-03-16 | 中国石油天然气股份有限公司 | Core permeability evolution simulation method and system |
| CN105510207A (en) * | 2016-01-29 | 2016-04-20 | 河海大学 | Method for determining sensitivity of crack rock mass permeability in all directions to porosity |
| CN105628586A (en) * | 2016-02-19 | 2016-06-01 | 北京理工大学 | Method for determining permeability of porous medium |
| CN105954801A (en) * | 2016-06-12 | 2016-09-21 | 成都理工大学 | Frequency-conversion-attribute-based reservoir permeability evaluation method |
-
2016
- 2016-10-11 CN CN201610888949.9A patent/CN107917865B/en active Active
Patent Citations (30)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3416376A (en) * | 1966-11-30 | 1968-12-17 | Fuller Co | Surface area measurement of variable length sample of finely divided solids |
| WO1993015389A1 (en) * | 1992-01-24 | 1993-08-05 | Abb Strömberg Drives Oy | Method and apparatus for determination of refiner mechanical pulp properties |
| CN1103165A (en) * | 1993-11-20 | 1995-05-31 | 大庆石油管理局勘探开发研究院 | Automatic measuring instrument for permeability of rock core |
| US5668306A (en) * | 1995-04-28 | 1997-09-16 | Doherty; David L. | Soil analysis method including separate analyses of core sample strata |
| WO2004104560A3 (en) * | 2003-05-21 | 2005-03-24 | Baker Hughes Inc | Formation-based interpretation of nmr data for carbonate reservoirs |
| US7430931B2 (en) * | 2003-08-08 | 2008-10-07 | Konstandinos Zamfes | Microgranulometry and methods of applications |
| US20090055098A1 (en) * | 2007-08-23 | 2009-02-26 | Mese Ali I | Determination of point of sand production initiation in wellbores using residual deformation characteristics and real time monitoring of sand protection |
| CN101937108A (en) * | 2009-07-03 | 2011-01-05 | 中国石油天然气股份有限公司 | Method for determining reserves of hypotonic clastic rock oil and gas reservoir |
| CN102175832A (en) * | 2011-01-10 | 2011-09-07 | 中国石油天然气股份有限公司 | Method for determining optimal saturation calculation model of typical reservoir |
| CN102175529A (en) * | 2011-01-26 | 2011-09-07 | 徐州师范大学 | Creep permeation full-distance coupling test system for broken rock sample |
| CN102507412A (en) * | 2011-11-07 | 2012-06-20 | 中国石油集团川庆钻探工程有限公司 | Crack-matrix permeability grade difference judging method for carbonate reservoir equivalent model |
| CN104169714A (en) * | 2012-01-13 | 2014-11-26 | 领英股份有限公司 | Method of determining reservoir properties and quality with multiple energy X-ray imaging |
| CN102608015A (en) * | 2012-03-08 | 2012-07-25 | 长沙理工大学 | Rock mass anisotropy permeability coefficient in-situ test method and device thereof |
| CN103792574A (en) * | 2012-10-30 | 2014-05-14 | 中国石油化工股份有限公司 | Method for detecting frequency-variable gas in storage layer. |
| CN103163057A (en) * | 2013-03-18 | 2013-06-19 | 河海大学 | Testing device and measuring and calculating method for gas permeability of compact rock material |
| CN103257081A (en) * | 2013-04-28 | 2013-08-21 | 北京大学 | Method and device for recovering oil and gas reservoir rock mechanics underground in-situ model |
| CN103558358A (en) * | 2013-09-04 | 2014-02-05 | 中国石油天然气股份有限公司 | Method and system for detecting interlayer crack effect of intrastratal heterogeneous model |
| CN104655540A (en) * | 2013-11-19 | 2015-05-27 | 中国石油大学(北京) | Method for determining ancient porosity of compact sandstone in pool-forming period |
| CN104977196A (en) * | 2014-04-14 | 2015-10-14 | 中国石油化工股份有限公司 | Standard substance used in measurement of permeability, preparation method and application thereof |
| CN104133040A (en) * | 2014-07-31 | 2014-11-05 | 中国石油大学(北京) | Method and device for predicting favorable distribution and growth range of conventional tight sandstone gas reservoir |
| CN105372166A (en) * | 2014-08-26 | 2016-03-02 | 中国石油天然气股份有限公司 | Method and device for obtaining permeability of argillaceous sandstone |
| CN104614439A (en) * | 2015-02-03 | 2015-05-13 | 中国石油化工股份有限公司胜利油田分公司技术检测中心 | Nondestructive detection device and method based on electric-field fingerprinting method |
| CN104863560A (en) * | 2015-03-09 | 2015-08-26 | 东方宝麟科技发展(北京)有限公司 | Wide-net fracturing method for shale gas exploitation |
| CN104965979A (en) * | 2015-06-16 | 2015-10-07 | 中国石油化工股份有限公司 | Tight sandstone effective reservoir identifying method |
| CN104989360A (en) * | 2015-07-10 | 2015-10-21 | 中国石油天然气股份有限公司 | Characterization method of low-permeability reservoir dynamic fracture |
| CN105182424A (en) * | 2015-08-03 | 2015-12-23 | 中国石油天然气股份有限公司 | Method and device for quantitatively predicting reservoir porosity based on patch saturation model |
| CN105403497A (en) * | 2015-12-08 | 2016-03-16 | 中国石油天然气股份有限公司 | Core permeability evolution simulation method and system |
| CN105510207A (en) * | 2016-01-29 | 2016-04-20 | 河海大学 | Method for determining sensitivity of crack rock mass permeability in all directions to porosity |
| CN105628586A (en) * | 2016-02-19 | 2016-06-01 | 北京理工大学 | Method for determining permeability of porous medium |
| CN105954801A (en) * | 2016-06-12 | 2016-09-21 | 成都理工大学 | Frequency-conversion-attribute-based reservoir permeability evaluation method |
Non-Patent Citations (5)
| Title |
|---|
| BAZIAR S. 等: "Prediction of permeability in a tight gas reservoir by using three soft computing approaches: A comparative study", 《JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING》 * |
| 叶素娟 等: "川西坳陷叠覆型致密砂岩气区储层特征及定量预测评价", 《石油学报》 * |
| 宋宁 等: "基于流动单元分类的非均质砂岩储集层渗透率预测", 《科技导报》 * |
| 王兆峰 等: "缝洞型碳酸盐岩储集体特征及预测——以A油田P_Z段为例", 《石油与天然气地质》 * |
| 蔺景龙 等: "基于分形理论预测砂岩储层渗透率", 《东北石油大学学报》 * |
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