CN115306373B - Prediction method suitable for reservoir injuries with different clay mineral contents - Google Patents
Prediction method suitable for reservoir injuries with different clay mineral contents Download PDFInfo
- Publication number
- CN115306373B CN115306373B CN202211128995.0A CN202211128995A CN115306373B CN 115306373 B CN115306373 B CN 115306373B CN 202211128995 A CN202211128995 A CN 202211128995A CN 115306373 B CN115306373 B CN 115306373B
- Authority
- CN
- China
- Prior art keywords
- clay mineral
- core
- liquid
- reservoir
- crushed
- 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.)
- Active
Links
- 239000002734 clay mineral Substances 0.000 title claims abstract description 77
- 230000006378 damage Effects 0.000 title claims abstract description 61
- 238000000034 method Methods 0.000 title claims abstract description 30
- 239000011148 porous material Substances 0.000 claims abstract description 38
- 239000007788 liquid Substances 0.000 claims abstract description 33
- 230000008859 change Effects 0.000 claims abstract description 28
- 208000027418 Wounds and injury Diseases 0.000 claims abstract description 23
- 208000014674 injury Diseases 0.000 claims abstract description 23
- 230000035699 permeability Effects 0.000 claims abstract description 23
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 claims abstract description 16
- 238000012360 testing method Methods 0.000 claims abstract description 13
- 239000011435 rock Substances 0.000 claims abstract description 9
- 229910052757 nitrogen Inorganic materials 0.000 claims abstract description 8
- 238000001179 sorption measurement Methods 0.000 claims abstract description 8
- 238000011549 displacement method Methods 0.000 claims abstract description 7
- 238000002050 diffraction method Methods 0.000 claims abstract description 6
- 230000001419 dependent effect Effects 0.000 claims abstract description 4
- 239000012530 fluid Substances 0.000 claims description 14
- 238000005553 drilling Methods 0.000 claims description 9
- 238000002360 preparation method Methods 0.000 claims description 9
- 238000011156 evaluation Methods 0.000 claims description 3
- 238000002474 experimental method Methods 0.000 description 6
- 239000007789 gas Substances 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000006073 displacement reaction Methods 0.000 description 2
- 230000005484 gravity Effects 0.000 description 2
- 238000002347 injection Methods 0.000 description 2
- 239000007924 injection Substances 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 238000002441 X-ray diffraction Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000004927 clay Substances 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000010419 fine particle Substances 0.000 description 1
- 230000009545 invasion Effects 0.000 description 1
- 238000012417 linear regression Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 239000004058 oil shale Substances 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 239000002244 precipitate Substances 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
Classifications
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B47/00—Survey of boreholes or wells
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B25/00—Apparatus for obtaining or removing undisturbed cores, e.g. core barrels or core extractors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Mining & Mineral Resources (AREA)
- Theoretical Computer Science (AREA)
- Geology (AREA)
- Computational Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Data Mining & Analysis (AREA)
- Pure & Applied Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Environmental & Geological Engineering (AREA)
- Algebra (AREA)
- Fluid Mechanics (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Geochemistry & Mineralogy (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Computing Systems (AREA)
- Operations Research (AREA)
- Geophysics (AREA)
- Investigation Of Foundation Soil And Reinforcement Of Foundation Soil By Compacting Or Drainage (AREA)
Abstract
The invention relates to a prediction method suitable for reservoir injuries with different clay mineral contents, which comprises the steps of taking a plunger-like core and a crushed-like core of the same sample: the method comprises the steps of testing a permeability change value of a well entering liquid before and after the well entering liquid damages the plunger-like core by using a displacement method to obtain a permeability damage rate K; testing the content of clay minerals in the crushed sample core by using an X-diffraction method, and testing the change values of the total pore volume V, the specific surface area S and the pore radius L of the crushed sample core before and after the crushed sample core is damaged by the well liquid by using a nitrogen adsorption method, so as to calculate the change rates of three damage target values, namely the total pore volume V, the specific surface area S and the pore radius L; and distinguishing the reservoir according to the clay mineral content of the reservoir, establishing a prediction model with the change rate of three injury target values before and after the damage to the crushed rock core by the well entering liquid as independent variables and the permeability injury rate K as dependent variables, and further evaluating the injury degree of the reservoir. The invention has better popularization and application in the field of reservoir protection.
Description
Technical Field
The invention belongs to the field of reservoir protection of oil and gas reservoirs, and particularly relates to a prediction method suitable for reservoir injuries with different clay mineral contents.
Background
The content, the type, the distribution, the occurrence and the like of the clay minerals have close relations to the damage of the stratum. Because clay minerals have fine particles, large specific surface area and special structural composition, they are extremely sensitive to invasion of external working fluids such as drilling fluids, injection water, well fluids, and the like. When the external fluid contacts, clay minerals often expand, particles migrate, form a certain precipitate and the like to block the oil and gas migration channels of the reservoir, so that the seepage capability of the reservoir is reduced, and the oil and gas layer is damaged. At present, the drilling, exploitation and development of oil and gas reservoirs cannot avoid the injection of water-based working fluid, so that the reservoirs are damaged to different degrees, and the exploitation efficiency of the oil and gas fields is reduced. Therefore, the damage evaluation of the well entering liquid to the reservoirs with different clay mineral contents is beneficial to evaluating the compatibility of various well entering liquids, optimizing the working liquid formula and providing a powerful reference for the later-stage reconstruction and protection of the reservoirs.
At present, a displacement method, a pulse permeability method and the like are mainly adopted in reservoir damage experiments. The two methods have strict requirements on sample quantity and pretreatment, and rock samples are required to be drilled and cut into round columns with the diameter of 2.5cm and the length of 5-10 cm, so that the drilling and cutting rate of the rock with low argillaceous content is higher, but the drilling and cutting rate of the rock with high argillaceous content, especially oil shale, is crisp in lithology, and has low page development, and the drilling and cutting rate often cannot meet the experimental requirements. Second, for very tight rock samples, the displacement method is not applicable.
The method omits a sample drilling and cutting link, reduces the use amount of samples, improves the experimental efficiency, and has better popularization and application in the field of reservoir protection.
Disclosure of Invention
Aiming at the problems, the invention provides a prediction method which is simple, low in sample demand and easy to process, a nitrogen adsorption experiment is adopted to test the change values of the total pore volume V, the specific surface area S and the pore radius L of the crushed sample core before and after the damage of the well entering liquid, the change rate is calculated, and a prediction model is built through correlation analysis with the permeability damage rate K obtained by the plunger sample core through a displacement method, so that the aim of evaluating the damage degree of a reservoir is achieved.
The technical scheme of the invention is as follows:
a prediction method suitable for reservoir injuries with different clay mineral contents is provided, and the principle is as follows:
reading GR value from logging curve, taking plunger-like core and broken-like core of the same sample on site;
The method comprises the steps of testing the permeability change value of a well entering liquid before and after the core is damaged by a plunger-type core by using a displacement method, and obtaining permeability damage rate K;
Testing the content of clay minerals in the crushed sample core by using an X-diffraction method, testing the change values of the total pore volume V, the specific surface area S and the pore radius L of the crushed sample core before and after the crushed sample core is damaged by the well liquid by using a nitrogen adsorption method, and further calculating the change rate;
analyzing the correlation between the clay mineral content and the permeability injury rate K, and observing the change rule;
According to different injuries brought by the clay mineral content to the broken sample core, the clay mineral content is divided into three sections, namely the clay mineral content is less than 25%, the clay mineral content is less than 25% < 50%, and the clay mineral content is more than 50%; taking the clay mineral content as an independent variable x, taking the permeability injury rate K as an objective function y, carrying out unitary regression one by one, and establishing a unitary function relation group:
wherein: y s、yh and y n are objective functions of permeability injury rate K corresponding to clay mineral content < 25%, clay mineral content < 50% and clay mineral content > 50%, respectively; x si、xhi and x ni are the clay mineral contents of i samples when the clay mineral content is less than 25%, 25% < the clay mineral content is less than 50%, and the clay mineral content is more than 50%, respectively;
according to the experimental result of the X-ray diffraction method, the value of i is 1 to n, the regression coefficient a s=0.9972、ah=1.0291、an = 0.9159 is determined, and a unitary linear regression equation set is established:
Correlation: r s 2=0.34;rh 2=0.52;rn 2 =0.71;
Wherein: x s、xh and x n are the clay mineral content in units of less than 25% of the clay mineral content, less than 50% of the clay mineral content and more than 50% of the clay mineral content; y s、yh and y n are objective functions of permeability injury rate K corresponding to clay mineral content < 25%, clay mineral content < 50% and clay mineral content > 50%, respectively;
from the above formula, there is a certain linear relation between the clay mineral content and the permeability injury rate K, and the correlation becomes better as the clay mineral content increases. That is, the larger the clay mineral content, the greater the specific gravity of the influence of the clay mineral content on the permeability injury rate.
Based on the relation, in order to more accurately predict the damage degree of the reservoir, the invention establishes a prediction model for reservoirs with different clay mineral contents in a partitioning way; when a prediction model is built for a reservoir with the clay mineral content less than 50%, the independent variable in the prediction model does not consider the factor of the clay mineral content because the dominant position of the specific gravity of the clay mineral content in the damage factors of the reservoir is not obvious; for shale reservoirs with clay mineral content greater than 50%, the clay mineral content is included in the prediction model argument factor when the prediction model is established because the clay mineral content occupies a large proportion.
The change rates of the three damage target values are calculated through analysis of data of the total pore volume V, the specific surface area S and the pore radius L, which are tested by a nitrogen adsorption method, before and after the damage of the well entering liquid; and establishing a prediction model in a partition way, and solving the problem of rapid prediction of the injury degree of different lithology reservoirs.
Taking the change rate of the total pore volume V, the specific surface area S and the pore radius L before and after the damage of the well fluid as independent variables, taking the permeability damage rate K measured by a displacement experiment on a plunger-like core as a target dependent variable, analyzing the relevance of the damage rates V%, S%, L% and the permeability damage rate K% of three damage targets of the total pore volume V, the specific surface area S and the pore radius L, and constructing a multi-factor multi-element function group:
Regression is carried out on the constructed multi-element function groups Y si,Yhi and Y ni according to three experimental data tested by a nitrogen adsorption method, regression coefficients a1, a2, a3 and a4 of each group and correlations R S、Rh and R n are determined, and a prediction model group is established;
the regression coefficients are brought into a multi-element function set, and the established prediction model set is as follows:
Wherein: v S、Vh、Vn is the total pore volume change rate when the clay mineral content is less than 25%, 25% < 50% and the clay mineral content is more than 50%, and the unit is dimensionless;
S S、Sh、Sn is the specific surface area change rate when the clay mineral content is less than 25%, 25% < 50% and > 50%, respectively, and the unit is dimensionless;
L S、Lh、Ln is the rate of change of pore radius when the clay mineral content is less than 25%, 25% < 50% and > 50% respectively, and the unit is dimensionless;
N n is the clay mineral content value of the crushed rock core measured by an X-diffraction method when the clay mineral content is more than 50 percent;
Y S、Yh、Yn is the predicted value of permeability injury rate when the clay mineral content is less than 25%, 25% < the clay mineral content is less than 50% and the clay mineral content is more than 50%, and the unit is dimensionless.
Preferably, the method for calculating the rate of change of the total pore volume V, the specific surface area S and the pore radius L is as follows:
Wherein: v Liquid and its preparation method is the total pore volume measured after the crushed sample core is treated by the well fluid, and the unit ml; v Dry is the total pore volume of the dry sample measured before the crushed sample core is treated, and the unit ml;
S Liquid and its preparation method is the specific surface area measured after the crushed sample core is treated by the well fluid, and the unit is that; s Dry is the specific surface area of the dry sample measured before the crushed sample core is not treated, and the unit is that;
L Liquid and its preparation method is the pore radius measured after the crushed sample core is treated by the well fluid, and the unit is r; l Dry is the pore radius of the dry sample measured before the crushed sample core is treated, and the unit is r.
Preferably, the well fluid comprises drilling fluid and well cementing fluid.
Preferably, the clay mineral contents are all absolute clay mineral contents.
The invention has the technical effects that:
The invention omits a sample drilling and cutting link, reduces the use amount of samples, improves the experimental efficiency, and has better popularization and application in the field of reservoir protection.
Detailed Description
Example 1
A prediction method suitable for reservoir injuries with different clay mineral contents comprises the following steps:
step 1: taking a plunger sample core and a broken sample core of the same sample;
Step2: the method comprises the steps of testing a permeability change value of a well entering liquid before and after the well entering liquid damages the plunger-like core by using a displacement method to obtain a permeability damage rate K;
Step 3: testing the content of clay minerals in the crushed sample core by using an X-diffraction method, and testing the change values of the total pore volume V, the specific surface area S and the pore radius L of the crushed sample core before and after the crushed sample core is damaged by the well liquid by using a nitrogen adsorption method, so as to calculate the change rates of three damage target values, namely the total pore volume V, the specific surface area S and the pore radius L;
Step 4: and distinguishing the reservoir according to the clay mineral content of the reservoir, establishing a prediction model with the change rate of three injury target values before and after the damage to the crushed rock core by the well entering liquid as independent variables and the permeability injury rate K as dependent variables, and further evaluating the injury degree of the reservoir.
Example 2
On the basis of embodiment 1, the prediction model is:
。
specific experimental example
A prediction method suitable for reservoir injuries with different clay mineral contents comprises the following steps:
Firstly, the clay content of 12 experimental sections is read from a logging curve, an X-diffraction experiment, a core well entering liquid damage displacement experiment and a nitrogen adsorption experiment are respectively carried out on site sampling, 12 groups of experimental data of each section are respectively obtained, and error analysis is carried out on the actual measurement value and the predicted value of the damage rate of the three sections. The results are shown in Table 1.
The average value of the root mean square errors obtained by the prediction model with the clay mineral content less than 25% is 1.63, the average value of the root mean square errors obtained by the prediction model with the clay mineral content less than 25% is 1.27, the average value of the root mean square errors obtained by the prediction model with the clay mineral content more than 50% is 0.95, the average root mean square errors are all in the allowable range, and the engineering error range of reservoir damage evaluation is met.
Claims (4)
1. A prediction method suitable for reservoir injuries with different clay mineral contents is characterized in that: the method comprises the following steps:
step 1: taking a plunger sample core and a broken sample core of the same sample;
Step2: the method comprises the steps of testing a permeability change value of a well entering liquid before and after the well entering liquid damages the plunger-like core by using a displacement method to obtain a permeability damage rate K;
Step 3: testing the content of clay minerals in the crushed sample core by using an X-diffraction method, and testing the change values of the total pore volume V, the specific surface area S and the pore radius L of the crushed sample core before and after the crushed sample core is damaged by the well liquid by using a nitrogen adsorption method, so as to calculate the change rates of three damage target values, namely the total pore volume V, the specific surface area S and the pore radius L;
step 4: distinguishing the reservoir according to the clay mineral content of the reservoir, establishing a prediction model with the change rate of three damage target values before and after damage to the crushed rock core by the well entering liquid as independent variables and the permeability damage rate K as dependent variables, and further realizing evaluation of the damage degree of the reservoir;
wherein, the prediction model is as follows:
wherein: v S、Vh、Vn is the total pore volume change rate when the clay mineral content is less than 25%, 25% < 50% and > 50%;
S S、Sh、Sn is the specific surface area change rate when the clay mineral content is less than 25%, 25% < 50% and > 50%;
L S、Lh、Ln is the rate of change of pore radius when the clay mineral content is less than 25%, 25% < 50% and > 50% respectively;
N n is the clay mineral content value of the crushed rock core measured by an X-diffraction method when the clay mineral content is more than 50%;
Y S、Yh、Yn is the predicted value of the permeability injury rate when the clay mineral content is less than 25 percent, 25 percent is less than 50 percent and the clay mineral content is more than 50 percent respectively.
2. The method for predicting damage to reservoirs having differing clay mineral contents as recited in claim 1 wherein: the method for calculating the change rate of the total pore volume V, the specific surface area S and the pore radius L comprises the following steps:
V%=|V Liquid and its preparation method －V Dry |/ V Dry ×100%
S%=|S Liquid and its preparation method －S Dry |/ S Dry ×100%
L%=| L Liquid and its preparation method －L Dry |/L Dry ×100%
Wherein: v Liquid and its preparation method is the total pore volume, ml, measured after the crushed core is treated with the well fluid;
V Dry is the total pore volume of the dry sample measured before the crushed sample core is treated, and ml;
S Liquid and its preparation method is the specific surface area which is measured after the crushed sample core is treated by the well liquid,%;
S Dry is the specific surface area of the dry sample measured before the crushed sample core is not treated,%;
L Liquid and its preparation method is the pore radius measured after the crushed sample core is treated by the well fluid;
L Dry is the pore radius of the dry sample measured before the crushed sample core is treated.
3. A method of predicting damage to reservoirs having differing clay mineral contents as recited in claim 2 wherein: the well-entering liquid comprises drilling liquid and well cementation liquid.
4. A method of predicting damage to reservoirs having differing clay mineral contents as recited in claim 3 wherein: the clay mineral content is the absolute content of the clay mineral.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211128995.0A CN115306373B (en) | 2022-09-16 | 2022-09-16 | Prediction method suitable for reservoir injuries with different clay mineral contents |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211128995.0A CN115306373B (en) | 2022-09-16 | 2022-09-16 | Prediction method suitable for reservoir injuries with different clay mineral contents |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115306373A CN115306373A (en) | 2022-11-08 |
| CN115306373B true CN115306373B (en) | 2024-09-10 |
Family
ID=83866360
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211128995.0A Active CN115306373B (en) | 2022-09-16 | 2022-09-16 | Prediction method suitable for reservoir injuries with different clay mineral contents |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115306373B (en) |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106093299A (en) * | 2016-06-02 | 2016-11-09 | 西南石油大学 | A kind of tight gas reservoir drilling fluid damage evaluation experimental technique |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5310002A (en) * | 1992-04-17 | 1994-05-10 | Halliburton Company | Gas well treatment compositions and methods |
| CN104650823B (en) * | 2015-02-11 | 2016-02-03 | 中国石油大学(北京) | Height ooze extra-high ooze reservoir protective material composition and drilling fluid and application thereof |
| CN109488290A (en) * | 2017-09-12 | 2019-03-19 | 中国石油天然气股份有限公司 | Evaluation method and device for damage degree of drilling fluid to reservoir |
| CN111967162A (en) * | 2020-08-20 | 2020-11-20 | 西南石油大学 | Compact sandstone gas reservoir drilling fluid reservoir damage evaluation method |
| CN112966365B (en) * | 2021-02-04 | 2023-09-12 | 中海石油(中国)有限公司 | Method for evaluating reverse condensation injury of ultralow condensation gas reservoir |
| CN113803057A (en) * | 2021-09-04 | 2021-12-17 | 中海石油(中国)有限公司湛江分公司 | Method for determining invasion surface coefficient of horizontal well drilling fluid of sandstone reservoir |
-
2022
- 2022-09-16 CN CN202211128995.0A patent/CN115306373B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106093299A (en) * | 2016-06-02 | 2016-11-09 | 西南石油大学 | A kind of tight gas reservoir drilling fluid damage evaluation experimental technique |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115306373A (en) | 2022-11-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Izadi et al. | A new approach in permeability and hydraulic-flow-unit determination | |
| Guo et al. | Experimental investigation on damage mechanism of guar gum fracturing fluid to low-permeability reservoir based on nuclear magnetic resonance | |
| CN109991123B (en) | Geochemical evaluation method for mobility of shale oil resources | |
| Soleymanzadeh et al. | A new technique for electrical rock typing and estimation of cementation factor in carbonate rocks | |
| Reyes et al. | Empirical correlation of effective stress dependent shale rock properties | |
| CN103196807A (en) | Analysis method for sandstone diagenesis process and pore evolution | |
| Amann‐Hildenbrand et al. | Effective gas permeability of Tight Gas Sandstones as a function of capillary pressure–a non‐steady‐state approach | |
| Heilweil et al. | Gas‐partitioning tracer test to quantify trapped gas during recharge | |
| Amann-Hildenbrand et al. | Laboratory testing procedure for CO2 capillary entry pressures on caprocks | |
| Yang et al. | Permeability evolution characteristics of intact and fractured shale specimens | |
| Nelson | An approach to evaluating fractured reservoirs | |
| McPhee et al. | Relative permeability | |
| CN115306373B (en) | Prediction method suitable for reservoir injuries with different clay mineral contents | |
| Noah et al. | Integration of well logging analysis with petrophysical laboratory measurements for Nukhul Formation at Lagia-8 well, Sinai, Egypt | |
| Wei et al. | Nuclear magnetic resonance study on the evolution of oil water distribution in multistage pore networks of shale oil reservoirs | |
| CN114441402B (en) | Method for evaluating permeability of tight sandstone | |
| Haldorsen et al. | An evaluation of the Prudhoe bay gravity drainage mechanism by complementary techniques | |
| 莫非 et al. | A method to determine permeability jail boundaries of tight sandstone cores from the Western Sichuan Basin | |
| CN112012727A (en) | Method for obtaining gas phase effective permeability and prediction method of reservoir productivity | |
| Li et al. | A novel approach to the quantitative evaluation of the mineral composition, porosity, and kerogen content of shale using conventional logs: A case study of the Damintun Sag in the Bohai Bay Basin, China | |
| CN113449408A (en) | Stratum pressure calculation method and device for shale gas well | |
| Liu et al. | Micropore Throat Structure and Movable Fluid Characteristics of Chang 63 Tight Sandstone in Baibao Area of Ordos Basin | |
| CN110672487B (en) | Method for predicting absolute permeability of compact rock | |
| Chen et al. | A novel method for calculating the dynamic reserves of tight gas wells considering stress sensitivity is under consideration | |
| Zhang et al. | The Novel Dynamic Monitoring Technology and Analysis Methods for Deep Carbonate Reservoirs |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |