CN115598736B - Method for determining desserts of shale and compact oil-gas horizontal well based on rock debris - Google Patents
Method for determining desserts of shale and compact oil-gas horizontal well based on rock debris Download PDFInfo
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- 239000011435 rock Substances 0.000 title claims abstract description 46
- 238000000034 method Methods 0.000 title claims abstract description 27
- 235000011850 desserts Nutrition 0.000 title claims abstract description 5
- 235000021185 dessert Nutrition 0.000 claims abstract description 61
- 229910052500 inorganic mineral Inorganic materials 0.000 claims abstract description 60
- 239000011707 mineral Substances 0.000 claims abstract description 60
- 238000005553 drilling Methods 0.000 claims abstract description 17
- 239000011347 resin Substances 0.000 claims abstract description 17
- 229920005989 resin Polymers 0.000 claims abstract description 17
- 238000005070 sampling Methods 0.000 claims abstract description 14
- 235000009508 confectionery Nutrition 0.000 claims abstract description 8
- 238000004519 manufacturing process Methods 0.000 claims abstract description 4
- DLHONNLASJQAHX-UHFFFAOYSA-N aluminum;potassium;oxygen(2-);silicon(4+) Chemical compound [O-2].[O-2].[O-2].[O-2].[O-2].[O-2].[O-2].[O-2].[Al+3].[Si+4].[Si+4].[Si+4].[K+] DLHONNLASJQAHX-UHFFFAOYSA-N 0.000 claims description 9
- 229910000514 dolomite Inorganic materials 0.000 claims description 9
- 239000010459 dolomite Substances 0.000 claims description 9
- 229910001748 carbonate mineral Inorganic materials 0.000 claims description 8
- XQCFHQBGMWUEMY-ZPUQHVIOSA-N Nitrovin Chemical compound C=1C=C([N+]([O-])=O)OC=1\C=C\C(=NNC(=N)N)\C=C\C1=CC=C([N+]([O-])=O)O1 XQCFHQBGMWUEMY-ZPUQHVIOSA-N 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 6
- 229910052655 plagioclase feldspar Inorganic materials 0.000 claims description 6
- QSHDDOUJBYECFT-UHFFFAOYSA-N mercury Chemical compound [Hg] QSHDDOUJBYECFT-UHFFFAOYSA-N 0.000 claims description 5
- 229910052753 mercury Inorganic materials 0.000 claims description 5
- 239000011148 porous material Substances 0.000 claims description 5
- 238000011010 flushing procedure Methods 0.000 claims description 4
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Abstract
The invention belongs to the technical field of shale and compact oil-gas exploration and development, and particularly relates to a method for determining desserts based on rock debris for a shale and compact oil-gas horizontal well, which comprises the following steps: selecting at least one vertical well around the vertical well according to the target well position, and obtaining a rock core containing a dessert well section in the vertical well; preparing a resin sample from the rock core; scanning the prepared resin samples in batches to obtain various mineral data of the vertical well dessert well section; establishing a profile of a straight well section, and determining a discrimination standard of a sweet spot well section and a non-sweet spot well section; sampling the rock debris at the target well position, and manufacturing a resin sample; scanning the resin sample to obtain various mineral data of the target well rock debris; a sweet spot location of the target well is determined. The drilling rate of the shale and compact oil-gas horizontal well reaches 100%, the drilling construction period is greatly shortened, and the exploration and development cost is reduced; providing a basis for the subsequent horizontal well subsection clustering and providing a construction basis for the later fracturing.
Description
Technical Field
The invention belongs to the technical field of shale and compact oil-gas exploration and development, and particularly relates to a method for determining desserts based on rock debris in a shale and compact oil-gas horizontal well.
Background
With the continuous decrease of the yield of conventional oil gas at home and abroad, the exploration concept is gradually changed and innovated, the unconventional oil gas becomes the resource succession field and makes a series of breakthroughs, and the rapid development of the exploration and development of shale and compact oil gas also makes the petroleum resources in the shale and compact layer series to be widely concerned. At present, newly developed oil fields have the characteristics of low reserves and abundance and low single-well yield, the benefit development is more difficult, and new fields, new types and new methods need to be searched.
At present, the reservoir dessert fine evaluation of a conventional well mainly depends on data such as a rock core and a logging model, the rock core experiment parameters provide first-hand underground data, key parameters are provided for a logging interpretation model, the interpretation accuracy of the logging model is improved, and a logging curve has advantages in continuity. However, in the process of determining the sweet spot in the development of shale and compact oil and gas reservoirs, the above means face the following problems:
1. reservoir coring is used as first-hand data, laboratory research is conducted on the reservoir coring, and fine evaluation on the reservoir coring is important, but for shale and compact oil and gas horizontal wells, a plurality of restriction conditions limit large-scale coring testing and analysis. Firstly, the experimental coring process based on the rock core is complex and high in cost, and meanwhile, coring drilling has influence on the stability of the well wall. Secondly, the requirement on the quality of the rock core is high, repeated experiments cannot be carried out, and the requirements on depth sections of laboratory analysis are met due to the influence of the number of the rock cores, so that various characteristic parameters of the whole reservoir section cannot be accurately evaluated. Finally, compared with a conventional core fluidity experiment, the shale core testing period is long, wherein the time consumption of the reservoir core experiment is as long as several times, the experiment difficulty is high, the conventional method for evaluating the pore seepage and pore throat structural parameters is difficult to develop in time, the rapid evaluation of the drilled reservoir is not facilitated, and the accuracy of the subsequent development and design work is influenced.
2. The conventional logging has a plurality of data in the exploration and development stage of an oil field, generally comprises density logging, neutron logging, acoustic logging, resistivity logging, natural gamma logging, borehole diameter logging, natural potential logging and the like, contains information such as lithology, physical property, conductivity, oil content and the like of a reservoir, and has irreplaceable effects in reservoir identification and dessert evaluation; compared with conventional well logging, the special well logging adopts a new method and theory, has stronger pertinence, higher resolution and better practicability, and comprises array acoustic wave imaging well logging, cross dipole transverse wave well logging, micro-resistivity scanning imaging well logging, nuclear magnetic resonance well logging, natural gamma energy spectrum well logging, lithology scanning well logging and the like. And shale reservoir development is mostly carried out in a horizontal well fracturing mode, and compared with the conventional oil well, the shale and compact oil-gas horizontal well has obvious difference. Shale, the tight oil gas horizontal well are influenced by problems such as difficult downhole of a logging tool and tool eccentricity caused by gravity, and conventional logging means have certain limitations, so that accurate evaluation of shale, tight oil gas reservoir pore structure parameters and rock mechanical parameters is directly influenced, and the accuracy of reservoir dessert evaluation is further reduced.
Natural gamma and resistivity curves measured in real time by LWD (logging while drilling) and MWD (measurement while drilling) in a conventional horizontal well can determine landing points for field geosteering personnel, judge the position of a hydrocarbon reservoir and predict the upper and lower interfaces of the hydrocarbon reservoir to provide real-time logging curves; well deviation, azimuth and tool face value can provide basis for directional well engineers to adjust drilling parameters, ensure target hitting and make the track meet geological requirements.
However, in shale and compact reservoirs, because of the characteristics of low porosity, low permeability and the like, in order to increase the recovery efficiency, the current development basically takes a horizontal well as a main part, so the dessert drilling rate of the horizontal well reservoir directly influences the development degree and the effect. At present, LWD/MWD logging while drilling can only provide some conventional logging curves including natural gamma, resistivity and the like on a drilling site, but due to the fact that lithology and physical properties of shale and compact oil and gas blocks are complex, the conventional logging curves have no obvious change characteristics, cannot visually and timely reflect rock formation information, and have no quantitative parameters to guide site track adjustment, which is the difficulty encountered in logging while drilling on shale and compact oil and gas horizontal wells.
In order to effectively solve the problems and ensure the accuracy of subsequent exploration and development of shale and compact oil gas, a new method is needed to solve the problems.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method for determining a sweet spot of a shale and compact oil-gas horizontal well based on rock debris.
In order to realize the purpose, the technical scheme of the invention is as follows:
a method of determining sweet spots based on cuttings for shale, tight oil and gas horizontal wells, comprising:
s1, selecting at least one vertical well around according to a target well position, and obtaining a rock core containing a dessert well section in the vertical well; preparing a resin sample from the rock core;
s2, scanning the resin samples prepared in the step S1 in batch to obtain various mineral data of the vertical well dessert well section, wherein the mineral data comprises mineral types and contents (mass percentage);
s3, determining the discrimination standard of the dessert layer and the non-dessert layer according to known characteristic parameters of the vertical well dessert well section, and establishing a typical section for dividing the dessert;
s4, sampling rock debris at the target well position, and manufacturing a resin sample;
s5, scanning the resin sample in the step S4 to obtain various mineral data of the target well rock debris, wherein the mineral data comprise mineral types and contents;
and S6, comparing the mineral data obtained in the step S5 with the judgment standard in the step S3, and determining the dessert layer of the target well.
Further, the criteria for discriminating between sweet-spot and non-sweet-spot layers are:
xwhich is an indication of the degree of porosity,ywhich is an index of brittleness, is shown,
represents the individual mineral content of the non-carbonate mineral, in mass percent, z represents the individual mineral content belonging to the carbonate mineral, in mass percent,
、
、
is a constant number of times, and is,
is a constant number of times, wherein,nthe value is 2.
Further, the specific method of step S1 is: selecting at least one vertical well in a shale oil research area according to a target well position, obtaining a rock core sample containing a dessert well section in the vertical well section, and cutting and pouring a plurality of resin samples with well number depth and well depth direction from shallow to deep direction.
Further, in step S2, scanning is performed using a MaipSCAN automatic mineral identification system.
Further, the characteristic parameters in the step S3 include characteristic mineral content, porosity and brittleness index.
Further, the specific method for establishing the straight well section profile in the step S3 is as follows: and (3) comparing the logging data of the straight well section with each mineral data obtained in the step (S2), comparing the trend conformity of a flushing resistivity RXO curve, a natural gamma GR curve and a density DEN curve in the logging data with a mineral data curve, determining characteristic minerals divided by the rock stratum according to the conformity, and dividing the core well section of the straight well into 12 sections along the depth direction according to the relative content of the minerals in the rock stratum.
Furthermore, determining the identification characteristics of the target layer dessert well section according to the mineral parameters, physical parameters and rock mechanical parameters of the dessert well section of the vertical well; firstly, analyzing and counting the porosity and the brittleness index, then analyzing and counting the characteristic minerals, and finally determining the identification characteristics of the dessert well section.
Further, the concrete method for sampling the rock debris in the step S4 is as follows: and determining a target entering point, drilling to the target entering point by using a drill bit, and taking rock debris samples according to field logging sampling intervals at the deflecting section part of the target entering point.
Further, step S6 includes determining that the horizontal segment of the target well is in the target zone according to the mineral data obtained in step S5 and the characteristic parameters in step S3.
Compared with the prior art, the invention has the following beneficial effects:
according to the method, the well section profile of the straight well section and the judgment standard of the dessert well section are determined through the data of the straight well section, the mineral data of the target well position are obtained, the target well can be guided to accurately reach a target layer by means of the well section profile of the straight well section, and the dessert well section is accurately positioned; the drilling rate of the shale and compact oil-gas horizontal well reaches 100%, the single horizontal well saves at least one logging time (120 hours), the drilling construction period is greatly shortened, and the exploration and development cost is reduced; providing basis for the subsequent horizontal well subsection clustering and providing construction basis for the later fracturing.
Compared with the exploration and development of shale and compact oil and gas wells in the prior art, the core sampling cost is high, the horizontal well is difficult to sample, the core sampling is avoided, a rock debris sampling mode is adopted, the sampling is simple and easy to obtain, and the cost is extremely low.
Drawings
FIG. 1 is a graph comparing a log data curve and a mineral data curve of a straight well section in an example.
FIG. 2 is a chart of a small interval of a vertical core interval.
Fig. 3 is a diagram of the subdivision of a horizontal well.
Fig. 4 is a sectional view of a horizontal well destination.
Figure 5 is a graph of data for water saturation (Sw) and oil saturation (So) in the high quality dessert layer for the vertical well of the example.
Detailed Description
The technical solutions of the present invention will be described in detail with reference to the accompanying drawings, and it is obvious that the described embodiments are not all embodiments of the present invention, and all other embodiments obtained by those skilled in the art without any inventive work belong to the protection scope of the present invention.
The scanning system adopted in the embodiment is a MaipSCAN automatic mineral identification system, and comprises a Beijing Boyuan micro-nano technology small ion radiation meter ETD-800C, a Zeiss EVO10 electron microscope, a Bruker electric refrigeration energy spectrometer XFlash6|60 and Chicosupposition institute of physics analysis software.
Firstly, taking a core sample of a straight well section in a shale oil research area, wherein the core sample is 30m long and comprises a dessert well section; according to the shallow-to-deep direction, 404 resin samples with the well number depth and the well depth direction are cut and poured, and the specifications of the resin samples are as follows: the length is 100mm, the width is 25mm, and the thickness is 14mm.
And (3) performing electron microscope scanning and energy spectrum quantitative analysis on the prepared core sample by using a MaipSCAN automatic mineral identification system to obtain data such as mineral parameters, physical parameters, rock mechanical parameters and the like of the sample. According to the obtained sample mineral data, the accuracy of the mineral data is verified by referring to logging (stratum layering) data of a vertical well (flushing zone resistivity RXO, natural gamma GR and density DEN). Then, by comparing logging data of a straight well section with logging data of minerals, as shown in fig. 1, the trend conformity of a flushing resistivity RXO curve and a dolomite relative content curve in the logging data is highest, the trend conformity of a natural gamma GR curve and a potassium feldspar relative content curve is high, the trend conformity of a logging density DEN curve and an inclined feldspar relative content curve is high, and the dolomite, the potassium feldspar and the inclined feldspar are determined to be used as characteristic minerals for rock stratum division. In order to distinguish well sections with different mineral contents, the core well section is divided into 12 small layers according to the relative content change of the characteristic minerals in lithology naming, and the method is shown in figure 2.
Calculating the oil storage content characterization value in the reservoir according to the following formula
The value of the sum of the values,
xwhich is an expression of the degree of porosity,ywhich is indicative of the index of brittleness,
represents the single mineral content of the non-carbonate mineral, in mass percent, z represents the single mineral content belonging to the carbonate mineral, in mass percent,
、
、
is a constant number of times, and is,
is a constant number of times, wherein,nthe value is 2.
In this embodiment, the constant coefficient is calculated by:
computing
: by combining the laboratory data analysis data of the high-quality dessert layer core (as shown in fig. 5), when the porosity exceeds 12%, the oil saturation is obviously increased, and the value of the porosity value is determined to be more than or equal to 12%; meanwhile, the output has an obvious relation with the permeability of a reservoir, and the average maximum mercury inlet saturation of the porosity value of more than or equal to 12 percent is 70 percent by combining a laboratory core mercury intrusion test, wherein the average maximum mercury inlet saturation represents that 30 percent of pores are not communicated. Therefore get it
Calculating out
: the actual oil production is related to subsequent exploration and development, mainly refers to fracturing and modifying a reservoir, and a modification result is related to rock brittleness.
And = h, = interbed minimum brittleness index/pay zone average brittleness index, wherein interbed minimum brittleness index means the minimum brittleness index of the interbed region of the vertical well, and pay zone average brittleness index means the average brittleness index of the pay zone of the vertical well, all obtained by the prior art.
wherein,xwhich is an expression of the degree of porosity,ywhich is indicative of the index of brittleness,
the content of the potassium feldspar is shown,
the content of plagioclase is shown,
representing the dolomite content. The discrimination criteria according to the dessert layer and the non-dessert layer are:
less than or equal to 50, is a non-dessert layer; 50 < (r) >, of
Less than or equal to 60, is a type III dessert layer (dessert layer with development value between the general dessert layer and the interlayer), and is less than 60
Less than or equal to 80, which is a type II dessert layer (a common dessert layer); 100 is not less than
More than 80, is a type I dessert layer (high-quality dessert layer).
According to the well section of the dessert known for that area (B in figure 2) 2 Well section), mineral property parameters, physical property parameters and rock mechanical parameters, as shown in table 1, mineral property characteristics are summarized, identification characteristics of a dessert well section of a target layer in the area are screened out, the accuracy of the formula is verified through data in table 1, layers 4, 6 and 8 in table 1 are all high-quality dessert layers, and parameters such as porosity, brittleness index and mineral content of each group are substituted into the high-quality dessert layers
In the calculation formula (c), obtained
Values between 80 and 100, i.e. representing
The accuracy of the calculation formula is high.
TABLE 1 vertical well dessert characteristic data sheet
After the judgment standard of the dessert well section is determined, monitoring the target well, and in order to accurately enter a target layer of the target well, drilling a drill bit to a deflecting section part of a target point, taking rock debris samples according to field logging sampling intervals, generally taking a packet of rock debris every 2m, sampling the rock debris to obtain resin rock debris samples, scanning by adopting a MaipSCAN automatic mineral identification system, and drawing detection data of a horizontal well into a horizontal well data graph in real time. Comparing the real-time horizontal well data map with the vertical well data map, finding that a well section with high content of potassium feldspar and high content of dolomite appears at a 3868-3872 m position of the deflecting section in the horizontal well while drilling real-time scanning, wherein the mineral characteristics are consistent with 3684.614-3684.645 m of the vertical well, such as the well section circled in the figure 3, and gradually verifying that the horizontal well accurately enters a target layer through characteristic minerals in the subsequent tracking and scanning process. And after entering the horizontal section, sampling interval is changed to every 4-8 m, a packet of rock debris is taken, and the horizontal well data and the vertical well data are compared and monitored in real time to judge that the horizontal well section accurately drills in a target layer. While a horizontal well is drilled, the scanning well section of the horizontal well is divided section by section according to the principle of dividing the small layer of the vertical well, and the horizontal well is divided into 8 small layers as shown in figure 3.
Then applying the section of the regional dessert well section established by the vertical well section to a horizontal well target layer, referring to the fluctuation trend of the types and the contents of target layer characteristic minerals (dolomite, potassium feldspar and plagioclase feldspar) measured by a MaipSCAN automatic mineral identification system, dividing the horizontal sections into eleven groups according to the changes of the porosity and the brittleness index content, and determining the horizontal well dessert well section as shown in figure 4; and determining a dessert well section dividing suggestion table of the target layer of the horizontal well, as shown in the table 2, wherein the interlayer is the non-dessert layer.
TABLE 2 horizontal well destination layer division suggestion table
Under the guidance of the method, the drilling rate of the target layer of the horizontal section of the horizontal well is 100%, so that at least one time of logging time is saved, a basis is provided for the subsequent horizontal well subsection clustering, and a construction suggestion is provided for the later stage fracturing.
Although the present invention has been described in detail with reference to examples, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the scope of the present invention.
Claims (7)
1. A method for determining desserts of a shale tight oil and gas horizontal well based on rock debris is characterized by comprising the following steps:
s1, selecting at least one vertical well around according to a target well position, and obtaining a rock core containing a dessert well section in the vertical well; carrying out resin sample preparation on the rock core;
s2, scanning the resin samples prepared in the step S1 in batch to obtain various mineral data of the vertical well dessert well section, wherein the mineral data comprise mineral types and contents;
s3, determining the discrimination standard of the dessert layer and the non-dessert layer according to the known characteristic parameters of the vertical well dessert well section, and establishing a typical section for dividing the dessert;
the discrimination criteria of the dessert layer and the non-dessert layer are as follows:
x represents porosity, y represents brittleness index,
represents the individual mineral content of the non-carbonate mineral, in mass percent, z represents the individual mineral content belonging to the carbonate mineral, in mass percent,
、
、
is a constant number of times, and is,
is a constant, wherein n takes the value of 2;
the constant coefficient calculation method comprises the following steps:
calculating out
: the porosity value is more than or equal to 12 percent of flat value by combining a laboratory core mercury intrusion testA mean maximum mercury intrusion saturation of 70%, wherein 30% of the pores are not connected, is calculated
，
=30/12；
Calculating out
：
= interbed minimum brittleness index/pay zone average brittleness index, wherein interbed minimum brittleness index refers to the minimum brittleness index of the interbed region of the vertical well, and pay zone average brittleness index refers to the average brittleness index of the pay zone of the vertical well;
s4, sampling rock debris at the target well position, and manufacturing a resin sample;
s5, scanning the resin sample in the step S4 to obtain various mineral data of the target well rock debris, wherein the mineral data comprises mineral types and contents;
s6, substituting each item of mineral data obtained in the step S5 into the step S3
In the calculation formula (2), obtain
Value of will
And comparing the value with the judgment standard in the step S3 to determine the dessert layer of the target well.
2. The method according to claim 1, wherein the specific method of step S1 is: selecting at least one vertical well in a shale oil research area according to a target well position, obtaining a core sample containing a dessert well section in the vertical well section, and cutting and pouring a plurality of resin samples with well number depth and well depth direction from shallow to deep.
3. The method according to claim 1, characterized in that in step S2, scanning is performed using a maipsccan automated mineral identification system.
4. The method of claim 1, wherein the step S3 of establishing the profile of the straight well section comprises the following steps: and (3) comparing the logging data of the straight well section with the mineral data obtained in the step (S2), comparing the trend conformity of a flushing resistivity RXO curve, a natural gamma GR curve and a density DEN curve in the logging data with the mineral data curve, determining characteristic minerals divided by the rock stratum according to the conformity, and dividing the core well section of the straight well into 12 sections along the depth direction according to the relative content of the minerals in the rock stratum.
5. The method of claim 4, wherein the identifying characteristics of the target layer sweet spot are determined from mineral data and rock mechanics parameters of the sweet spot section of the vertical well;
firstly, analyzing and counting the porosity and the brittleness index, then analyzing and counting the characteristic minerals, and finally determining the identification characteristics of the dessert well section.
6. The method of claim 1, wherein the rock debris sampling in step S4 is performed by: and determining a target entering point, drilling to the target entering point by using a drill bit, and taking rock debris samples according to field logging sampling intervals at the deflecting section part of the target entering point drilled by the drill bit.
7. The method of claim 1, wherein step S6 further comprises determining that the horizontal section of the target well is in the target zone according to the mineral data obtained in step S5 and the characteristic parameter in step S3.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104677734A (en) * | 2015-02-12 | 2015-06-03 | 中国石油大学(华东) | Multi-scale information integration tight formation brittleness index measuring method |
| WO2016144390A1 (en) * | 2015-03-12 | 2016-09-15 | Saudi Arabian Oil Company | Identifying sweet spots in unconventional hydrocarbon reservoirs |
| CN106204303A (en) * | 2016-07-08 | 2016-12-07 | 西安石油大学 | A kind of shale gas reservoir compressibility evaluation methodology based on weight distribution |
| CN110412661A (en) * | 2019-08-01 | 2019-11-05 | 中国石油天然气股份有限公司大港油田分公司 | The evaluation method and device of particulate oil gas pool dessert section advantage section cluster |
| CN110714753A (en) * | 2019-08-09 | 2020-01-21 | 中国华能集团清洁能源技术研究院有限公司 | Shale reservoir compressibility evaluation method |
| CN111694068A (en) * | 2020-05-30 | 2020-09-22 | 中国石油天然气股份有限公司 | Large-scale fresh water lake basin continental facies mud shale oil formation and enrichment evaluation method |
| CN114577833A (en) * | 2022-05-05 | 2022-06-03 | 克拉玛依禾鑫石油科技有限公司 | Method for rapidly and quantitatively analyzing clay minerals in glutenite detritus matrix and application |
| CN115030707A (en) * | 2021-03-03 | 2022-09-09 | 中国石油化工股份有限公司 | Rapid evaluation method of oil shale dessert |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130262069A1 (en) * | 2012-03-29 | 2013-10-03 | Platte River Associates, Inc. | Targeted site selection within shale gas basins |
| US11873709B2 (en) * | 2020-10-07 | 2024-01-16 | Saudi Arabian Oil Company | Log based diagenetic rock typing and sweet spot identification for tight gas sandstone reservoirs |
-
2022
- 2022-12-14 CN CN202211600961.7A patent/CN115598736B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104677734A (en) * | 2015-02-12 | 2015-06-03 | 中国石油大学(华东) | Multi-scale information integration tight formation brittleness index measuring method |
| WO2016144390A1 (en) * | 2015-03-12 | 2016-09-15 | Saudi Arabian Oil Company | Identifying sweet spots in unconventional hydrocarbon reservoirs |
| CN106204303A (en) * | 2016-07-08 | 2016-12-07 | 西安石油大学 | A kind of shale gas reservoir compressibility evaluation methodology based on weight distribution |
| CN110412661A (en) * | 2019-08-01 | 2019-11-05 | 中国石油天然气股份有限公司大港油田分公司 | The evaluation method and device of particulate oil gas pool dessert section advantage section cluster |
| CN110714753A (en) * | 2019-08-09 | 2020-01-21 | 中国华能集团清洁能源技术研究院有限公司 | Shale reservoir compressibility evaluation method |
| CN111694068A (en) * | 2020-05-30 | 2020-09-22 | 中国石油天然气股份有限公司 | Large-scale fresh water lake basin continental facies mud shale oil formation and enrichment evaluation method |
| CN115030707A (en) * | 2021-03-03 | 2022-09-09 | 中国石油化工股份有限公司 | Rapid evaluation method of oil shale dessert |
| CN114577833A (en) * | 2022-05-05 | 2022-06-03 | 克拉玛依禾鑫石油科技有限公司 | Method for rapidly and quantitatively analyzing clay minerals in glutenite detritus matrix and application |
Non-Patent Citations (7)
| Title |
|---|
| Characteristics of imbibition in tight oil reservoirs from the perspective of physical experiments and theory;Renyi Cao et al.;《Energy Sci Eng》;第1-13页 * |
| Reservoir Characterization of Eagle Ford Shale through Lithofacies Analysis for Identification of Sweet Spot and Best Landing Point;Ajit K. Sahoo et al.;《2013, Unconventional Resources Technology Conference》;第1376-1383页 * |
| 含岩屑砂岩储层" 甜点" 测井评价技术难点与对策;刘双莲等;《石油物探》;第59卷(第1期);第141-149页 * |
| 渤海湾盆地沧东凹陷孔二段湖相页岩油甜点评价与勘探实践;韩文中等;《石油勘探与开发》;第48卷(第4期);第777-786页 * |
| 湖相碳酸盐岩致密油主控因素及"甜点" 刻画;胡英杰;《特种油气藏》;第25卷(第6期);第6-11、18页 * |
| 致密地层岩石脆性指数的测井优化建模;范卓颖等;《石油学报》;第36卷(第11期);第1411-1420页 * |
| 表面活性剂对页岩油储层高温高压渗吸驱油效果的影响因素;张金风等;《大庆石油地质与开发》;第1-8页 * |
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