CN113049784A - Prediction method suitable for water sensitivity of shale reservoir - Google Patents
Prediction method suitable for water sensitivity of shale reservoir Download PDFInfo
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 76
- 238000000034 method Methods 0.000 title claims abstract description 45
- 230000035945 sensitivity Effects 0.000 title claims abstract description 28
- 230000006378 damage Effects 0.000 claims abstract description 35
- 229910052900 illite Inorganic materials 0.000 claims abstract description 32
- VGIBGUSAECPPNB-UHFFFAOYSA-L nonaaluminum;magnesium;tripotassium;1,3-dioxido-2,4,5-trioxa-1,3-disilabicyclo[1.1.1]pentane;iron(2+);oxygen(2-);fluoride;hydroxide Chemical compound [OH-].[O-2].[O-2].[O-2].[O-2].[O-2].[F-].[Mg+2].[Al+3].[Al+3].[Al+3].[Al+3].[Al+3].[Al+3].[Al+3].[Al+3].[Al+3].[K+].[K+].[K+].[Fe+2].O1[Si]2([O-])O[Si]1([O-])O2.O1[Si]2([O-])O[Si]1([O-])O2.O1[Si]2([O-])O[Si]1([O-])O2.O1[Si]2([O-])O[Si]1([O-])O2.O1[Si]2([O-])O[Si]1([O-])O2.O1[Si]2([O-])O[Si]1([O-])O2.O1[Si]2([O-])O[Si]1([O-])O2 VGIBGUSAECPPNB-UHFFFAOYSA-L 0.000 claims abstract description 32
- 239000011148 porous material Substances 0.000 claims abstract description 23
- 239000011707 mineral Substances 0.000 claims abstract description 21
- 208000027418 Wounds and injury Diseases 0.000 claims abstract description 18
- 208000014674 injury Diseases 0.000 claims abstract description 18
- 229910052500 inorganic mineral Inorganic materials 0.000 claims abstract description 18
- 229910052901 montmorillonite Inorganic materials 0.000 claims abstract description 15
- 238000005259 measurement Methods 0.000 claims abstract description 13
- 239000003511 smectite mixed layer mineral Substances 0.000 claims abstract description 13
- 230000008859 change Effects 0.000 claims abstract description 12
- 239000011248 coating agent Substances 0.000 claims abstract description 4
- 238000000576 coating method Methods 0.000 claims abstract description 4
- 238000010183 spectrum analysis Methods 0.000 claims abstract description 4
- 230000008569 process Effects 0.000 claims description 16
- 238000004364 calculation method Methods 0.000 claims description 11
- 239000007788 liquid Substances 0.000 claims description 10
- 238000001035 drying Methods 0.000 claims description 6
- 238000011065 in-situ storage Methods 0.000 claims description 6
- 230000015572 biosynthetic process Effects 0.000 claims description 5
- 238000002791 soaking Methods 0.000 claims description 4
- 229920006395 saturated elastomer Polymers 0.000 claims description 3
- 238000005266 casting Methods 0.000 abstract description 2
- 238000004512 die casting Methods 0.000 abstract 1
- 239000010410 layer Substances 0.000 description 15
- 238000012360 testing method Methods 0.000 description 7
- 230000035699 permeability Effects 0.000 description 6
- 239000011435 rock Substances 0.000 description 5
- 238000011156 evaluation Methods 0.000 description 4
- 239000004927 clay Substances 0.000 description 3
- 239000002734 clay mineral Substances 0.000 description 3
- 239000013078 crystal Substances 0.000 description 3
- 239000012530 fluid Substances 0.000 description 3
- 239000002245 particle Substances 0.000 description 3
- 238000006073 displacement reaction Methods 0.000 description 2
- 238000005553 drilling Methods 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 230000005012 migration Effects 0.000 description 2
- 238000013508 migration Methods 0.000 description 2
- 238000010998 test method Methods 0.000 description 2
- 238000004438 BET method Methods 0.000 description 1
- 238000002441 X-ray diffraction Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 238000011549 displacement method Methods 0.000 description 1
- 239000012153 distilled water Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000008398 formation water Substances 0.000 description 1
- 238000000227 grinding Methods 0.000 description 1
- 238000002347 injection Methods 0.000 description 1
- 239000007924 injection Substances 0.000 description 1
- 239000011229 interlayer Substances 0.000 description 1
- 230000002427 irreversible effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- QSHDDOUJBYECFT-UHFFFAOYSA-N mercury Chemical compound [Hg] QSHDDOUJBYECFT-UHFFFAOYSA-N 0.000 description 1
- 229910052753 mercury Inorganic materials 0.000 description 1
- 238000000655 nuclear magnetic resonance spectrum Methods 0.000 description 1
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- 238000002360 preparation method Methods 0.000 description 1
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- 238000001228 spectrum Methods 0.000 description 1
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- G01N33/24—Earth materials
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/08—Investigating permeability, pore-volume, or surface area of porous materials
- G01N15/088—Investigating volume, surface area, size or distribution of pores; Porosimetry
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Abstract
The invention relates to a prediction method suitable for water sensitivity of a shale reservoir, which comprises the following steps: sample pretreatment; finding an illite and illite mixed layer in the cubic sample in a target view field; and confirming that illite and illite-montmorillonite mixed layers exist in the target vision field through an energy spectrum analysis system; measurement of illite content WI% and content of illite-montmorillonite mixed layer WISPercent; measuring illite mineral area S before water-sensitive injuryI frontIllite-smectite mixed layer mineral area SIS frontAnd pore area Sk front(ii) a Water-sensitive injuries; coating a film on the surface of the cube sample subjected to water-sensitive injury, and then placing the cube sample on the sample seat again at the same position; measuring illite mineral area S after water-sensitive injuryAfter IIllite-smectite mixed layer mineral area SAfter ISAnd pore area Sk is back(ii) a Calculating the illite mineral areaExpansion ratio phiIIllite-smectite mixed layer mineral area expansion rate phiISAnd rate of change of pore area phik(ii) a Then calculating a water sensitivity predicted value Y; the invention solves the problem that the surface porosity cannot be quantitatively analyzed due to the difficulty in die casting of the shale sample casting body slice.
Description
Technical Field
The invention relates to the technical field of petroleum, in particular to a prediction method suitable for water sensitivity of a shale reservoir.
Background
During the operation processes of drilling, well completion, fracturing and injection production of oil and gas fields, external fluid enters the stratum and is easy to react with clay minerals in a series of ways, such as clay mineral expansion, migration, dispersion and the like, so that the influence on the permeability and the productivity of reservoir holes is brought to different degrees. Irreversible reservoir damage can also result if not properly constructed. The clay expansion mainly causes the reduction of the radius of a seepage pore or a throat of a reservoir, the migration of particles blocks seepage channel systems such as the pore and the throat, and the permeability of the reservoir is reduced.
The core displacement method is the most common reservoir water sensitivity evaluation method at present, and is also a macroscopic comprehensive water sensitivity evaluation method closest to reservoir conditions. Various fluids associated with formation damage are injected under approximate formation conditions according to darcy's law, and the permeability of the rock sample and its changes are measured to evaluate the extent of reservoir permeability damage. Reference is mainly made to the experimental industry standard (SY/T5358-2010), but the standard is mainly suitable for sensitivity evaluation of clastic rock reservoir rock samples with air permeability of more than 1 millidarcy. No reference standard exists for shale and tight sandstone reservoirs with air permeability less than 1 millidarcy.
Because the shale is very compact, the conventional core displacement experiment method is difficult to complete the water sensitivity test of the shale, and in the displacement process, fluid is difficult to enter a core sample, and other means such as manual seam making, use of an artificial core and the like are usually needed. The natural shale sample contains a large amount of clay minerals, is very easy to swell when meeting water, has very low success rate in the process of artificial seam making and sample drilling, and brings certain difficulty to the preparation of the sample.
Therefore, the water-sensitive damage degree of the shale reservoir stratum is indirectly predicted by combining tests such as a shale expansion instrument test method, a pore throat radius measurement test method, water-sensitive mineral crystal layer spacing measurement and the like.
Shale dilatometer experimental method: grinding a rock core sample to particles with a certain size, soaking the particles in liquid such as formation water, distilled water and the like, and testing the rock sample expansion rate by adopting a shale expansion instrument, wherein the calculation formula is as follows:
wherein E is the expansion ratio,%; h istThe height of the clay sample at the time t is mm; h is0Is the initial height, mm, of the clay sample.
Throat radius measurement test: and obtaining the pore structure and pore diameter change of the reservoir by a mercury intrusion method, a BET method and a nuclear magnetic resonance spectrum analysis method.
Testing the interval between crystal layers of the water-sensitive minerals: by using the X-ray diffraction principle, the inter-layer distance between the water-sensitive mineral and the crystal layer before and after expansion can be quantitatively measured according to the Bragg equation (d ═ lambda/2 sin theta).
The method is a water-sensitive injury evaluation method and has the following defects: firstly, mineral types and occurrence state changes which cause reservoir water sensitivity damage cannot be accurately and intuitively obtained; reservoir space structure change and pore area change of reservoir water sensitivity damage cannot be accurately and intuitively obtained; and thirdly, the water-sensitive mineral expansion rate change caused by the water-sensitive damage cannot be intuitively and accurately obtained.
Disclosure of Invention
The invention aims to solve the problems and provides a prediction method suitable for water sensitivity of a shale reservoir.
The technical scheme of the invention is as follows:
a prediction method suitable for water sensitivity of a shale reservoir comprises the following steps:
(1) sample pretreatment: making the core sample into a cubic sample of 10mm multiplied by 10 mm; fixing the cubic sample on a sample holder;
(2) selecting a target view, and finding the illite and the illite-montmorillonite mixed layer in the cubic sample in the target view; and confirming that illite and illite-montmorillonite mixed layers exist in the target vision field through an energy spectrum analysis system;
(3) measuring the content W of illite in the cubic sampleI% content of illite-montmorillonite mixed layer WIS％；
Measurement of illite mineral area S of cubic sample before water-sensitive injuryI frontIllite-smectite mixed layer mineral area SIS frontAnd pore area Sk front；
(4) Taking down the cubic sample from the sample seat for water-sensitive damage;
(5) coating a film on the surface of the cube sample subjected to water-sensitive injury, and then placing the cube sample on the sample seat again at the same position; measurement of illite mineral area S of cube sample after water-sensitive injuryAfter IIllite-smectite mixed layer mineral area SAfter ISAnd pore area Sk is back(ii) a Calculating the area expansion rate phi of the illite mineralIIllite-smectite mixed layer mineral area expansion rate phiISAnd rate of change of pore area phik；
(6) Calculating a water sensitivity predicted value Y;
and (2) when the sample is preprocessed in the step (1), finding a point in the cubic sample, marking the corresponding position of the point and the sample seat, and when the surface of the cubic sample subjected to water-sensitive damage is coated with a film and then placed on the sample seat again at the same position in the step (5), placing the cubic sample at the corresponding position of the point and the sample seat, and determining that the positions of the samples on the sample seat are consistent.
Before the water-sensitive injury in the step (3) and after the water-sensitive injury in the step (5), when the cube sample is measured, the points are fixed to the target vision field, so that the in-situ fixed-point same-multiple observation is realized; and (5) determining that the measurement conditions before and after the water-sensitive injury are consistent.
The process of the water-sensitive injury in the step (4) is as follows: under the condition of simulating the formation pressure and temperature, a cubic sample is pumped out through a vacuumizing saturation device; and adding liquid into the vacuumizing saturation device to soak the cubic sample, and taking out and drying the sample after the sample is fully saturated with the liquid.
The liquid is in-situ layer water, the soaking time is 48 hours, and the drying is carried out at the temperature lower than 100 ℃.
The illite area expansion ratio phiIThe calculation process of (2) is as follows:
area expansion ratio phi of illite-montmorillonite mixed layerISThe calculation process of (2) is as follows:
rate of change of pore area ΦkThe calculation process of (2) is as follows:
the invention has the technical effects that:
the invention determines the water-sensitive mineral types to be illite and illite mixed layers by utilizing a scanning electron microscope and combining an energy spectrum method, and records the illite content WI% and content of illite-montmorillonite mixed layer WISPercent; carrying out water-sensitive damage treatment on the cubic sample by a vacuumizing saturation device; calculating the area expansion rate phi of illite minerals before and after the water-sensitive damage of the cubic sampleIIllite-smectite mixed layer mineral area expansion rate phiISAnd rate of change of pore area phik(ii) a And then calculating to obtain a water sensitivity prediction value. The water-sensitive damage degree is obtained through the method, the microscopic changes of the sensitive mineral types, mineral occurrence states, structures and pore spaces can be obtained, the method is a simple, rapid and visual shale reservoir water-sensitive prediction method, and more real bases can be provided for researching the shale reservoir water-sensitive damage mechanism. Meanwhile, the problem that the surface porosity cannot be quantitatively analyzed due to the fact that the shale sample casting body slice is difficult to die-cast is solved, pollution is reduced, the process is simplified, and meanwhile cost is saved.
Detailed Description
Example 1
A prediction method suitable for water sensitivity of a shale reservoir comprises the following steps:
(1) sample pretreatment: making the core sample into a cubic sample of 10mm multiplied by 10 mm; fixing the cubic sample on a sample holder;
(2) selecting a target view, and finding the illite and the illite-montmorillonite mixed layer in the cubic sample in the target view; and confirming that illite and illite-montmorillonite mixed layers exist in the target vision field through an energy spectrum analysis system;
(3) measuring the content W of illite in the cubic sampleI% content of illite-montmorillonite mixed layer WIS％；
Measurement of illite mineral area S of cubic sample before water-sensitive injuryI frontIllite-smectite mixed layer mineral area SIS frontAnd pore area Sk front；
(4) Taking down the cubic sample from the sample seat for water-sensitive damage;
(5) coating a film on the surface of the cube sample subjected to water-sensitive injury, and then placing the cube sample on the sample seat again at the same position; measurement of illite mineral area S of cube sample after water-sensitive injuryAfter IIllite-smectite mixed layer mineral area SAfter ISAnd pore area Sk is back(ii) a Calculating the area expansion rate phi of the illite mineralIIllite-smectite mixed layer mineral area expansion rate phiISAnd rate of change of pore area phik；
(6) Calculating a water sensitivity predicted value Y;
example 2
On the basis of embodiment 1, the method further comprises the following steps:
and (2) when the sample is preprocessed in the step (1), finding a point in the cubic sample, marking the corresponding position of the point and the sample seat, and when the surface of the cubic sample subjected to water-sensitive damage is coated with a film and then placed on the sample seat again at the same position in the step (5), placing the cubic sample at the corresponding position of the point and the sample seat, and determining that the positions of the samples on the sample seat are consistent.
Before the water-sensitive injury in the step (3) and after the water-sensitive injury in the step (5), when the cube sample is measured, the points are fixed to the target vision field, so that the in-situ fixed-point same-multiple observation is realized; and (5) determining that the measurement conditions before and after the water-sensitive injury are consistent.
The process of the water-sensitive injury in the step (4) is as follows: under the condition of simulating the formation pressure and temperature, a cubic sample is pumped out through a vacuumizing saturation device; and adding liquid into the vacuumizing saturation device to soak the cubic sample, and taking out and drying the sample after the sample is fully saturated with the liquid. Wherein the liquid is in-situ layer water, the soaking time is 48h, and the drying is carried out at the temperature lower than 100 ℃.
Example 3
On the basis of embodiment 2, the method further comprises the following steps:
the illite area expansion ratio phiIThe calculation process of (2) is as follows:
area expansion ratio phi of illite-montmorillonite mixed layerISThe calculation process of (2) is as follows:
rate of change of pore area ΦkThe calculation process of (2) is as follows:
examples of specific applications
Taking the prolonged south shale reservoir of the oil field as an example, the prediction method provided by the invention can obtain the following data:
finally, the water sensitivity predicted value Y and the water sensitivity index measured value I are respectively carried out on 20 groups of data by utilizing a root mean square error formulaWAnd (4) standard error calculation is carried out, wherein error values of three groups of data are large, account for 15% of the total test data and are lower than 80% of the total test data, the root mean square error (delta) of 20 groups of data is 1.52, and the delta value is smaller than 2, so that the accuracy of the predicted value Y of the water sensitivity of the mathematical model is good, and the predicted value Y can be used as an index for judging the water sensitivity of the shale reservoir.
Claims (6)
1. A prediction method suitable for water sensitivity of a shale reservoir is characterized by comprising the following steps: the method comprises the following steps:
(1) sample pretreatment: making the core sample into a cubic sample of 10mm multiplied by 10 mm; fixing the cubic sample on a sample holder;
(2) selecting a target view, and finding the illite and the illite-montmorillonite mixed layer in the cubic sample in the target view; and confirming that illite and illite-montmorillonite mixed layers exist in the target vision field through an energy spectrum analysis system;
(3) measuring the content W of illite in the cubic sampleI% content of illite-montmorillonite mixed layer WIS％；
Measurement of illite mineral area S of cubic sample before water-sensitive injuryI frontIllite-smectite mixed layer mineral area SIS frontAnd pore area Sk front；
(4) Taking down the cubic sample from the sample seat for water-sensitive damage;
(5) coating a film on the surface of the cube sample subjected to water-sensitive injury, and then placing the cube sample on the sample seat again at the same position; measurement of illite mineral area S of cube sample after water-sensitive injuryAfter IIllite-smectite mixed layer mineral area SAfter ISAnd pore area Sk is back(ii) a Calculating the area expansion rate phi of the illite mineralIIllite-smectite mixed layer mineral area expansion rate phiISAnd rate of change of pore area phik；
(6) Calculating a water sensitivity predicted value Y;
2. the method for predicting the water sensitivity of the shale reservoir according to claim 1, wherein the method comprises the following steps: and (2) when the sample is preprocessed in the step (1), finding a point in the cubic sample, marking the corresponding position of the point and the sample seat, and when the surface of the cubic sample subjected to water-sensitive damage is coated with a film and then placed on the sample seat again at the same position in the step (5), placing the cubic sample at the corresponding position of the point and the sample seat, and determining that the positions of the samples on the sample seat are consistent.
3. The method for predicting the water sensitivity of the shale reservoir according to claim 2, wherein the method comprises the following steps: before the water-sensitive injury in the step (3) and after the water-sensitive injury in the step (5), when the cube sample is measured, the points are fixed to the target vision field, so that the in-situ fixed-point same-multiple observation is realized; and (5) determining that the measurement conditions before and after the water-sensitive injury are consistent.
4. The method for predicting the water sensitivity of the shale reservoir according to claim 3, wherein the method comprises the following steps: the process of the water-sensitive injury in the step (4) is as follows: under the condition of simulating the formation pressure and temperature, a cubic sample is pumped out through a vacuumizing saturation device; and adding liquid into the vacuumizing saturation device to soak the cubic sample, and taking out and drying the sample after the sample is fully saturated with the liquid.
5. The method for predicting the water sensitivity of the shale reservoir according to claim 4, wherein the method comprises the following steps: the liquid is in-situ layer water, the soaking time is 48 hours, and the drying is carried out at the temperature lower than 100 ℃.
6. The method for predicting the water sensitivity of the shale reservoir according to claim 5, wherein the method comprises the following steps: the illite area expansion ratio phiIThe calculation process of (2) is as follows:
area expansion ratio phi of illite-montmorillonite mixed layerISThe calculation process of (2) is as follows:
rate of change of pore area ΦkThe calculation process of (2) is as follows:
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|---|---|---|---|---|
| CN113984620A (en) * | 2021-10-25 | 2022-01-28 | 中国科学院武汉岩土力学研究所 | Uranium reservoir acidification and permeation-increasing transformation evaluation method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105067794A (en) * | 2015-07-24 | 2015-11-18 | 成都理工大学 | Method for testing water sensitivity, salt sensitivity and alkali sensitivity of shale reservoir stratum |
| CN108897906A (en) * | 2018-05-24 | 2018-11-27 | 西安石油大学 | A kind of reservoir sensitivity damage analogy method based on digital cores model |
| CN111694856A (en) * | 2020-06-11 | 2020-09-22 | 中国石油大学(北京) | Intelligent prediction method and device for reservoir sensitivity |
| CN111694855A (en) * | 2020-06-11 | 2020-09-22 | 中国石油大学(北京) | Intelligent prediction data processing method and device for reservoir sensitivity |
-
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105067794A (en) * | 2015-07-24 | 2015-11-18 | 成都理工大学 | Method for testing water sensitivity, salt sensitivity and alkali sensitivity of shale reservoir stratum |
| CN108897906A (en) * | 2018-05-24 | 2018-11-27 | 西安石油大学 | A kind of reservoir sensitivity damage analogy method based on digital cores model |
| CN111694856A (en) * | 2020-06-11 | 2020-09-22 | 中国石油大学(北京) | Intelligent prediction method and device for reservoir sensitivity |
| CN111694855A (en) * | 2020-06-11 | 2020-09-22 | 中国石油大学(北京) | Intelligent prediction data processing method and device for reservoir sensitivity |
Non-Patent Citations (2)
| Title |
|---|
| 吴广 等: "储层水敏系统评价方法与水敏机理研究", 《石油天然气学报》 * |
| 蒲春生 等著: "《异常应力构造低渗油藏大段泥页岩井壁稳定》", 31 December 2015, 中国石油大学出版社 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113984620A (en) * | 2021-10-25 | 2022-01-28 | 中国科学院武汉岩土力学研究所 | Uranium reservoir acidification and permeation-increasing transformation evaluation method |
| CN113984620B (en) * | 2021-10-25 | 2022-11-22 | 中国科学院武汉岩土力学研究所 | Uranium reservoir acidizing permeability-increasing reconstructability evaluation method |
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