CN116256295A - Quantitative evaluation method for quick injury of loose sandstone reservoir - Google Patents
Quantitative evaluation method for quick injury of loose sandstone reservoir Download PDFInfo
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Abstract
The invention relates to a quantitative evaluation method for quick injury of a loose sandstone reservoir. The method comprises the following steps: s1, carrying out reservoir stratum quick-sensitivity evaluation experiments by using a rock core, and calculating to obtain the permeability of the rock core and the quick-sensitivity injury degree; s2: acquiring daily liquid yield, wellbore radius and perforation thickness parameters of a production well in a development site; calculating to obtain the critical flow rate of the oil production well, and further converting the critical flow rate of the core into the field application linear flow rate by utilizing the total porosity and the core cross-sectional area of the oil production well; s3: fitting a relation between effective porosity, permeability, clay content and core speed sensitivity on the corresponding field application linear flow velocity points of each core experiment; s4, fitting between linear flow velocity points of the coreless experiment by adopting a two-point method to obtain the damage rate of the reservoir; s5, obtaining reservoir stratum speed-sensitive damage distribution by utilizing well vibration combination among wells; the patent designs a method for accurately predicting quick injury of loose sandstone from the novel and applicable angles, and the stable and economic development of the power-assisted oil field is realized.
Description
Technical Field
The invention designs a loose sandstone reservoir quick-sensitivity injury quantitative evaluation method, which combines indoor core experiments, field development data and logging data, and realizes reservoir quick-sensitivity injury rate quantitative calculation by using the logging data and the field development data. The method comprises the steps of obtaining critical flow rate of particle migration of a loose sandstone reservoir and corresponding speed-sensitive damage rate through an indoor core experiment, converting the critical flow rate into field critical flow rate, and obtaining the relation between the damage rate and logging data through fitting under different critical flow rate conditions. The invention belongs to the technical field of reservoir protection.
Background
Loose sandstone is the main reservoir rock of the Suaeda 19-3 oil field, and the quality of the reservoir is related to the development benefit of the oil field. Two problems often occur with the development of this type of oilfield: (1): partial directional oil well large pressure difference production, the liquid yield is decreased more rapidly; (2): after the new water injection well and the old well are acidified, the water absorption capacity is quickly decreased. Preliminary analysis of the Suaeda 19-3 field was considered to be: ubiquitous particulate migration phenomena and reservoir sensitivity are key factors that cause both problems.
Tachypnea is an important component of reservoir sensitivity and is a manifestation of particulate migration. Large-scale particulate migration can cause reservoir roar to become plugged, thereby reducing reservoir seepage capacity and correspondingly reducing oil well production, which severely affects oil field development. The clay content of the Suaei 19-3 oilfield reservoir is high, and the phenomenon of particle migration is common. The quantitative evaluation of the quick injury degree of the reservoir stratum, the reasonable injection flow rate is provided for the development site and the importance thereof, and is a key step for ensuring the efficient development of the oil field.
From the current state of research at home and abroad, the existing reservoir quick-sensitive quantitative characterization method mainly has two problems: (1) Most of the speed-sensitive quantitative studies are focused on the core scale, and the results are given according to the indoor core flow experiment. The research result of the core scale is difficult to popularize to the whole well or the work area, and the applicability is not great; (2) The existing reservoirs have more data on the requirements of quick and quantitative evaluation, and the cost for analyzing the content of sensitive minerals in various reservoirs in the reservoirs is high. In general, the existing quantitative evaluation method for the reservoir quick-sensitivity injury has small research scale and insufficient applicability; and the modeling requirement data is more, the cost is high, and the like.
Disclosure of Invention
In order to solve the problems, the invention designs a quantitative evaluation method for quick injury of a loose sandstone reservoir. According to the method, an indoor core experiment is utilized, and the reservoir stratum speed-sensitive injury rate of different displacement mediums of the reservoir stratum under different flow rates is obtained through simulation; based on the core experiment, the relation between logging parameters and reservoir quick sensitivity is fitted, so that quantitative prediction of the loose sandstone reservoir quick sensitivity is realized. The invention combines reservoir microscopic parameters, field development parameters, logging parameters and seismic data, and constructs the loose sandstone reservoir speed-sensitive quantitative prediction method from different dimensions. The method can provide reasonable injection flow rate for oil field development, thereby reducing or avoiding particle migration of the loose sandstone reservoir and assisting the long-term economic development of the loose sandstone reservoir oil field.
A loose sandstone reservoir quick-sensitive injury quantitative evaluation method is characterized by comprising the following specific steps of:
s1: and (3) using simulated formation water and silicone oil to displace the natural rock core and the reservoir sand at different injection flow rates, and carrying out a reservoir quick-sensitivity evaluation experiment. And calculating the core permeability and the speed-sensitive injury degree at different displacement speeds.
S2: and 3 parameters of daily liquid production amount, borehole radius and perforation thickness of the oil field oil production well are obtained, and the critical flow rate of the oil production well is calculated by utilizing a formula. The critical flow rate is converted into the linear flow rate of practical application in site by adopting the total porosity and the core cross-sectional area of the oil production well.
S3: and converting the core displacement speed into on-site linear flow velocity, and fitting a relational expression between effective porosity, permeability and clay content and the core experiment speed-sensitive injury degree at each linear flow velocity point.
S4: and (3) between the linear flow velocity points, interpolating by adopting a two-point method to obtain the damage degree of the reservoir, thereby realizing the quantitative prediction of the speed sensitivity under any flow velocity.
S5: and (3) between wells without logging data constraint, adopting well-seismic combination to carry out constraint to obtain reservoir stratum speed-sensitive spreading distribution.
Further, in step S1, the change in permeability due to the sensitivity of flow rate is calculated by the formula (1):
wherein Dvn is the rate of change of permeability of the rock sample at different flow rates; kn is the corresponding permeability (mD) at different flow rates; ki is the initial permeability (mD) (the permeability corresponding to the minimum flow rate).
The flow rate of the corresponding previous point when the rock permeability change rate Dvn is greater than 20% is the critical flow rate. The critical flow obtained by the indoor core evaluation experiment needs to be converted into the field critical yield, and the process is carried out by the following formula (2) and formula (3):
wherein Qc is the indoor flow (ml/min); vc is the critical flow rate (m/d); a is the cross-sectional area (cm) of the core 2 )；
Porosity (%);
wherein Q is critical yield or implantation amount (m 3 D); h is the effective thickness (m) of the oil layer; r is (r) w Is the wellbore radius (cm); d is the diameter (cm) of the experimental core.
The extent of speed sensitive injury is defined as:
D v ＝max(D v1 …D v7 …D vn ) (4)
wherein Dv is the rate of speed sensitive injury; rock sample permeability injury rate at different flow rates.
In S2, the liquid production amount in the stable production period of half a year before the production of the on-site oil production well is applied, and the on-site linear flow rate is obtained through calculation in the formulas (2) and (3).
In S3, under the experimental linear flow rate, fitting to obtain a relational expression of effective porosity, permeability, argillaceous content and core speed-sensitive injury rate. The method preliminarily achieves the aim of predicting the damage rate of the reservoir by using the field logging data.
The linear flow rate of the core experiment is limited, and in order to realize the quantitative prediction of the speed sensitivity at any flow rate, in S4, a two-point method is adopted between critical flow rates to establish the relation among effective porosity, permeability, argillaceous content and the speed sensitivity injury rate. And taking the linear flow velocity and the injury rate corresponding to the core experiment as the left and right endpoints, and establishing a linear equation to obtain a velocity-sensitive prediction formula under the continuous flow velocity.
Compared with the prior art, the invention has the beneficial effects that
(1) The method is combined with the field development field to have wide practical applicability
According to the method, the indoor core flow experimental result is combined with logging data to obtain a model of single-well reservoir speed-sensitive quantitative characterization; on the basis, the Petrel software is utilized to extract attribute data of the whole working area, and the fitted formula is utilized to perform the quantitative evaluation of the full-area reservoir stratum speed sensitivity. The method can be applied to single well and work area level speed sensitivity evaluation, and has wide adaptability.
(2) Realizing the quantitative characterization of reservoir stratum speed sensitivity under any flow velocity
According to the invention, a two-point method is used for fitting between flow velocity points corresponding to the coreless experiment to obtain the speed-sensitive quantitative prediction model under any flow velocity. The speed-sensitive prediction model of any flow rate is a key of single well prediction, and provides a basis for the speed-sensitive quantitative characterization of the whole reservoir.
Drawings
FIG. 1 is a quantitative evaluation result of the velocity sensitive injury of a simulated formation oil displacement core reservoir;
FIG. 2 is a quantitative evaluation result of the simulated formation water displacement core reservoir velocity sensitive injury;
FIG. 3 is a three attribute model of a reservoir and a velocity sensitive injury spread profile;
fig. 4 is a summary drawing.
Detailed Description
The invention relates to a loose sandstone reservoir speed-sensitive injury quantitative evaluation method, which is more specifically described below by combining drawings and cases, so that the purposes, technical schemes and advantages of the invention are more clearly understood.
S1: in the design of the core speed-sensitive experiment evaluation scheme, two displacement media, namely simulated formation water and refined silicone oil, which are close to the on-site fluid property are adopted in consideration of the difference of the fluid properties under different operation modes. The experimental design of the step:
(1) Washing oil to be hydrophilic from an experimental core and reservoir sand which need to displace stratum water according to the specification of SY/T5358-2010, and then drying the core and reservoir sand which need to be used for the experiment, wherein the natural core needs to be tested for air permeability Kg;
(2) Vacuum saturating natural core with refined silicone oil and simulated stratum water respectively, soaking for more than 24h, filling reservoir sand into sand filling pipe, and soaking with silicone oil and stratum water for 2-3 days;
(3) And loading a fully saturated natural core rock sample and a sand filling pipe into the core holder, wherein the sand filling pipe is required to be provided with a nylon net on an outlet pad of the screen pipe to prevent large-area sand from being discharged, the natural core is required to enable the flowing direction of liquid in the rock sample to be consistent with the flowing direction of gas in the process of measuring the gas permeability, and the condition that no air remains in the system in the whole experimental process is ensured. And then slowly adjusting the confining pressure to 2.0MPa, and keeping the confining pressure value to be 1.5-2.0 MPa larger than the population pressure of the core all the time in the detection process.
(4) The displacement medium is a core of silicone oil and a sand filling pipe, and the silicone oil is respectively injected into the core at the flow rates of 0.25ml/min, 0.5ml/min, 1.0ml/min, 2.0ml/min, 4.0ml/min and 6.0 ml/min; the displacement medium is a rock core of stratum water and a sand filling pipe, and stratum water is respectively injected into the rock core at the flow rates of 0.25ml/min, 0.5ml/min, 1.0ml/min, 1.5ml/min, 2.0ml/min, 3.0ml/min, 4.0ml/min, 6.0ml/min, 8.0ml/min, 10.0ml/min and 12.0 ml/min; after the flow is stable, recording the displacement pressure difference under each displacement flow rate;
(5) After the experiment is completed, the experimental data are used for calculating the core permeability change rate Dvn and the speed-sensitive injury degree at different displacement speeds.
And judging the sensitivity of the hydrocarbon reservoir core to the flow rate according to the change relation of the injection speed and the permeability, and calculating the critical flow rate with obviously reduced permeability. As the flow rate increases, the flow rate of the previous point corresponding to the rock permeability change rate Dvn being greater than 20% is the critical flow rate.
Calculating the permeability change rate:
wherein Dvn is the rate of change of permeability of the rock sample at different flow rates; kn is the corresponding permeability (mD) at different flow rates; ki is the initial permeability (mD) (the permeability corresponding to the minimum flow rate).
Converting the critical flow obtained by the indoor core evaluation experiment into the on-site critical yield:
wherein Qc is the indoor flow (ml/min); vc is the critical flow rate (m/d); a is the cross-sectional area (cm) of the core 2 )；
Porosity (%); q is critical yield or implantation quantity (m 3 D); h is the effective thickness (m) of the oil layer; r is (r) w Is the wellbore radius (cm); d is the diameter (cm) of the experimental core.
Calculating the injury degree:
D v ＝max(D v1 …D v7 …D vn ) (4)
wherein Dv is the rate of speed sensitive injury; rock sample permeability injury rate at different flow rates.
Reservoir sensitivity injury evaluation criteria are as in table 1:
TABLE 1 reservoir sensitivity injury evaluation criteria
| Injury index (%) | ≤5 | 5～30 | 30～50 | 50～70 | ≥70 |
| Injury assessment | Without any means for | Weak and weak | Moderate weakness | Moderate bias strength | Strong strength |
S2: and (3) applying the liquid production amount of the field oil extraction well in the stable production period of half a year before the production, and carrying out calculation in the formulas (2) and (3) to obtain the field linear flow rate. Indoor core experiments were coupled to field applications.
In S3, fitting the on-site critical yield corresponding to the critical flow of the indoor core experiment to obtain a relational expression (table 2) of effective porosity, permeability, clay content and core quick-sensitivity injury rate. The method preliminarily achieves the aim of predicting the damage rate of the reservoir by using the field logging data.
TABLE 2 formula for the fit of porosity, permeability, and shale content to the damage rate at different flow rates
| Linear flow Rate (m/d) | Fitting formula | R 2 |
| 2 | y＝0.0126*KCOAT-338.58*VSH-683.66*PHIE+270.225 | 0.77 |
| 6 | y＝-0.031*KCOAT+187.174*VSH+567.16*PHIE-148.61 | 0.65 |
| 10 | y＝-0.043*KCOAT+311.95*VSH+773.34*PHIE-209.94 | 0.70 |
| 15 | y＝0.021*KCOAT-143.75*VSH-758.58*PHIE+238.61 | 0.65 |
| 20 | y＝-0.0133*KCOAT+321.52*VSH-365.81*PHIE+87.013 | 0.71 |
| 25 | y＝-0.0288*KCOAT+318.94*VSH-507.05*PHIE+157.28 | 0.78 |
In the formulas of Table 2, KOAT is the effective porosity, PHIE is the permeability, and VSH is the clay content.
S4: indoor core experiments cannot simulate reservoir velocity-sensitive conditions at all critical flows. The invention adopts a two-point method to establish an equation, and the damage rate between any flow rates and any linear flow rates is improved. And obtaining an injury rate calculation formula under any flow rate by taking known linear flow rate points as left and right end points through a two-point slope interpolation method. The solving mode is as follows:
set at linear flow velocity v 1 Sensitivity value of y 1 The method comprises the steps of carrying out a first treatment on the surface of the At a linear flow velocity v 2 The core velocity sensitivity value of (2) is y 2 . Then the linear flow rate is v 1 And v 2 Velocity sensitive value Y of arbitrary flow velocity v:
s5: logging data can only reflect longitudinal stratum parameters at well points, and seismic data can reflect lateral reservoir spread. And (3) extracting amplitude attribute and frequency division attribute of 50Hz and 60Hz from the seismic attribute data by adopting a well-seismic combination method to establish a seismic attribute fusion. And respectively monitoring the porosity, the permeability and the clay content of the target layer by using a neural network module of the Petrel platform, and carrying out supervised machine learning training to respectively establish an attribute model of the porosity, the permeability and the clay content. The reservoir velocity sensitive spread prediction situation is calculated by the formulas in S3 and S4 as shown in FIG. 3:
the invention discloses a loose sandstone reservoir speed-sensitive quantitative prediction method based on multidimensional, fusion of indoor core experiments, logging, on-site development and seismic data design. The method can realize quick and quantitative prediction of the loose sandstone reservoir, lighten or avoid the particle migration of the reservoir and assist the long-term economic scale development of the oil field.
Claims (4)
1. The quantitative evaluation method for the quick injury of the loose sandstone reservoir is characterized by comprising the following steps of:
s1: using simulated formation water and silicone oil to displace natural rock core and reservoir sand at different injection flow rates, performing a reservoir quick-sensitivity evaluation experiment, and calculating the rock core permeability and quick-sensitivity injury degree at different displacement speeds;
s2: acquiring daily liquid yield, wellbore radius and perforation thickness parameters of a production well in a development site; calculating to obtain the critical flow rate of the oil production well; further, converting the core critical flow rate into the field application linear flow rate by utilizing the total porosity and the core cross-sectional area of the oil production well;
s3: fitting a relation between effective porosity, permeability, clay content and core speed sensitivity on the corresponding field application linear flow velocity points of each core experiment;
s4: establishing a linear equation relation between linear flow velocity points of the coreless experiment by adopting a two-point method to obtain the reservoir damage rate at any flow velocity;
s5, extracting amplitude attribute and frequency division attribute of 50Hz and 60Hz in the seismic attribute data by using a well earthquake combination method between wells to establish a seismic attribute fusion; and (3) establishing an attribute model for establishing porosity, permeability and clay content by using Petrel software, and calculating to obtain the reservoir quick-sensitive spreading prediction condition by using the formulas in S3 and S4.
2. The quantitative evaluation method for the rapid injury of the unconsolidated sandstone reservoir according to claim 1, wherein the quantitative evaluation method comprises the following steps: in step S3, on the on-site linear flow velocity point corresponding to each core experiment, a relation between the core velocity sensitivity and the logging data is obtained by fitting with a minimum curvature method:
In the table: KCOAT is porosity, VSH is the clay content, PHIE is permeability.
3. The quantitative evaluation method for the rapid injury of the unconsolidated sandstone reservoir according to claim 1, wherein the quantitative evaluation method comprises the following steps: in step S4, on the linear flow velocity point of the coreless experiment, a relation between the core velocity sensitivity and logging data is obtained by fitting by a two-point method, and a velocity sensitivity quantitative prediction relation under any flow velocity is obtained; the solving mode is as follows:
wherein, Y is the speed-sensitive value of any flow velocity v, and is linear flow v 1 A speed sensitivity value of y 1 Linear flow velocity v 2 The core velocity sensitivity value of (2) is y 2 。
4. The quantitative evaluation method for the rapid injury of the unconsolidated sandstone reservoir according to claim 1, wherein the quantitative evaluation method comprises the following steps: in step S5, through well-seismic combination, an attribute model for establishing porosity, permeability and clay content is established by using Petrel software, so that reservoir quick-sensitive spreading prediction is realized.
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| CN106153518A (en) * | 2016-06-22 | 2016-11-23 | 西南石油大学 | Compact sandstone gas reservoir fracturing liquid damage experimental evaluation method |
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| CN116859021A (en) * | 2023-07-06 | 2023-10-10 | 西南石油大学 | Method for evaluating reservoir sensitivity through productivity damage rate |
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