CN107975363A - Condensate gas well takes liquid critical flow Forecasting Methodology and device - Google Patents
Condensate gas well takes liquid critical flow Forecasting Methodology and device Download PDFInfo
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- CN107975363A CN107975363A CN201710983242.0A CN201710983242A CN107975363A CN 107975363 A CN107975363 A CN 107975363A CN 201710983242 A CN201710983242 A CN 201710983242A CN 107975363 A CN107975363 A CN 107975363A
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B47/00—Survey of boreholes or wells
Abstract
What the embodiment of the present application provided a kind of condensate gas well takes liquid critical flow Forecasting Methodology and device, and this method includes：Determine the fisrt feature parameter and second feature parameter of condensate gas well, the fisrt feature parameter includes hole angle, surface tension, gas-liquid density, the critical Weber Number and drag coefficient of drop, and the second feature parameter includes Gaseous Z-factor, oil pipe cross-sectional area, temperature and pressure；According to the fisrt feature parameter, determine the condensate gas well takes liquid critical gas flow velocity；Liquid critical gas flow velocity and the second feature parameter are taken according to described, determines that the condensate gas well takes liquid critical flow.The embodiment of the present application can improve the accuracy for taking the prediction of liquid critical flow of condensate gas well.
Description
Technical field
This application involves condensate gas well production technique field, more particularly, to a kind of condensate gas well to take liquid critical flow pre-
Survey method and device.
Background technology
Condensate gas is that oil is dissolved in the mixture formed in natural gas under high-temperature and high-pressure conditions, and it is thousands of to be frequently located in underground
In the rock of meter Shen.After subsurface temperature, pressure exceed critical condition, liquid hydrocarbon retrograde evaporation and the gas that generates are referred to as solidifying
Gassing.After extraction, inverse light oil, i.e. condensate are condensed into since surface pressure, temperature reduce.
Different from conventional gas well, condensate gas well is in recovery process, with the reduction of stratum energy and bottom pressure, condensation
Oil or water flooding can output, there is oil-producing and grease with two kinds of operating modes of production, form oil-gas two-phase flow in the wellbore and move or oil gas water
Three-phase Flow.When upper returning air-flow amount is not enough to drop to carry out pit shaft, shaft bottom will produce hydrops, so as to cause condensate gas
Significantly the underproduction even stops production well.Therefore, be correctly predicted out condensate gas well takes liquid critical flow to its rational proration and carrying
High recovery rate is of great significance.
Only have the liquid critical flow of taking for being suitable for conventional gas well to calculate method at present, and lack for definite condensate gas well
Take liquid critical flow and calculate method.Since conventional gas well and condensate gas well property are different, if by conventional gas well to take liquid critical
Method of calculating flux is applied to the critical flow for calculating condensate gas well, often brings large error.Therefore, how accurately to determine
The liquid critical flow of taking of condensate gas well is a technical problem to be solved urgently.
The content of the invention
What the purpose of the embodiment of the present application was to provide a kind of condensate gas well takes liquid critical flow Forecasting Methodology and device, with
Improve the accuracy for taking liquid critical flow for determining condensate gas well.
To reach above-mentioned purpose, on the one hand, the embodiment of the present application provide a kind of condensate gas well to take liquid critical flow pre-
Survey method, including：
Determine the fisrt feature parameter and second feature parameter of condensate gas well, the fisrt feature parameter include hole angle,
Surface tension, gas-liquid density, the critical Weber Number and drag coefficient of drop, the second feature parameter include gas deviation system
Number, oil pipe cross-sectional area, temperature and pressure；
According to the fisrt feature parameter, determine the condensate gas well takes liquid critical gas flow velocity；
Liquid critical gas flow velocity and the second feature parameter are taken according to described, determines that the condensate gas well takes liquid critical flow
Amount.
The condensate gas well of the embodiment of the present application takes liquid critical flow Forecasting Methodology, described to be determined according to the characteristic parameter
The condensate gas well takes liquid critical gas flow velocity, including：
Liquid critical gas flow velocity is taken according to what the following formula determined the condensate gas well：
Wherein, u takes liquid critical gas flow velocity, We for condensate gas wellcrFor the critical Weber Number of drop, β is hole angle, Cd
For the drag coefficient of drop, ρlFor fluid density, ρgFor gas density, σ is gas-liquid surface tension force.
The condensate gas well of the embodiment of the present application takes liquid critical flow Forecasting Methodology, and liquid critical gas is taken described in the basis
Flow velocity and the second feature parameter, determine that the condensate gas well takes liquid critical flow, including：
Determine that the condensate gas well of the condensate gas well takes liquid critical flow according to the following formula：
Wherein, QscLiquid critical flow is taken for the condensate gas well, A is oil pipe cross-sectional area, and p is pressure, and u is condensate gas well
Take liquid critical gas flow velocity, Z is Gaseous Z-factor, and T is temperature.
The condensate gas well of the embodiment of the present application takes liquid critical flow Forecasting Methodology, the drag coefficient of the drop by with
Under type obtains：
Determine the drag coefficient of rigid spheres corresponding with drop in condensate gas well；
The drag coefficient of the drop is determined according to the drag coefficient of the rigid spheres.
The condensate gas well of the embodiment of the present application takes liquid critical flow Forecasting Methodology, under laminar flow condition, the rigid ball
The drag coefficient of body is determined by the following formula：
Wherein, Cd(solid)For the drag coefficient of drop, Re is Reynolds number, and tanh is hyperbolic tangent function.
The condensate gas well of the embodiment of the present application takes liquid critical flow Forecasting Methodology, under turbulent-flow conditions, the rigid ball
The drag coefficient of body is determined by the following formula：
Cd(solid)=-3.316 × 10-18Re3+7.3×10-12Re2-4.918×10-6Re+1.143
Wherein, Cd(solid)For the drag coefficient of drop, Re is Reynolds number.
The condensate gas well of the embodiment of the present application takes liquid critical flow Forecasting Methodology, the draging according to the rigid spheres
Force coefficient determines the drag coefficient of the drop, including：
According to formulaDetermine the drag coefficient of the drop；
Wherein, Cd(droplet)For the drag coefficient of drop, Cd(solid)For the drag coefficient of rigid spheres, μlGlued for liquid
Degree, μgFor gas viscosity, Re is Reynolds number.
The condensate gas well of the embodiment of the present application takes liquid critical flow Forecasting Methodology, under oil-producing operating mode, the surface
Power is determined by the following formula：
Wherein, σgoFor oil gas surface tension, t is temperature, and API is severe, and p is pressure, γgFor gas relative density.
The condensate gas well of the embodiment of the present application takes liquid critical flow Forecasting Methodology, in the case where grease is with operating mode is produced, the table
Face tension force is determined by the following formula：
Wherein,σgwFor air water surface tension, t is temperature, and σ (23.33) is
Air water surface tension of the temperature at 23.33 DEG C, σ (137.78) are air water surface tension of the temperature at 137.78 DEG C, and p is pressure
Power.
The condensate gas well of the embodiment of the present application takes liquid critical flow Forecasting Methodology, and the Gaseous Z-factor passes through following
Formula determines：
Wherein, Z is Gaseous Z-factor, and p is pressure, and T is temperature, γgFor gas relative density.
On the other hand, what the embodiment of the present application additionally provided a kind of condensate gas well takes liquid critical flow prediction meanss, including：
Characteristic parameter determining module, for determining the fisrt feature parameter and second feature parameter of condensate gas well, described
One characteristic parameter includes hole angle, surface tension, gas-liquid density, the critical Weber Number and drag coefficient of drop, and described second is special
Levying parameter includes Gaseous Z-factor, oil pipe cross-sectional area, temperature and pressure；
Critical flow velocity determining module, for according to the fisrt feature parameter, determine the condensate gas well to take liquid critical
Gas flow rate；
Critical flow determining module, for taking liquid critical gas flow velocity and the second feature parameter according to, determines
The condensate gas well takes liquid critical flow.
On the other hand, what the embodiment of the present application additionally provided another condensate gas well takes liquid critical flow prediction meanss, bag
Memory, processor and the computer program being stored on the memory are included, the computer program is by the processor
Following steps are performed during operation：
Determine the fisrt feature parameter and second feature parameter of condensate gas well, the fisrt feature parameter include hole angle,
Surface tension, gas-liquid density, the critical Weber Number and drag coefficient of drop, the second feature parameter include gas deviation system
Number, oil pipe cross-sectional area, temperature and pressure；
According to the fisrt feature parameter, determine the condensate gas well takes liquid critical gas flow velocity；
Liquid critical gas flow velocity and the second feature parameter are taken according to described, determines that the condensate gas well takes liquid critical flow
Amount.
The technical solution provided by the embodiments of the present application more than is as it can be seen that the embodiment of the present application determines the of condensate gas well first
One characteristic parameter and second feature parameter, wherein fisrt feature parameter include hole angle, surface tension, gas-liquid density, drop
Critical Weber Number and drag coefficient, second feature parameter include Gaseous Z-factor, oil pipe cross-sectional area, temperature and pressure；Its
It is secondary to take liquid critical gas flow velocity according to what fisrt feature parameter determined condensate gas well；Then according to taking liquid critical gas flow velocity and the
Two characteristic parameters determine that condensate gas well takes liquid critical flow.Due to considering temperature, pressure, drag coefficient, surface tension comprehensively
The influence of liquid critical flow, therefore the condensate gas that the embodiment of the present application predicts are taken to condensate gas well with parameters such as critical Weber Numbers
Well to take liquid critical flow more accurate.
Brief description of the drawings
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, below will be to embodiment or existing
There is attached drawing needed in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments described in application, for those of ordinary skill in the art, in the premise of not making the creative labor property
Under, other attached drawings can also be obtained according to these attached drawings.In the accompanying drawings：
Fig. 1 is the flow chart for taking liquid critical flow Forecasting Methodology of condensate gas well in one embodiment of the application；
Fig. 2 is the drop force analysis schematic diagram of directional well in condensate gas well in one embodiment of the application；
Fig. 3 be one embodiment of the application under turbulent-flow conditions Reynolds number nonlinear fitting situation different from drag coefficient
Schematic diagram；
Fig. 4 is the structure diagram for taking liquid critical flow prediction meanss of condensate gas well in one embodiment of the application；
Fig. 5 is the structure diagram for taking liquid critical flow prediction meanss of condensate gas well in another embodiment of the application.
Embodiment
It is in order to make those skilled in the art better understand the technical solutions in the application, real below in conjunction with the application
The attached drawing in example is applied, the technical solution in the embodiment of the present application is clearly and completely described, it is clear that described implementation
Example is merely a part but not all of the embodiments of the present application.It is common based on the embodiment in the application, this area
Technical staff's all other embodiments obtained without creative efforts, should all belong to the application protection
Scope.
Before the embodiment of the present application is described, principle description first is carried out to the embodiment of the present application, in order to this area skill
The embodiment of the present application is more clearly understood in art personnel.
By taking the directional well of condensate gas well as an example, experiment shows, liquid phase is natural by being dispersed into droplet in directional well
Gas carries out pit shaft.Therefore, drop particle analysis theories can be based on, force analysis are carried out to directional well drop, such as Fig. 2 institutes
Show, since the flow velocity of liquid and gas is essentially identical, drop is from the frictional force of air-flow, therefore drop is subject to self gravitation (FG)、
Buoyancy (Fb), air-flow to the drag (D) of drop, the support force (N) of oil pipe and frictional force (f), (along oil pipe can only be taken by drop
Take ground out of, otherwise the component of drag D horizontal directions can not balance).When stress reaches balance to drop in the gas flow, it falls
Speed is u, and when gas flow rate is more than u, drop is carried over pit shaft, therefore u is directional well takes liquid critical gas flow velocity.
According to Newton's second law, the stress balance relation of drop can be represented with equation, along borehole wall direction and perpendicular to
The stress relational expression in pit shaft direction is respectively：
FbCos β+D=FG cosβ+f (1)
N+FbSin β=FG sinβ (2)
The equivalent diameter of drop sphere is d, therefore self gravitation (F suffered by dropG), buoyancy (Fb), air-flow is to the drag of drop
(D) it is：
β is hole angle in formula, and unit is degree；D is liquid-drop diameter, unit m；ρl, ρgRespectively liquid (water or oil) is gentle
The density of body, unit kg/m3；U takes liquid critical gas flow velocity, unit m/s for directional well；CdFor the drag coefficient of drop, nothing
Dimension；G is acceleration of gravity, unit m/s2。
According to friction law, oil pipe frictional force suffered by drop can use formula (4) to represent:
F=λ N (4)
λ is friction coefficient in formula, and dimensionless is related with Reynolds number to oil pipe roughness.
Simultaneous formula (2), formula (3) and formula (4), can try to achieve drop friction is：
In addition, drop is subject to make drop keep complete surface tension and cause the inertia of droplet rupture in the gas flow in itself
The effect of power, and the ratio between inertia force and surface tension are Weber number.Correlative study thinks that maximum gauge drop is carried in gas well
Pit shaft, then shaft bottom will not produce hydrops, and drop maximum gauge can be by critical Weber Number WecrTo determine, drop maximum gauge can table
It is shown as：
dm=Wecrσ/(ρgu2) (6)
In formula, WecrFor critical Weber Number, dimensionless；σ is surface tension, unit mN/m.
Formula (3), formula (5), formula (6) are substituted into formula (1), the general-purpose computations mould that directional well takes liquid critical gas flow velocity can be obtained
Type：
Wherein, σ is gas-liquid surface tension force, and friction coefficient (λ) is related to Reynolds number with the degree of roughness of tube wall, conventional oil pipe
Middle friction coefficient is between 0.01~0.1.Research shows that the different influences to taking liquid critical gas flow velocity of friction coefficient λ are micro-
Its is micro-, therefore λ can use 0.1, and then can try to achieve (wherein,)：
γ in formulagFor gas relative density, dimensionless.
Since above-mentioned model is theoretical based on drop particle, have ignored drop and drop in actual condensate gas well, tube wall it
Between influence each other.Research shows, according to gas-liquid mist flow switching criterion, is considering the situation of gas-liquid mist flow transformer effect
Under, it is bigger than particle the calculated results by 30% or so actually to take flow velocity.Therefore formula (8) is done in the embodiment of the present application and is repaiied as follows
Just：
The critical gas velocity for calculating gained is converted into the critical gas flows amount under mark condition：
Wherein, deviation factor is：
In above formula, QscTo take liquid critical flow, unit m3/d；A is oil pipe cross-sectional area, unit m2；P is pressure,
Unit is MPa；T is temperature, unit K；Z is Gaseous Z-factor, dimensionless.
From formula (9), formula (10) and formula (11) as can be seen that the parameter that calculating condensate gas well takes liquid critical flow includes hole deviation
Angle, critical Weber Number, drag coefficient, surface tension, gas-liquid density, Gaseous Z-factor, oil pipe sectional area, temperature and pressure.
In the case of given production, hole angle, oil pipe sectional area and fluid density are certain, and gas density and deviation factor are by pressure
Determined with temperature.Therefore, the accuracy that new model calculates depends primarily upon temperature, pressure, drag coefficient, surface tension and critical
Weber number, below illustrates it one by one：
First, temperature and pressure
Prediction condensate gas well takes liquid critical flow except needing accurate computation model, it is also necessary to knows maximum critical flow
Position in the wellbore.Flow quantity of taking at well head is all taken flow quantity by domestic and international Most scholars as the maximum in pit shaft,
But research shows, this can bring very big error to prediction, and maximum takes the optional position that flow quantity is likely to appear in pit shaft.Temperature
Degree changes with pressure with the difference of mine shaft depth, is an important factor for causing to take flow quantity differentiation in pit shaft.Base
The influence of hole angle, and condensate gas well meeting are not considered generally in the temperature of conventional water outlet gas well and the distributed model of pressure along pit shaft
There is oil-producing and grease with two kinds of operating modes of production, have relatively big difference with conventional water outlet gas well.Therefore, in temperature and pressure,
The embodiment of the present application is considered in hole angle and pit shaft to be influenced caused by oil gas water three phase, with the realistic well condition with condensate gas well
More match.It is specific as follows：
Distributed model of the condensate gas well pressure along well depth：
In formula, pwhFor well head pressure, unit MPa；H is well depth, unit m；D is pipe aperture, unit m；For
Barometric gradient, unit MPa/100m.
Distributed model of the condensate gas well temperature along well depth：
In formula,For temperature gradient, unit for DEG C/100m；twhFor wellhead temperature, teFor formation temperature, unit is DEG C；Ar
For relaxation distance, unit 1/m；cpFor specific heat at constant pressure, unit is J/ (kg DEG C)；η is Joule-Thomson effect coefficient, single
Position for DEG C/Pa；qwaxThe heat of fusion released for analysis wax, unit J/kg.
2nd, surface tension
Oil-producing or grease occurs with two kinds of operating modes of production in condensate gas well in process of production, therefore needs to consider air water surface
The gentle oil meter face tension force of power.Research shows that surface tension heel pressure is temperature dependent, and the computation model of air water surface tension is：
Wherein,
In formula, σgwFor air water surface tension, unit mN/m；σ (137.78) is the air water surface of 137.78 DEG C of temperature
Power, unit mN/m；σ (23.33) be 23.3 DEG C of temperature air water surface tension, unit mN/m.
The computation model of oil gas surface tension is：
In formula, σgoFor oil gas surface tension, unit mN/m；API is severe.
Found by qualitative research, the change of temperature is little to effect of surface tension, and the change of pressure is to surface tension
There is considerable influence, such as in 10MPa~60MPa pressure limits, oil gas surface tension changes in 0mN/m~1mN/m, and air water
Surface tension changes in 15mN/m~45mN/m；Under the conditions of identical temperature and pressure, oil gas surface tension is much smaller than air water table
Face tension force, therefore condensate is easier to carry out pit shaft than water flooding, takes liquid critical flow smaller.Therefore, using surface tension as
Definite value consideration is likely to result in large error, does not meet live actual production.
In view of condensate gas well in process of production, it may appear that oil-producing and grease are taken liquid in calculating and faced with two kinds of operating modes of production
, it is necessary to carry out separate computations with production well to oil-producing well and grease during boundary's flow：The surface tension of production wells, which calculates, can use formula
(16) calculate；Grease can use formula (14) to calculate with the surface tension of gas-producing well, because water flooding can take pit shaft out of by gas, coagulate
Condensate oil is with regard to that can be carried over pit shaft.
3rd, critical Weber Number
At present, many scholars are handled critical Weber Number as definite value both at home and abroad, but are studied research and shown that drop is broken
Critical Weber Number when broken generally fluctuates (being shown in Table 1) 5~60, it is seen that changing greatly for critical Weber Number, also result in condensation
The value range of liquid-drop diameter is wider in gas well, therefore being taken as definite value can cause to take liquid critical flow to calculate error larger.Cause
This, liquid-drop diameter needs to be calculated with formula (6) and accurate Weber number.
1 measuring critical Weber Number of table
4th, drag coefficient
The drag coefficient C of dropdIt is related to reynolds number Re.The situation of change of Reynolds number is more complicated, domestic and foreign scholars
Mainly it has been fitted (10 under laminar flow condition3≤Re≤2×105) Reynolds number and drag coefficient computation model, more classical is several
A model is as follows：
Clift＆Gauvin model of fit is
Graf model of fit is
Haider＆Levenspiel model of fit is
Then, Reza Barati utilize multiple-factor inheritance coding method, introduce hyperbolic tangent function tanh, are fitted mould
Type is:
It is square by contrasting the logarithmic deviation quadratic sums (SSLD) of different model of fit, logarithmic deviation in the embodiment of the present application
Root (RMSLD) and relative error (SRE) (being shown in Table 2), it can be seen that Reza Barati models are significantly improved in precision, therefore
In some embodiments of the application, the model can be used under laminar flow condition.
The different model accuracy contrasts of table 2
From standard resistance curve, (2 × 10 under turbulent-flow conditions5≤Re≤106), drag coefficient is with Reynolds number
Change fluctuation is larger, therefore drag coefficient takes definite value error larger.Therefore, Nonlinear Quasi can be carried out to the relevant experimental data of turbulent flow
Close, see the table below shown in 3：
Reynolds number and drag coefficient relation nonlinear fitting under 3 turbulent-flow conditions of table
From table 3 and Fig. 3 it will be evident that the R side of cube equation is 0.940, illustrate that the degree of fitting of this model is preferable；
F statistics are 25.902, have passed through F inspections, have illustrated that regression model effect is preferable.Therefore, it is turbulent flow C to take cubic modeld(solid)
With the relational model of Re, equation represents as follows：
Cd(solid)=-3.316 × 10-18Re3+7.3×10-12Re2-4.918×10-6Re+1.143 (21)
Since formula (20) and formula (21) are obtained by being fitted rigid spheres drag coefficient, and drop and solid particle are not
Together, internal flow is caused because drop can be subject to airflow influence during exercise, causes the drag coefficient ratio of drop
The drag coefficient of solid particle is small.To solve this problem, can be modified by following formula：
In formula, Cd(droplet)For the drag coefficient of drop, Cd(solid)For the drag coefficient of rigid spheres, μlGlued for liquid
Degree, μgFor gas viscosity.
It can be seen from the above that under laminar flow condition, the drag coefficient of drop can be determined by formula (20) and formula (22)；And
Under turbulent-flow conditions, the drag coefficient of drop can be determined by formula (21) and formula (22), so as to obtain the drag force of drop
Coefficient, is consistent with the drag coefficient of drop reality.
Refering to what is shown in Fig. 1, on the basis of above description, the condensate gas well of the embodiment of the present application to take liquid critical flow pre-
Survey method, may comprise steps of：
S101, the fisrt feature parameter and second feature parameter for determining condensate gas well, the fisrt feature parameter include well
Oblique angle, surface tension, gas-liquid density, the critical Weber Number and drag coefficient of drop, it is inclined that the second feature parameter includes gas
Poor coefficient, oil pipe cross-sectional area, temperature and pressure.
In the application some embodiments, the drag coefficient of the drop obtains in the following manner：
The drag coefficient of rigid spheres corresponding with drop in condensate gas well is determined first；Then according to the rigid spheres
Drag coefficient determine the drag coefficient of the drop.Specifically refer to the above-mentioned description as described in drag coefficient part.
S102, according to the fisrt feature parameter, determine the condensate gas well takes liquid critical gas flow velocity.
In the application some embodiments, it is described according to the characteristic parameter determine the condensate gas well to take liquid critical
Gas flow rate, can determine according to above-mentioned formula (9).
S103, take liquid critical gas flow velocity and the second feature parameter according to, determines that the condensate gas well takes liquid
Critical flow.
In the application some embodiments, liquid critical gas flow velocity and second feature ginseng are taken described in the basis
Number, determines that the condensate gas well takes liquid critical flow, can be determined according to above-mentioned formula (10).
The details of above steps refers to above-mentioned principle description, and details are not described herein.It is although in addition, above-described
Process flow includes the multiple operations occurred with particular order, it should however be appreciated that understand, these processes can include it is more or
Less operation, these operations sequentially can be performed or performed parallel (such as using parallel processor or multi-thread environment).
One exemplary embodiment of the application is described below.
The physical parameter of Xinjiang block condensate gas well is as follows：Condensate relative density is 0.83~0.87, water flooding phase
It is 1.11~1.19 to density, natural gas relative density is 0.61~0.73, oil pressure 8MPa~36MPa, pipe aperture 62mm,
Hole angle is 30 °~90 °.The condensate gas well that scholar releases before applying respectively takes liquid critical flow and calculates model and the application reality
Apply example and carry out hydrops prediction, and compared with the hydrops situation of pit shaft reality, contrast situation see the table below shown in 4.
As shown in Table 4, the macro-forecast precision of the prosperous models of Yuan Zhi is 68%, and wherein the precision of prediction of hydrops well is 94%,
Precision of prediction without hydrops well is only 43%.The model only accounts for operating mode of the grease with production, and minimum in pit shaft is taken aquatic products
Tolerance takes liquid critical flow as condensate gas well.Under the same terms, take water ratio take oil it is increasingly difficult.Actual aerogenesis in hydrops well
Amount takes flow quantity less than theoretical, whether production wells or the same gas-producing well of grease, and what which calculated takes liquid critical flow
Amount is all not less than theoretical flow quantity of taking, therefore the precision of the model prediction hydrops well is high；Without actual gas production in hydrops well
Take flow quantity higher than theoretical, the grease which calculates with gas-producing well take flow quantity and theory take flow quantity it is essentially identical from
And predict accurate, but the production wells that calculates of the model takes flow quantity and takes flow quantity much larger than theory, therefore also greater than reality
Gas production causes the precision of prediction of not hydrops well low so as to prediction error.
The model Zhou Dynasty and Li Zhi flat-die type macro-forecasts precision are 50% or so, wherein the precision of prediction of hydrops well does not exceed
87%, but the precision of prediction of hydrops well is only 19%.The two models are derived based on straight well, do not consider well
The influence at oblique angle, the and because fluid-carrying capability of straight well is more than directional well fluid-carrying capability, thus model calculate to take flow quantity small
Flow quantity is taken in theoretical.Actual gas production does not take flow quantity higher than theory in hydrops well, therefore the model prediction not hydrops well
Precision is high；And theory takes liquid throughput and is higher than actual gas production in hydrops well, if the flow quantity of taking that model calculates is produced less than actual
Tolerance, prediction produces mistake, so as to cause the precision of prediction of hydrops well low.And the new model that the embodiment of the present application proposes is whether
To hydrops well or the precision of prediction of hydrops well has not exceeded 93%, is suitable for the hydrops prediction of the Xinjiang block, to solidifying yet
The prediction that gassing well takes liquid critical flow plays certain directive significance and practical value.
4 condensate gas well of table takes the contrast of flow quantity model prediction accuracy
In fact, being shown by the applied analysis to each field case, the precision of prediction of the embodiment of the present application exceedes
90%, compared with condensate gas well takes liquid critical flow common calculation model, precision of prediction improves 26%~41%, i.e. the application
What embodiment can be more accurately predicted condensate gas well takes liquid critical flow, so as to improve the ultimate recovery of condensate gas well.
Shown in Figure 4, a kind of condensate gas well of the embodiment of the present application is taken liquid critical flow prediction meanss and can be included：
Characteristic parameter determining module 41, is determined for the fisrt feature parameter and second feature parameter of condensate gas well,
The fisrt feature parameter includes hole angle, surface tension, gas-liquid density, the critical Weber Number and drag coefficient of drop, described
Second feature parameter includes Gaseous Z-factor, oil pipe cross-sectional area, temperature and pressure；
Critical flow velocity determining module 42, can be used for, according to the fisrt feature parameter, determining taking for the condensate gas well
Liquid critical gas flow velocity；
Critical flow determining module 43, can be used for taking liquid critical gas flow velocity and second feature ginseng according to
Number, determines that the condensate gas well takes liquid critical flow.
Refering to what is shown in Fig. 5, the embodiment of the present application another kind condensate gas well is taken liquid critical flow prediction meanss and can be included
Memory, processor and the computer program being stored on the memory, the computer program are transported by the processor
Following steps are performed during row：
Determine the fisrt feature parameter and second feature parameter of condensate gas well, the fisrt feature parameter include hole angle,
Surface tension, gas-liquid density, the critical Weber Number and drag coefficient of drop, the second feature parameter include gas deviation system
Number, oil pipe cross-sectional area, temperature and pressure；
According to the fisrt feature parameter, determine the condensate gas well takes liquid critical gas flow velocity；
Liquid critical gas flow velocity and the second feature parameter are taken according to described, determines that the condensate gas well takes liquid critical flow
Amount.
The device of the above embodiments of the present application is corresponding with the method for above-described embodiment, therefore, is related to the above-mentioned reality of the application
The device details of example is applied, the method for referring to above-described embodiment, details are not described herein.
For convenience of description, it is divided into various units during description apparatus above with function to describe respectively.Certainly, this is being implemented
The function of each unit can be realized in same or multiple softwares and/or hardware during application.
The present invention be with reference to according to the method for the embodiment of the present invention, the flow of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that it can be realized by computer program instructions every first-class in flowchart and/or the block diagram
The combination of flow and/or square frame in journey and/or square frame and flowchart and/or the block diagram.These computer programs can be provided
The processors of all-purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices is instructed to produce
A raw machine so that the instruction performed by computer or the processor of other programmable data processing devices, which produces, to be used in fact
The device for the function of being specified in present one flow of flow chart or one square frame of multiple flows and/or block diagram or multiple square frames.
These computer program instructions, which may also be stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that the instruction being stored in the computer-readable memory, which produces, to be included referring to
Make the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one square frame of block diagram or
The function of being specified in multiple square frames.
These computer program instructions can be also loaded into computer or other programmable data processing devices so that counted
Series of operation steps is performed on calculation machine or other programmable devices to produce computer implemented processing, thus in computer or
The instruction performed on other programmable devices is provided and is used for realization in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in a square frame or multiple square frames.
In a typical configuration, computing device includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include computer-readable medium in volatile memory, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only storage (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer-readable instruction, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase transition internal memory (PRAM), static RAM (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only storage (ROM), electric erasable
Programmable read only memory (EEPROM), fast flash memory bank or other memory techniques, read-only optical disc read-only storage (CD-ROM),
Digital versatile disc (DVD) or other optical storages, magnetic cassette tape, the storage of tape magnetic rigid disk or other magnetic storage apparatus
Or any other non-transmission medium, the information that can be accessed by a computing device available for storage.According in the embodiment of the present application
Define, computer-readable medium does not include temporary computer readable media (transitory media), such as data-signal of modulation
And carrier wave.
It should also be noted that, term " comprising ", "comprising" or its any other variant are intended to nonexcludability
Comprising so that process, method, commodity or equipment including a series of elements not only include those key elements, but also wrapping
Include other elements that are not explicitly listed, or further include for this process, method, commodity or equipment it is intrinsic will
Element.In the absence of more restrictions, the key element limited by sentence "including a ...", it is not excluded that wanted including described
Also there are other identical element in the process of element, method, commodity or equipment.
It will be understood by those skilled in the art that embodiments herein can be provided as method, system or computer program product.
Therefore, the application can be using the embodiment in terms of complete hardware embodiment, complete software embodiment or combination software and hardware
Form.Deposited moreover, the application can use to can use in one or more computers for wherein including computer usable program code
The shape for the computer program product that storage media is implemented on (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
Formula.
The application can be described in the general context of computer executable instructions, such as program
Module.Usually, program module includes performing particular task or realizes routine, program, object, the group of particular abstract data type
Part, data structure etc..The application can also be put into practice in a distributed computing environment, in these distributed computing environment, by
Task is performed and connected remote processing devices by communication network.In a distributed computing environment, program module can be with
In the local and remote computer-readable storage medium including storage device.
Each embodiment in this specification is described by the way of progressive, identical similar portion between each embodiment
Divide mutually referring to what each embodiment stressed is the difference with other embodiment.It is real especially for system
For applying example, since it is substantially similar to embodiment of the method, so description is fairly simple, related part is referring to embodiment of the method
Part explanation.
The foregoing is merely embodiments herein, is not limited to the application.For those skilled in the art
For, the application can have various modifications and variations.All any modifications made within spirit herein and principle, be equal
Replace, improve etc., it should be included within the scope of claims hereof.
Claims (12)
1. a kind of condensate gas well takes liquid critical flow Forecasting Methodology, it is characterised in that including：
Determine the fisrt feature parameter and second feature parameter of condensate gas well, the fisrt feature parameter includes hole angle, surface
Tension force, gas-liquid density, the critical Weber Number and drag coefficient of drop, the second feature parameter include Gaseous Z-factor, oil
Pipe cross-sectional area, temperature and pressure；
According to the fisrt feature parameter, determine the condensate gas well takes liquid critical gas flow velocity；
Liquid critical gas flow velocity and the second feature parameter are taken according to described, determines that the condensate gas well takes liquid critical flow.
2. condensate gas well as claimed in claim 1 takes liquid critical flow Forecasting Methodology, it is characterised in that described in the basis
What characteristic parameter determined the condensate gas well takes liquid critical gas flow velocity, including：
Liquid critical gas flow velocity is taken according to what the following formula determined the condensate gas well：
<mrow>
<mi>u</mi>
<mo>=</mo>
<mn>2.47</mn>
<mroot>
<mfrac>
<mrow>
<mn>0.1</mn>
<msub>
<mi>We</mi>
<mrow>
<mi>c</mi>
<mi>r</mi>
</mrow>
</msub>
<mi>s</mi>
<mi>i</mi>
<mi>n</mi>
<mi>&beta;</mi>
<mo>+</mo>
<msub>
<mi>We</mi>
<mrow>
<mi>c</mi>
<mi>r</mi>
</mrow>
</msub>
<mi>c</mi>
<mi>o</mi>
<mi>s</mi>
<mi>&beta;</mi>
</mrow>
<msub>
<mi>C</mi>
<mi>d</mi>
</msub>
</mfrac>
<mn>4</mn>
</mroot>
<mrow>
<mo>(</mo>
<mroot>
<mfrac>
<mrow>
<mi>&sigma;</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>&rho;</mi>
<mi>l</mi>
</msub>
<mo>-</mo>
<msub>
<mi>&rho;</mi>
<mi>g</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<msup>
<msub>
<mi>&rho;</mi>
<mi>g</mi>
</msub>
<mn>2</mn>
</msup>
</mrow>
</mfrac>
<mn>4</mn>
</mroot>
<mo>)</mo>
</mrow>
</mrow>
Wherein, u takes liquid critical gas flow velocity, We for condensate gas wellcrFor the critical Weber Number of drop, β is hole angle, CdFor liquid
The drag coefficient of drop, ρlFor fluid density, ρgFor gas density, σ is gas-liquid surface tension force.
3. condensate gas well as claimed in claim 1 takes liquid critical flow Forecasting Methodology, it is characterised in that described in the basis
Liquid critical gas flow velocity and the second feature parameter are taken, determines that the condensate gas well takes liquid critical flow, including：
Determine that the condensate gas well of the condensate gas well takes liquid critical flow according to the following formula：
<mrow>
<msub>
<mi>Q</mi>
<mrow>
<mi>s</mi>
<mi>c</mi>
</mrow>
</msub>
<mo>=</mo>
<mn>2.5</mn>
<mo>&times;</mo>
<msup>
<mn>10</mn>
<mn>8</mn>
</msup>
<mfrac>
<mrow>
<mi>A</mi>
<mi>p</mi>
<mi>u</mi>
</mrow>
<mrow>
<mi>Z</mi>
<mi>T</mi>
</mrow>
</mfrac>
</mrow>
Wherein, QscLiquid critical flow is taken for the condensate gas well, A is oil pipe cross-sectional area, and p is pressure, and u is taking for condensate gas well
Liquid critical gas flow velocity, Z are Gaseous Z-factor, and T is temperature.
4. condensate gas well as claimed in claim 1 takes liquid critical flow Forecasting Methodology, it is characterised in that the drop drags
Force coefficient obtains in the following manner：
Determine the drag coefficient of rigid spheres corresponding with drop in condensate gas well；
The drag coefficient of the drop is determined according to the drag coefficient of the rigid spheres.
5. condensate gas well as claimed in claim 4 takes liquid critical flow Forecasting Methodology, it is characterised in that in laminar flow condition
Under, the drag coefficient of the rigid spheres is determined by the following formula：
<mrow>
<msub>
<mi>C</mi>
<mrow>
<mi>d</mi>
<mrow>
<mo>(</mo>
<mrow>
<mi>s</mi>
<mi>o</mi>
<mi>l</mi>
<mi>i</mi>
<mi>d</mi>
</mrow>
<mo>)</mo>
</mrow>
</mrow>
</msub>
<mo>=</mo>
<mn>5.4856</mn>
<mo>&times;</mo>
<msup>
<mn>10</mn>
<mn>9</mn>
</msup>
<mi>tanh</mi>
<mrow>
<mo>(</mo>
<mfrac>
<mrow>
<mn>4.377</mn>
<mo>&times;</mo>
<msup>
<mn>10</mn>
<mrow>
<mo>-</mo>
<mn>9</mn>
</mrow>
</msup>
</mrow>
<mi>Re</mi>
</mfrac>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mn>0.071</mn>
<mi>tanh</mi>
<mrow>
<mo>(</mo>
<mfrac>
<mn>700.657</mn>
<mi>Re</mi>
</mfrac>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mn>0.389</mn>
<mi>tanh</mi>
<mrow>
<mo>(</mo>
<mfrac>
<mn>74.154</mn>
<mi>Re</mi>
</mfrac>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mn>0.12</mn>
<mi>tanh</mi>
<mrow>
<mo>(</mo>
<mfrac>
<mn>7429.1</mn>
<mi>Re</mi>
</mfrac>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mn>1.717</mn>
<mi>tanh</mi>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<mrow>
<mi>Re</mi>
<mo>+</mo>
<mn>2.33448</mn>
</mrow>
</mfrac>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mn>0.4744</mn>
</mrow>
Wherein, Cd(solid)For the drag coefficient of drop, Re is Reynolds number, and tanh is hyperbolic tangent function.
6. condensate gas well as claimed in claim 4 takes liquid critical flow Forecasting Methodology, it is characterised in that in turbulent-flow conditions
Under, the drag coefficient of the rigid spheres is determined by the following formula：
Cd(solid)=-3.316 × 10-18Re3+7.3×10-12Re2-4.918×10-6Re+1.143
Wherein, Cd(solid)For the drag coefficient of drop, Re is Reynolds number.
7. take liquid critical flow Forecasting Methodology such as claim 4 to 6 any one of them condensate gas well, it is characterised in that institute
The drag coefficient that the drop is determined according to the drag coefficient of the rigid spheres is stated, including：
According to formulaDetermine the drag coefficient of the drop；
Wherein, Cd(droplet)For the drag coefficient of drop, Cd(solid)For the drag coefficient of rigid spheres, μlFor liquid viscosity, μgFor
Gas viscosity, Re are Reynolds number.
8. condensate gas well as claimed in claim 1 takes liquid critical flow Forecasting Methodology, it is characterised in that in oil-producing operating mode
Under, the surface tension is determined by the following formula：
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<msub>
<mi>&sigma;</mi>
<mrow>
<mi>g</mi>
<mi>o</mi>
</mrow>
</msub>
<mo>=</mo>
<mo>&lsqb;</mo>
<mn>42.4</mn>
<mo>-</mo>
<mn>0.047</mn>
<mrow>
<mo>(</mo>
<mn>1.8</mn>
<mi>t</mi>
<mo>-</mo>
<mn>459.67</mn>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mn>0.267</mn>
<mi>A</mi>
<mi>P</mi>
<mi>I</mi>
<mo>&rsqb;</mo>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mn>0.10152</mn>
<mi>p</mi>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>A</mi>
<mi>P</mi>
<mi>I</mi>
<mo>=</mo>
<mrow>
<mo>(</mo>
<mn>141.5</mn>
<mo>/</mo>
<msub>
<mi>&gamma;</mi>
<mi>g</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mn>131.5</mn>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
Wherein, σgoFor oil gas surface tension, t is temperature, and API is severe, and p is pressure, γgFor gas relative density.
9. condensate gas well as claimed in claim 1 takes liquid critical flow Forecasting Methodology, it is characterised in that produces work together in grease
Under condition, the surface tension is determined by the following formula：
<mrow>
<msub>
<mi>&sigma;</mi>
<mrow>
<mi>g</mi>
<mi>w</mi>
</mrow>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mn>1.8</mn>
<mrow>
<mo>(</mo>
<mn>410.9</mn>
<mo>-</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
</mrow>
<mn>206</mn>
</mfrac>
<mo>&lsqb;</mo>
<mi>&sigma;</mi>
<mrow>
<mo>(</mo>
<mn>23.33</mn>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>&sigma;</mi>
<mrow>
<mo>(</mo>
<mn>137.78</mn>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
<mo>+</mo>
<mi>&sigma;</mi>
<mrow>
<mo>(</mo>
<mn>137.78</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein,σgwFor air water surface tension, t is temperature, and σ (23.33) is temperature
Air water surface tension at 23.33 DEG C, σ (137.78) are air water surface tension of the temperature at 137.78 DEG C, and p is pressure.
10. condensate gas well as claimed in claim 1 takes liquid critical flow Forecasting Methodology, it is characterised in that the gas is inclined
Poor coefficient is determined by the following formula：
<mrow>
<mi>Z</mi>
<mo>=</mo>
<mn>1</mn>
<mo>/</mo>
<mrow>
<mo>(</mo>
<mfrac>
<mrow>
<mn>1</mn>
<mo>+</mo>
<mn>5.072</mn>
<mo>&times;</mo>
<msup>
<mn>10</mn>
<mn>6</mn>
</msup>
<mo>&times;</mo>
<mrow>
<mo>(</mo>
<mi>p</mi>
<mo>+</mo>
<mn>0.098</mn>
<mo>)</mo>
</mrow>
<mo>&times;</mo>
<msup>
<mn>10</mn>
<mrow>
<mn>1.785</mn>
<msub>
<mi>&gamma;</mi>
<mi>g</mi>
</msub>
</mrow>
</msup>
</mrow>
<msup>
<mrow>
<mo>(</mo>
<mi>T</mi>
<mo>+</mo>
<mn>273.15</mn>
<mo>)</mo>
</mrow>
<mn>3.875</mn>
</msup>
</mfrac>
<mo>)</mo>
</mrow>
</mrow>
Wherein, Z is Gaseous Z-factor, and p is pressure, and T is temperature, γgFor gas relative density.
11. a kind of condensate gas well takes liquid critical flow prediction meanss, it is characterised in that including：
Characteristic parameter determining module, for determining the fisrt feature parameter and second feature parameter of condensate gas well, described first is special
Levying parameter includes hole angle, surface tension, gas-liquid density, the critical Weber Number and drag coefficient of drop, the second feature ginseng
Number includes Gaseous Z-factor, oil pipe cross-sectional area, temperature and pressure；
Critical flow velocity determining module, for according to the fisrt feature parameter, determine the condensate gas well to take liquid critical gas
Flow velocity；
Critical flow determining module, for taking liquid critical gas flow velocity and the second feature parameter according to, determines described
Condensate gas well takes liquid critical flow.
12. a kind of condensate gas well takes liquid critical flow prediction meanss, including memory, processor and it is stored in described deposit
Computer program on reservoir, it is characterised in that the computer program performs following steps when being run by the processor：
Determine the fisrt feature parameter and second feature parameter of condensate gas well, the fisrt feature parameter includes hole angle, surface
Tension force, gas-liquid density, the critical Weber Number and drag coefficient of drop, the second feature parameter include Gaseous Z-factor, oil
Pipe cross-sectional area, temperature and pressure；
According to the fisrt feature parameter, determine the condensate gas well takes liquid critical gas flow velocity；
Liquid critical gas flow velocity and the second feature parameter are taken according to described, determines that the condensate gas well takes liquid critical flow.
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| CN108763657A (en) * | 2018-05-04 | 2018-11-06 | 中国石油天然气集团有限公司 | Horizontal gas well continuously takes liquid critical flow and determines method and device |
| CN112031741A (en) * | 2020-08-28 | 2020-12-04 | 中石化石油工程技术服务有限公司 | Method for determining continuous critical liquid carrying flow rate of large-gradient gas well in east China sea |
| CN113516326A (en) * | 2020-04-10 | 2021-10-19 | 中国石油化工股份有限公司 | Method for evaluating critical liquid discharge capacity of shale gas horizontal well |
| CN113836680A (en) * | 2021-11-25 | 2021-12-24 | 德仕能源科技集团股份有限公司 | Automatic filling method and technology for petroleum oil pipe |
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| CN112031741B (en) * | 2020-08-28 | 2024-04-30 | 中石化石油工程技术服务有限公司 | Method for determining continuous critical liquid carrying flow rate of high-inclination gas well in east China sea area |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108763657A (en) * | 2018-05-04 | 2018-11-06 | 中国石油天然气集团有限公司 | Horizontal gas well continuously takes liquid critical flow and determines method and device |
| CN113516326A (en) * | 2020-04-10 | 2021-10-19 | 中国石油化工股份有限公司 | Method for evaluating critical liquid discharge capacity of shale gas horizontal well |
| CN113931621A (en) * | 2020-07-14 | 2022-01-14 | 中国石油天然气股份有限公司 | Method and device for determining gas well accumulated liquid information and storage medium |
| CN113931621B (en) * | 2020-07-14 | 2023-08-22 | 中国石油天然气股份有限公司 | Method, device and storage medium for determining gas well hydrops information |
| CN112031741A (en) * | 2020-08-28 | 2020-12-04 | 中石化石油工程技术服务有限公司 | Method for determining continuous critical liquid carrying flow rate of large-gradient gas well in east China sea |
| CN112031741B (en) * | 2020-08-28 | 2024-04-30 | 中石化石油工程技术服务有限公司 | Method for determining continuous critical liquid carrying flow rate of high-inclination gas well in east China sea area |
| CN113836680A (en) * | 2021-11-25 | 2021-12-24 | 德仕能源科技集团股份有限公司 | Automatic filling method and technology for petroleum oil pipe |
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