CN115906695A - Multi-information fusion production profile well logging interpretation optimization method - Google Patents
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Abstract
The invention discloses a multi-information fusion production profile well logging interpretation optimization method, and relates to the technical field of oil well oil-water yield prediction. The method comprises the steps of establishing an optimized quantitative calculation method for the average speed of a shaft and the apparent speed of each phase of oil and water influenced by factors such as the response of a coupling instrument, the fluid property, the reservoir characteristics and the like based on seven-parameter production profile logging information of a medium-high production well or the collecting umbrella production profile logging information of a low-production well, considering the fluid property, the reservoir characteristic parameters and the self influence of a logging instrument, and based on shaft hydromechanics and a reservoir oil-water two-phase seepage theory, so as to realize the accurate prediction of the oil-water yield of each production layer. The invention comprehensively considers the influence of multiple factors, eliminates the limitations of self measurement error of a monitoring instrument and single evaluation of single-layer yield of the production well by means of shaft monitoring information to the maximum extent, provides a more accurate new method for dynamic prediction of single-layer production of the oil well, and effectively supports optimization and adjustment of water exploration and control of the oil well and a development scheme at the next stage.
Description
Technical Field
The invention relates to a multi-information fusion production profile well logging interpretation optimization method, which mainly aims at quantitatively predicting oil-water yield of a production zone of an oil well. By combining the information of production profile logging information, fluid properties, reservoir characteristic parameters, oil well wellhead production dynamics and the like, starting from the theoretical analysis of wellbore hydrodynamics and reservoir oil-water two-phase seepage, an optimized quantitative interpretation model of the production profile logging information considering the fluid properties, the flow of the wellbore oil-water two-phase fluid and the reservoir oil-water two-phase seepage is established, the accurate prediction of the oil well single-layer oil-water yield is realized, and the method is an accurate and reliable interpretation method of the production profile logging information.
Background
The accurate evaluation of the oil-water yield of each production zone of the oil well is the key basis for guiding the water finding and controlling of the oil well and the optimization and adjustment of the development scheme of the next stage. The current oil well production profile logging method is limited by the single well production divided into the conventional seven-parameter production profile logging method suitable for medium-high production wells (the total oil-water production is higher than 30 square/day) and the flow-collecting umbrella type production profile logging method suitable for low production wells (the total oil-water production is 0-30 square/day). The conventional seven-parameter production profile logging instrument can simultaneously record turbine FLOW (FLOW), fluid Temperature (TEMP), fluid pressure (SPT), water holding capacity (HYDR), fluid Density (FDEN), magnetic signal (CCL) and natural Gamma Ray (GR) information when being put down a well once; the collecting umbrella type production profile logging instrument can record point-measuring collecting umbrella Flow (FLDC), point-measuring water retention rate (HDDC) and point-measuring fluid density (FDDC) information when going down a well once, and different processing methods are correspondingly selected for different monitoring data to finish quantitative interpretation. Magnetic signals (CCL) and natural Gamma (GR) in the conventional seven-parameter production profile logging data are mainly used for depth correction of curve data; the fluid Temperature (TEMP) and the fluid pressure (SPT) are used for supporting the conversion of the physical parameters of the oil-water two-phase fluid, so that the accurate conversion of the underground and ground conditions of the oil-water two-phase fluid is realized; the method can be used for calculating the total average velocity of oil-water two-phase fluid in a shaft based on the FLOW information of the turbine, the water holding rate (HYDR) and the Fluid Density (FDEN) information are used for calculating the oil-water phase holding rate, and the apparent velocity of the oil-water phase fluid can be calculated based on the combination of the oil-water phase fluid holding rate and the total average velocity and a slip model. Aiming at the processing and interpretation of the flow-collecting umbrella type production profile well logging information, on the basis of point logging information processing, the processing and interpretation of the production profile well logging information is supported by a physical experiment plate method to realize the calculation of the apparent velocity of each phase fluid of oil and water. On the basis of the calculation of the phase separation apparent velocity of each phase of fluid in the shaft, the quantitative prediction of the oil-water yield of each production layer of the oil well can be realized on the basis of the mass conservation law and the pipe constant.
In the application process of the actual production profile logging information, the requirement of oil-water yield of each production zone on the data quality is high by only depending on the production profile logging information, and when the monitoring data quality is good and the interference between production zones is small, the single-layer oil-water yield prediction precision is high; when the fluid property of the oil well is complex, the interference between production layers is obvious or the monitor is obviously influenced by the environment, the error of predicting the single-layer yield of the oil well by only depending on the logging information of the production profile is extremely large, and the prediction result can not meet the actual production requirement of a mine field. Therefore, the problem that the skilled person needs to solve urgently is how to make up the limitation of predicting the single-layer production of the oil well by only depending on the production profile logging information and provide a new feasible solution for obtaining more accurate single-layer production dynamics of the oil well.
Disclosure of Invention
The invention aims to provide a multi-information fusion production profile well logging interpretation optimization method, and the interpretation result obtained by the method can accurately reflect the oil and water yield of each production layer of a production well, clearly indicate the primary and secondary production layers and the water outlet position of the well, and further lay a foundation for efficient development of the oil field.
In order to achieve the above technical objects, the present invention provides the following technical solutions.
A multi-information fusion production profile well logging interpretation optimization method sequentially comprises the following steps:
(1) Dividing a production profile well logging interpretation layer based on well logging information and a shaft structure;
(2) Calculating the average fluid velocity of each interpretation layer of the production profile logging;
(3) Calculating the apparent velocity of the oil phase fluid and the apparent velocity of the water phase fluid of each interpretation layer based on the average fluid velocity of each interpretation layer;
(4) Constructing an optimized processing and interpretation objective function of the logging data of the production profile;
(5) And solving the optimal value of the optimization processing interpretation objective function to obtain a logging interpretation result of the production profile.
The following will specifically explain the steps:
(1) Dividing a production profile logging interpretation layer based on logging information and a shaft structure, and specifically comprising:
dividing the oil well into an oil well for developing a seven-parameter production profile logging and an oil well for developing a collector umbrella production profile logging according to the yield of the oil well;
aiming at an oil well for developing seven-parameter production profile logging, selecting a curve response stable section between two production layers to divide an explanation layer based on turbine flow, water holdup and fluid density curve response characteristics;
aiming at an oil well for carrying out manifold umbrella production profile well logging, an interpretation layer is divided at a point-measuring position between two production layers, and the number of the interpretation layers is matched with that of the production layers.
(2) Calculating the average fluid velocity of each interpretation layer of the production profile logging based on the flow logging data, which specifically comprises the following steps:
aiming at an oil well for developing seven-parameter production profile well logging, the method calculates each interpretation layer by utilizing an up-down subsection turbine rotating speed and cable speed intersection analysis method considering the influence of positive and negative rotation of a turbine and starting speedThe specific expression of the average fluid velocity of (2) is as follows:
in the formula, for an oil well that developed a seven parameter production profile log: v. of m,k Average fluid velocity for the kth interpretation layer; v. of a,k+ Calculating the apparent fluid velocity for the kth interpretation layer turbine in forward rotation; v. of th+ The starting speed of the turbine in forward rotation; v. of a,k- Calculating the apparent fluid velocity when the turbine of the kth interpretation layer reverses; v. of th- The starting speed when the turbine rotates reversely; c v,k Velocity profile correction coefficients for the kth interpretation layer;
preferably, before calculating the average fluid velocity of each interpretation layer, the method further comprises the step of calculating the starting velocity v when the turbine rotates forwards th+ And the starting speed v at the time of turbine reversal th- And (6) carrying out correction.
Aiming at an oil well for carrying out manifold umbrella production profile well logging, the average fluid speed of each interpretation layer is calculated by averaging the response data of the point-to-point turbine measurement and combining a physical experiment plate interpolation method.
(3) Calculating the apparent velocity of the oil phase fluid and the apparent velocity of the water phase fluid of each interpretation layer based on the average fluid velocity of each interpretation layer, and specifically comprises the following steps:
for wells that develop seven parameter production profile logs: according to the average fluid velocity of each interpretation layer, combining with a slippage model to calculate and obtain the apparent velocity of the oil phase fluid and the apparent velocity of the water phase fluid of each interpretation layer of the production profile logging, the concrete formula is,
in the formula, for an oil well that developed a seven parameter production profile log: v. of so,k Apparent velocity of the oil phase fluid for the kth explaining layer; v. of sw,k Is the kth solutionThe apparent velocity of the water phase fluid of the release layer; v. of m,k Average fluid velocity for the kth interpretation layer; CPS w The response value of the water holdup meter under the condition of full water is shown; CPS m,k Logging response values for the k interpretation layer water holdup; CPS o The response value of the water holdup meter under the full oil condition is shown; v. of sow,k The slippage rate of the oil phase relative to the water phase is explained for the k < th > time;
the slippage speed of the oil phase relative to the water phase in the kth interpretation layer is specifically calculated by the following formula:
in the formula, ρ o,k Logging the oil phase density of the kth interpretation zone for the production profile; rho w,k Logging the density of the water phase of the kth interpretation zone for the production profile;
aiming at an oil well for developing the collector parachute production profile logging, the oil content and the water content of each interpretation layer are obtained by adopting physical experiment plate interpolation, and the apparent velocity of oil phase fluid and the apparent velocity of water phase fluid of each interpretation layer of the production profile logging are obtained by calculation:
v' so,k ＝v' m,k ·C o,k
v' sw,k ＝v' m,k ·C w,k
in the formula, aiming at the oil well for developing the flow-collecting umbrella production profile well logging: v' so,k Apparent velocity of the oil phase fluid for the kth explaining layer; v' sw,k The apparent velocity of the water phase fluid of the kth interpretation layer; v' m,k Average fluid velocity for the kth interpretation layer; c w,k Is the water content of the kth interpretation layer; c o,k The oil content of the k-th interpretation layer.
(4) The method comprises the following steps of constructing an optimization processing interpretation objective function of the logging data of the production profile, wherein the optimization processing interpretation objective function comprises the following specific steps:
for an oil well that developed a seven parameter production profile log:
respectively calculating the oil yield Q of the corresponding production layer according to the apparent velocity of the oil phase fluid and the apparent velocity of the water phase fluid of each interpretation layer o,n And water yield Q w,n ；
Q o,n ＝0.036·π·(D 2 -d 2 )·(v so,k -v so,k+1 )
Q w,n ＝0.036·π·(D 2 -d 2 )·(v sw,k -v sw,k+1 )
In the formula, Q o,n The oil production of the nth production zone; q w,n Water production of the nth producing zone; d is the inner diameter of the oil pipe or the sleeve; d is the outer diameter m of the production profile logging instrument; n =0, 1, 2 \8230; v. of so,k Apparent velocity of the oil phase fluid for the kth interplanar phase; v. of so,k+1 The apparent velocity of the oil phase in the k +1 th interpretation layer; v. of sw,k The apparent velocity of the aqueous phase for the kth interpretation layer; v. of sw,k+1 The apparent velocity of the aqueous phase of the k +1 th interpretation layer; the nth generation layer is positioned between the kth interpretation layer and the (k + 1) th interpretation layer;
according to the oil production Q of the corresponding production zone o,n And water yield Q w,n Calculating the predicted oil yield f of the corresponding production zone o,n And predicting water production rate f w,n ；
Based on the basic theory of oil reservoir seepage mechanics and in combination with the capacity equation, calculating the oil phase yield Q of the single-layer production layer op,n And aqueous phase yield Q wp,n ；
In the formula, Q ot Metering daily oil production for a wellhead; q wt Metering daily water yield for a wellhead; k is a radical of formula ro,n The relative permeability of the oil phase of the nth production zone; k is a radical of rw,n Relative permeability of the water phase of the nth produced layer; k is a radical of n Effective permeability for the nth production zone; p is a radical of n Formation pressure for the nth producing formation; mu.s o,n Viscosity of produced oil for nth producing formation; mu.s w,n Viscosity of produced water for nth producing zone; h n Is the thickness of the nth yield layer.
The single-layer oil-water yield is predicted based on the formula, the relative permeability of each phase of oil-water needs to be accurately obtained, and the accurate prediction of the single-layer oil-water yield can be realized through the water saturation numerical value by establishing the relation between the relative permeability ratio of the two phases of oil-water and the reservoir water saturation, and the method is represented as follows:
in the formula, S w,n The water saturation of the nth output layer is obtained through open hole well logging data processing and interpretation; a. b is a coefficient obtained based on oil-water phase permeability experimental data fitting;
oil phase yield from monolayer pay Q op,n And aqueous phase yield Q wp,n Calculating the oil yield f of the productivity equation of the corresponding production zone op,n Water yield f of capacity equation wp,n ；
According to predicted oil production rate f of corresponding production zone o,n And yield equation oil yield f op,n Constructing and developing an optimization processing interpretation objective function of the oil yield of the seven-parameter production profile logging:
in the formula, eor 1 Accumulating errors for the oil production rates of the N production zones; f. of o,n Predicted pay for nth pay zone; f. of op,n The oil yield of the capacity equation of the nth production zone is calculated;
according to the predicted water yield f of the corresponding production zone w,n Water yield f of capacity equation wp,n Constructing and developing a seven-parameter production profile well logging water yield optimization processing interpretation objective function:
in the formula, eor 2 Accumulating errors for the water production rates of the N production zones; f. of w,n Predicted water production rate for the nth pay zone; f. of wp,n The water yield of the capacity equation of the nth production layer;
aiming at an oil well for developing flow collecting umbrella production profile well logging:
according to the apparent velocities of the oil phase fluid and the water phase fluid of the interpretation layers, the oil production quantity Q 'of the corresponding production layer is respectively calculated' o,n And water production amount Q' w,n ；
According to the oil production quantity Q 'of the corresponding production layer' o,n And water production amount Q' w,n Calculating the predicted oil production rate f 'of the corresponding production layer' o,n And predicted water production rate f' w,n ；
Calculating oil phase yield Q 'of single-layer production layer by combining with capacity equation based on basic theory of reservoir seepage mechanics' op,n And aqueous phase yield Q' wp,n ；
Oil phase production Q 'from Single layer production layer' op,n And aqueous phase yield Q' wp,n Calculating the oil yield f 'of the capacity equation of the corresponding production layer' op,n And capacity equation water yield f' wp,n ；
According to the predicted oil production rate f 'of the corresponding production layer' o,n Oil yield f 'of capacity equation' op,n Constructing and developing a flow-collecting umbrella production profile well logging oil yield optimization processing interpretation objective function:
in the formula, eor 1 'is the cumulative error of oil production rates of N' producing zones; f' o,n Predicted pay for nth' productive layer; f' op,n The oil yield of the capacity equation of the nth' productive layer is calculated;
according to the predicted water production rate f 'of the corresponding production layer' w,n And capacity equation water yield f' wp,n Constructing and developing a flow-collecting umbrella production profile well logging water production rate optimization processing interpretation objective function:
in the formula, eor 2 ' is the accumulated error of the water production rate of N production zones; f' w,n Predicted water production rate for the nth' productive zone; f' wp,n The water production rate is the capacity equation of the nth' productive layer.
(5) Solving the optimal value of the optimization processing interpretation objective function to obtain a logging interpretation result of the production profile, which specifically comprises the following steps:
optimizing the constructed optimized processing and interpreting objective function of the logging data of the output profile based on a backbone particle swarm algorithm, and solving the minimum value of the optimized processing and interpreting objective function;
the backbone particle swarm optimization realizes the updating of particle positions in a mode of randomly sampling by Gaussian distribution, wherein the mean value of the Gaussian distribution is the center of an individual optimal position and a global optimal position of particles, the standard deviation is the deviation of the individual optimal position and the global optimal position of the particles, the individual optimal position of the particles corresponds to the solution value of the minimum value of an optimization processing interpretation objective function, the optimization processing interpretation objective function comprises the development of an optimization processing interpretation objective function of oil production rate of seven-parameter production profile logging, the development of an optimization processing interpretation objective function of water production rate of seven-parameter production profile logging, the development of an optimization processing interpretation objective function of oil production rate of manifold umbrella production profile logging and the development of an optimization processing interpretation objective function of water production rate of manifold umbrella production profile logging, and a particle position updating model can be expressed as,
in the formula, x ij (t) is the position of the ith particle at time t in the jth iteration; p is a radical of ij (t) the optimal position of the ith particle individual at the t moment in the jth iteration; ξ is a standard normally distributed random number.
The invention provides a new method for optimizing and explaining well logging information of a multi-information coupling production profile on the basis of well logging information of an oil well production profile, comprehensively considering wellbore fluid properties, response of a logging instrument and reservoir characteristics, combining seepage mechanics, related theories of fluid mechanics and optimization method principles, and establishing an oil well oil-water phase apparent velocity optimization quantitative calculation method model influenced by coupling multiple factors by comprehensively considering the response of the logging instrument, the fluid properties and the reservoir characteristics, thereby realizing accurate prediction of single-layer oil-water yield based on the well production profile logging information under different conditions and providing accurate support parameters for optimization and adjustment of a development scheme of a water finding and control water stage and a lower stage of an oil well.
Compared with the prior art, the invention has the remarkable advantages that:
1) Compared with the traditional method for explaining the logging curve only by depending on the production profile, the method considers the influences of shaft dynamics, stratum characteristics and instruments, adopts an optimization method to process comprehensive analysis to obtain an optimal solution, and overcomes the defect of large error of quantitative explanation only depending on the production profile logging data;
2) The quantitative evaluation precision is high. By fusing stratum information, the problem that the processing and interpretation precision of the well logging data of the output profile is low due to the entrance effect when multiple production layers are adjacent is effectively solved, and the prediction precision of the oil-water yield of a single layer is improved;
3) The operability is strong. The basic information data adopted by the invention can be conveniently obtained for any oil well developing the production profile logging, and the application operability of the mine field is strong and the implementation is convenient.
Drawings
FIG. 1 is a schematic flow chart of a multi-information fusion production profile well logging interpretation optimization method proposed by the present invention;
FIG. 2 is a chart of total flow and water cut calculated by interpolation according to turbine response and water retention values in manifold umbrella production profile logging;
FIG. 3 is a flow chart illustrating the comprehensive data processing according to the present invention;
FIG. 4 is a plot of oil and water permeability from a core test of an example well pay zone.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a new optimization and interpretation method of well logging information of a multi-information coupling production profile based on well logging information of an oil well production profile, comprehensively considering wellbore fluid properties, response of a logging instrument and reservoir characteristics, combining related theories of seepage mechanics and hydromechanics and optimization method principles, and establishing an oil well oil-water phase apparent velocity optimization and quantitative calculation method model influenced by coupling multiple factors by comprehensively considering the response of the logging instrument, the fluid properties and the reservoir characteristics, as shown in figure 1, the method comprises the following steps:
(1) Dividing a production profile well logging interpretation layer based on well logging information and a shaft structure;
dividing the oil well into an oil well for developing a seven-parameter production profile logging and an oil well for developing a collector umbrella production profile logging according to the yield of the oil well;
aiming at an oil well for carrying out seven-parameter production profile logging, selecting a curve response stable section between two production layers to divide an explanation layer based on turbine flow, water holdup and fluid density curve response characteristics, wherein the thickness of the explanation layer is generally larger than 0.2m;
aiming at an oil well for carrying out manifold umbrella production profile well logging, an interpretation layer is divided at a point-measuring position between two production layers, and the number of the interpretation layers is matched with that of the production layers.
(2) Calculating the average fluid velocity of each interpretation layer of the production profile logging based on the flow logging information;
aiming at an oil well for developing seven-parameter production profile logging, on the premise of knowing the production dynamics and production profile logging information of an oil well wellhead, the method for calculating the average fluid speed by means of the seven-parameter production profile logging information can eliminate the influence of the factors of the instrument by means of an up-down subsection turbine rotating speed and cable speed intersection analysis method considering the influences of the positive and negative rotation of a turbine and the starting speed, and the average fluid speed of each interpretation layer is calculated, wherein the specific expression is as follows:
in the formula, for an oil well that develops a seven parameter production profile log: v. of m,k Average fluid velocity for the kth interpretation layer; v. of a,k+ The apparent fluid velocity is calculated when the turbine of the kth interpretation layer rotates forwards (clockwise when viewed from bottom to top); v. of th+ Is the starting speed of the turbine in the forward rotation, which is equal to v of the turbine in the zero flow a+ Or obtained in a laboratory calibration experiment; v. of a,k- The apparent fluid velocity calculated when the turbine of the kth interpretation layer rotates reversely (anticlockwise from bottom to top); v. of th- Is the starting speed of the turbine when the turbine rotates reversely, which is equal to v of the turbine in zero flow a- Or obtained in a laboratory calibration experiment; c v,k Velocity profile correction factors for the kth interpretation layer;
wherein, the average apparent fluid velocity v of the k interpretation layer calculated when the turbine rotates positively a,k+ And the average apparent fluid velocity v of the k-th interpretation layer calculated when the turbine rotates reversely a,k- The following equations are respectively obtained:
in the formula, RPS i，k+ Response values measured for the ith pass of the kth interpretive layer in (rad/s) for normal rotation of the turbine rotor; v li+ The unit of the instrument speed is (m/min) when the turbine rotor rotates forwards and is measured in the ith time, i =0, 1, 2\8230 \8230, 8; n is a radical of + The number of effective measuring points is the number of the effective measuring points when the turbine rotates forwards; RPS j，k- The response value measured for the jth turn of the kth interpretation layer at the time of the reversal of the turbine rotor is expressed by (rad/s); v lj- The unit of the instrument speed is (m/min) when the turbine rotor rotates forwards and is measured in the ith time, j =0, 1, 2\8230, and \8230is8; n is a radical of - The number of effective measuring points is the number of effective measuring points when the turbine rotates reversely.
In a preferred embodiment, before calculating the average fluid velocity of each interpretation layer, the method further comprises the step of calculating the starting velocity v when the turbine rotates forwards based on the instrument experiment calibration value th+ And the starting speed v at the time of turbine reversal th- And (6) carrying out correction.
Aiming at an oil well for carrying out flow collection umbrella production profile well logging, point measurement turbine response data corresponding to the depth are selected by combining the positions of production layers, relative stable sections in the point measurement turbine response data are selected based on point measurement time, an average value is obtained to obtain turbine response of the depth position, and then average fluid speeds v 'of corresponding explanation layers are obtained by combining a physical experiment chart interpolation method' m,k The calibration of the fluid speed under the unified response standard can be realized based on the plate interpolation, and the influence of the instrument can be well eliminated.
(3) Calculating the apparent velocity of the oil phase fluid and the apparent velocity of the water phase fluid of each interpretation layer based on the average fluid velocity of each interpretation layer;
for wells that develop seven parameter production profile logs: according to the average fluid velocity of each interpretation layer, the apparent velocity of the oil phase fluid and the apparent velocity of the water phase fluid of each interpretation layer of the production profile logging are calculated by combining a slippage model, the specific formula is,
in the formula, for an oil well that developed a seven parameter production profile log: v. of so,k Apparent velocity of the oil phase fluid for the kth explaining layer; v. of sw,k The apparent velocity of the water phase fluid of the kth interpretation layer; v. of m,k Average fluid velocity for the kth interpretation layer; CPS w The response value of the water holdup meter under the condition of full water is shown; CPS m,k Logging a well response value for the water holdup of the kth interpretation layer; CPS o The response value of the water holdup meter under the full oil condition is shown; v. of sow,k The slippage rate of the oil phase relative to the water phase is explained for the k < th > time;
the slippage speed of the oil phase relative to the water phase in the kth interpretation layer is specifically calculated by the following formula:
in the formula, ρ o,k Logging the oil phase density of the kth interpretation zone for the production profile; rho w,k Logging the density of the water phase of the kth interpretation zone for the production profile;
and for the oil well for carrying out the collecting umbrella production profile logging, adopting physical experiment plate interpolation to obtain the oil content and the water content of each interpretation layer, and calculating to obtain the apparent velocity of oil phase fluid and the apparent velocity of water phase fluid of each interpretation layer of the production profile logging:
v' so,k ＝v' m,k ·C o,k
v' sw,k ＝v' m,k ·C w,k
in the formula, aiming at the oil well for developing the flow-collecting umbrella production profile well logging: v' so,k Apparent velocity of the oil phase fluid for the kth explaining layer; v' sw,k The aqueous phase of the k-th explanation layerA fluid superficial velocity; v' m,k Average fluid velocity for the kth interpretation layer; c w,k Is the water content of the kth interpretation layer; c o,k The oil content of the kth interpretation layer.
(4) Constructing an optimized processing and interpretation objective function of the logging data of the production profile;
for wells that develop seven parameter production profile logs:
respectively calculating the oil yield Q of the corresponding production layer according to the apparent velocity of the oil phase fluid and the apparent velocity of the water phase fluid of each interpretation layer o,n And water yield Q w,n ；
Q o,n ＝0.036·π·(D 2 -d 2 )·(v so,k -v so,k+1 )
Q w,n ＝0.036·π·(D 2 -d 2 )·(v sw,k -v sw,k+1 )
In the formula, Q o,n The oil production of the nth producing zone; q w,n Water production of the nth producing zone; d is the inner diameter of the oil pipe or the sleeve; d is the outer diameter m of the production profile logging instrument; n =0, 1, 2 \8230; v. of so,k Apparent velocity of the oil phase fluid for the kth interpretive layer; v. of so,k+1 The apparent velocity of the oil phase in the k +1 th interpretation layer; v. of sw,k The apparent velocity of the aqueous phase for the kth interpretation layer; v. of sw,k+1 The apparent velocity of the aqueous phase of the k +1 th interpretation layer; the nth generation layer is positioned between the kth interpretation layer and the (k + 1) th interpretation layer;
here, the oil production Q o,n And water yield Q w,n Respectively obtaining the oil yield and the water yield of the nth output layer of the oil well by only depending on the logging information of the output profile according to Q o,n And Q w,n Calculating the predicted oil yield f of the corresponding production zone o,n And predicting water production rate f w,n ；
In the production process of the oil well, the oil-gas-water yield of the well mouth can be recorded in real time in one day, and the oil phase yield Q of the single-layer production layer is calculated based on the oil-water yield of the well mouth and according to the basic theory of oil reservoir seepage mechanics and the yield equation by combining with the oil phase yield Q of the oil reservoir op,n And aqueous phase yield Q wp,n ；
In the formula, Q ot Metering daily oil production for a wellhead; q wt Metering daily water yield for a wellhead; k is a radical of ro,n The relative permeability of the oil phase of the nth production zone; k is a radical of rw,n Relative permeability of the water phase of the nth produced layer; k is a radical of formula n Effective permeability for the nth production zone; p is a radical of n Formation pressure for the nth producing formation; mu.s o,n Viscosity of produced oil for nth producing formation; mu.s w,n Viscosity of produced water for nth producing zone; h n Is the thickness of the nth production layer.
Based on the above formula, the yield of the single-layer oil-water is predicted, the relative permeability of each phase of the oil-water needs to be accurately obtained, and the accurate prediction of the yield of the single-layer oil-water can be realized through the water saturation value by establishing the relationship between the relative permeability ratio of the two phases of the oil-water and the water saturation of the reservoir, which is expressed as follows:
in the formula, S w,n The water saturation of the nth output layer is obtained through open hole well logging data processing and interpretation; a. b is a coefficient obtained based on oil-water phase permeability experimental data fitting;
oil phase yield from monolayer pay Q op,n And aqueous phase yield Q wp,n Calculating the oil yield f of the productivity equation of the corresponding production zone op,n Water yield f of capacity equation wp,n ；
According to predicted oil production rate f of corresponding production zone o,n Oil yield f of capacity equation op,n Constructing and developing an oil yield optimization processing interpretation objective function of a seven-parameter production profile logging:
in the formula eor 1 Accumulating errors for the oil production rates of the N production zones; f. of o,n Predicted pay for nth pay zone; f. of op,n The oil yield of the capacity equation of the nth production zone is calculated;
according to the predicted water yield f of the corresponding production zone w,n Water yield f of capacity equation wp,n Constructing and developing a seven-parameter production profile well logging water yield optimization processing interpretation objective function:
in the formula eor 2 Accumulating errors for the water production rates of the N production zones; f. of w,n Predicted water production rate for the nth pay zone; f. of wp,n The water yield of the capacity equation of the nth production layer;
aiming at an oil well for developing manifold umbrella production profile well logging:
and obtaining an interpretation objective function for developing manifold parachute output profile well logging oil production rate optimization processing and water production rate optimization processing:
in the formula eor 1 'is the cumulative error of oil production rate of N' production zones; f' o,n Predicted pay for nth' productive zone; f' op,n The oil yield for the capacity equation of the nth' productive layer;
in the formula eor 2 Accumulated error of water yield of N production layers; f' w,n Predicted water production rate for the nth' productive zone; f' wp,n The water production rate is the capacity equation for the nth' productive zone.
(5) And solving the optimal value of the optimization processing interpretation objective function to obtain a logging interpretation result of the production profile.
Optimizing the constructed optimized processing and interpreting objective function of the logging data of the output profile based on a backbone particle swarm algorithm, and solving the minimum value of the optimized processing and interpreting objective function;
the backbone particle swarm algorithm realizes the updating of the particle positions by adopting a mode of random sampling in Gaussian distribution, wherein the mean value of the Gaussian distribution is the center of the individual optimal position and the global optimal position of the particles, the standard deviation is the deviation of the individual optimal position and the global optimal position of the particles, a particle position updating model can be expressed as,
in the formula, x ij (t) is the position of the ith particle at time t in the jth iteration; p is a radical of ij (t) the optimal position of the ith particle individual at the t moment in the jth iteration; xi is a standard normally distributed random number, wherein the optimal position of each particle corresponds to the minimum value of an optimization processing interpretation objective function, and the optimization processing interpretation objective function comprises the development of an oil yield optimization processing interpretation objective function of a seven-parameter output profile logging, the development of a water yield optimization processing interpretation objective function of a seven-parameter output profile logging, the development of an oil yield optimization processing interpretation objective function of a collector umbrella output profile logging or the development of a collector umbrella output profileAnd the optimization processing of the surface logging water yield explains the objective functions of four types.
And (5) minimizing the value of the optimization processing interpretation objective function obtained based on the prediction in the step (4) so that the oil-water yield of each production zone obtained by final prediction is closest to the true value, namely
Obtaining the minimum error through the iterative optimization of the backbone particle swarm algorithm loop, and outputting Q under the condition of the minimum error w,n And Q o,n And the optimal oil and water yield value of the producing zone n is obtained, and the optimal oil and water yield data of all the producing zones of the corresponding oil well can be obtained through layer-by-layer circular calculation.
The following examples of the present invention are given in conjunction with the summary of the invention:
the N236 well is a northwest China oil well, the inner diameter of a casing of the well is 157.08mm, the depth of a bell mouth is 4714.8m, the depths of perforation layers are 4749-4754 m and 4757-4768 m, the production dynamic information monitoring is carried out by adopting conventional seven-parameter production profile well logging counting, the outer diameter of an instrument is 38mm, the response value of a water holdup short circuit in the instrument in total water is 10000CPS, the response value in total oil is 26000CPS, the measurement well section is 4688.24-4786.97 m, and the oil production in the day is 22.37m through well mouth measurement test 3 (d) daily yield of water 350.69m 3 (d) water content 94.004%. Based on the logging curve response characteristics, the improved 2 perforation layers are subdivided into 4 production layers for fine explanation, and the production layers after subdivision are as follows: 4749-4754 m, 4757-4760 m, 4760-4763 m, 4763-4768 m, production zone layer thickness of 5m, 3m, 5m, production zone middle fluid pressure of 47.345MPa, 47.397MPa, 47.405MPa, 47.422MPa, corresponding divided explainer layers of 4732.3-4733.125 m, 4754.725-4755.325 m, 4759.125-4759.65 m, 4762.825-4763.575 m, 4771.825-4772.825 m, wherein 4732.3-4733.125 m corresponds to a full flow interval, 4771.825-4772.825 m corresponds to a zero flow interval, five explainer layers correspond to fluid temperatures of 114.698 deg.712 deg.114 deg.639 deg.608 deg.374 deg.C, 114.244 deg.23 deg.C, 47.018MPa, 47.395 deg.47.47.47.47 deg.47 MPa, 47.395MPa412MPa, 47.442MPa, water holdup counts 10119.753CPS, 10146.599CPS, 9990.901CPS, 9986.316CPS, 9989.271CPS, 5 interpretation layer visual fluid speeds of 13.405m/min, 10.952m/min, 6.841m/min, 2.212m/min, 1.387m/min are obtained by the method of the step (2) based on the speed of 10 turbine rotating speeds vs. cables, the interpretation middle speed profile correction coefficient takes a value of 0.503, the effective permeability of 4 production layers is respectively 20.367mD, 25.714mD, 18.147mD, 16.203mD improved based on the interpretation of well completion data, the oil-water yield of each production layer of the well is comprehensively predicted by adopting seven parameter information and formation information based on the technical route of fig. 3, the comprehensive evaluation result of the production profile logging of the well is shown in fig. 4, and the comprehensive interpretation water cut error is 0.301%. The predicted oil-water yield of each pay zone is shown in the table below.
The first track from left to right in the data processing and interpretation comprehensive result chart finally generated by the oil production well is a logging depth track; the second path is a depth correction curve path and comprises an open hole well logging natural gamma GR (well completion), a production well logging natural gamma GR and a magnetic positioning CCL curve; the third is an open hole logging data processing and explaining reservoir oil-gas junction argumentation; the fourth path is an oil well perforation layer section path; the fifth channel is a wellbore fluid property channel and comprises fluid temperature, fluid pressure, fluid density and water holding rate counting curves; the sixth path is a turbine rotor speed path for 5 times of up measurement and 5 times of down measurement; the seventh path is an instrument speed path for 5 times of upper measurement and 5 times of lower measurement; the eighth line is a line for explaining the water holding rate of the shaft and the fluid velocity; the ninth step is the oil-water yield of each production layer obtained by comprehensive treatment and explanation; the tenth is the production profile.
In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A multi-information fusion production profile well logging interpretation optimization method is characterized by comprising the following steps:
(1) Dividing a production profile well logging interpretation layer based on well logging information and a shaft structure;
(2) Calculating the average fluid velocity of each interpretation layer of the production profile logging;
(3) Calculating the apparent velocity of the oil phase fluid and the apparent velocity of the water phase fluid of each interpretation layer based on the average fluid velocity of each interpretation layer;
(4) Constructing an optimization processing and interpretation objective function of the logging data of the output profile;
(5) And solving the optimal value of the optimization processing interpretation objective function to obtain a logging interpretation result of the production profile.
2. The multi-information-fusion production profile well logging interpretation optimization method according to claim 1, wherein the step (1) specifically comprises:
dividing the oil well into an oil well for developing a seven-parameter production profile logging and an oil well for developing a collector umbrella production profile logging according to the yield of the oil well;
aiming at an oil well for developing seven-parameter production profile logging, selecting a curve response stable section between two production layers to divide an explanation layer based on turbine flow, water holdup and fluid density curve response characteristics;
aiming at an oil well for carrying out manifold umbrella production profile well logging, an interpretation layer is divided at a point-measuring position between two production layers, and the number of the interpretation layers is matched with that of the production layers.
3. The method for optimizing multi-information fusion production profile well logging interpretation according to claim 2, wherein the step (2) comprises the following steps:
aiming at an oil well for developing seven-parameter production profile well logging, calculating the average fluid speed of each interpretation layer by utilizing an up-down subsection turbine rotating speed and cable speed intersection analysis method considering the influence of the positive and negative rotation of a turbine and the starting speed, wherein the specific expression is as follows:
in the formula, for an oil well that developed a seven parameter production profile log: v. of m,k Average fluid velocity for the kth interpretation layer; v. of a,k+ Calculating the apparent fluid velocity for the positive rotation of the turbine of the kth interpretation layer; v. of th+ The starting speed of the turbine in forward rotation is obtained; v. of a,k- Calculating the apparent fluid velocity when the turbine of the kth interpretation layer reverses; v. of th- The starting speed when the turbine rotates reversely; c v,k Velocity profile correction coefficients for the kth interpretation layer;
aiming at an oil well for carrying out manifold umbrella production profile well logging, the average fluid speed of each interpretation layer is calculated by averaging the response data of the point-to-point turbine measurement and combining a physical experiment plate interpolation method.
4. The method of claim 3, wherein the calculating the average fluid velocity of each interpretation layer for a well undergoing seven parameter production profile logging further comprises calculating the starting velocity v for forward rotation of the turbine before calculating the average fluid velocity of each interpretation layer th+ And the starting speed v at the time of turbine reversal th- And (6) carrying out correction.
5. The multi-information-fusion production profile well logging interpretation optimization method according to claim 3, wherein the step (3) specifically comprises:
for wells that develop seven parameter production profile logs: according to the average fluid velocity of each interpretation layer, the apparent velocity of the oil phase fluid and the apparent velocity of the water phase fluid of each interpretation layer of the production profile logging are calculated by combining a slippage model, the specific formula is,
in the formula, for an oil well that develops a seven parameter production profile log: v. of so,k Apparent velocity of the oil phase fluid for the kth explaining layer; v. of sw,k The apparent velocity of the water phase fluid of the kth interpretation layer; v. of m,k Average fluid velocity for the kth interpretation layer; CPS w The response value of the water holdup meter under the condition of full water is shown; CPS m,k Logging response values for the k interpretation layer water holdup; CPS o The response value of the water holdup meter under the full oil condition is shown; v. of sow,k The slippage rate of the oil phase relative to the water phase for the kth interpretation layer;
aiming at an oil well for developing the collector parachute production profile logging, the oil content and the water content of each interpretation layer are obtained by adopting physical experiment plate interpolation, and the apparent velocity of oil phase fluid and the apparent velocity of water phase fluid of each interpretation layer of the production profile logging are obtained by calculation:
v' so,k ＝v' m,k ·C o,k
v' sw,k ＝v' m,k ·C w,k
in the formula, aiming at an oil well for developing flow collecting umbrella production profile logging: v' so,k Apparent velocity of the oil phase fluid for the kth explaining layer; v' sw,k The apparent velocity of the aqueous phase fluid of the kth interpretation layer; v' m,k Average fluid velocity for the kth interpretation layer; c w,k Is the water content of the kth interpretation layer; c o,k The oil content of the k-th interpretation layer.
6. The method for optimizing the logging interpretation of the multi-information-fusion production profile according to claim 5, wherein for an oil well for which seven-parameter production profile logging is performed, the slippage velocity of the oil phase relative to the water phase in the kth interpretation layer is calculated by the following formula:
in the formula, ρ o,k Logging the oil phase density of the kth interpretation zone for the production profile; rho w,k The water phase density of the kth interpretation zone was logged for the production profile.
7. The multi-information-fusion production profile well logging interpretation optimization method according to claim 5, wherein the step (4) specifically comprises:
for wells that develop seven parameter production profile logs:
respectively calculating the oil yield Q of the corresponding production layer according to the apparent velocity of the oil phase fluid and the apparent velocity of the water phase fluid of each interpretation layer o,n And water yield Q w,n ；
According to the oil production Q of the corresponding production zone o,n And water yield Q w,n Calculating the predicted oil yield f of the corresponding production zone o,n And predicting water production rate f w,n ；
Based on the basic theory of oil reservoir seepage mechanics and in combination with the capacity equation, calculating the oil phase yield Q of the single-layer production layer op,n And aqueous phase yield Q wp,n ；
Oil phase yield from monolayer pay Q op,n And aqueous phase yield Q wp,n Calculating the oil yield f of the productivity equation of the corresponding production zone op,n Water yield f of capacity equation wp,n ；
According to predicted oil production rate f of corresponding production zone o,n Oil yield f of capacity equation op,n Constructing and developing an oil yield optimization processing interpretation objective function of a seven-parameter production profile logging:
in the formula, eor 1 Accumulating errors for oil production rates of N production zones; f. of o,n Predicted pay for nth pay zone; f. of op,n The oil yield of the capacity equation of the nth production zone is calculated;
according to the predicted water yield f of the corresponding production zone w,n Water yield f of capacity equation wp,n Constructing and developing a seven-parameter production profile well logging water yield optimization processing interpretation objective function:
in the formula, eor 2 Accumulating errors for the water production rates of the N production zones; f. of w,n Predicted water production rate for the nth production zone; f. of wp,n The water yield of the capacity equation of the nth production layer;
aiming at an oil well for developing flow collecting umbrella production profile well logging:
according to the apparent velocities of the oil phase fluid and the water phase fluid of the interpretation layers, the oil production quantity Q 'of the corresponding production layer is respectively calculated' o,n And water production amount Q' w,n ；
According to the oil production quantity Q 'of the corresponding production layer' o,n And water production amount Q' w,n Calculating the predicted oil production rate f 'of the corresponding production layer' o,n And predicted water production rate f' w,n ；
Based on the basic theory of oil reservoir seepage flow mechanics, the oil phase yield Q 'of the single-layer production layer is calculated by combining a capacity equation' op,n And aqueous phase yield Q' wp,n ；
Oil phase production Q 'from Single layer production layer' op,n And aqueous phase yield Q' wp,n Calculating the oil yield f 'of the capacity equation of the corresponding production layer' op,n And capacity equation water yield f' wp,n ；
Predicted oil yield f 'according to corresponding production layer' o,n And oil yield f of capacity equation' op,n Constructing and developing a flow-collecting umbrella production profile well logging oil yield optimization processing interpretation objective function:
in the formula eor 1 'is the cumulative error of oil production rate of N' production zones; f' o,n Predicted pay for nth' productive zone; f' op,n The oil yield for the capacity equation of the nth' productive layer;
according to the predicted water production rate f 'of the corresponding production layer' w,n And capacity equation water yield f' wp,n Constructing and developing a flow-collecting umbrella output profile well logging water yield optimization processing interpretation objective function:
in the formula eor 2 ' is the accumulated error of the water production rate of N production zones; f' w,n Predicted water production rate for the nth' productive zone; f' wp,n The water production rate is the capacity equation for the nth' productive zone.
8. The multi-information-fusion production profile well logging interpretation optimization method according to claim 7, wherein the step (5) specifically comprises:
optimizing the constructed optimized processing and interpreting objective function of the logging data of the output profile based on a backbone particle swarm algorithm, and solving the minimum value of the optimized processing and interpreting objective function;
the backbone particle swarm optimization realizes the updating of particle positions by adopting a mode of randomly sampling in Gaussian distribution, wherein the mean value of the Gaussian distribution is the center of an individual optimal position and a global optimal position of particles, the standard deviation is the deviation of the individual optimal position and the global optimal position of the particles, the individual optimal position of the particles corresponds to the minimum value of an optimization processing interpretation objective function, the optimization processing interpretation objective function comprises the development of an optimization processing interpretation objective function of oil yield of logging with a seven-parameter production profile, the development of an optimization processing interpretation objective function of water yield of logging with a seven-parameter production profile, the development of an optimization processing interpretation objective function of oil yield of logging with a manifold umbrella production profile, the development of an optimization processing interpretation objective function of water yield of logging with a manifold umbrella production profile, and the particle position updating model can be expressed as,
in the formula, x ij (t) is the position of the ith particle at time t in the jth iteration; p is a radical of formula ij (t) the optimal position of the ith particle individual at the t moment in the jth iteration; ξ is a standard normally distributed random number.
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