CN111323823A - Method and system for determining logging porosity curve - Google Patents
Method and system for determining logging porosity curve Download PDFInfo
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Abstract
The invention provides a method and a system for determining a logging porosity curve. The method comprises the following steps: generating an aqueous poisson impedance and an air poisson impedance; generating a fitting function of the water-containing Poisson impedance according to the water-containing Poisson impedance corresponding to the historical porosity; generating a plurality of fitting functions of the gas-containing Poisson impedance according to the gas-containing Poisson impedance corresponding to the historical porosity; determining a water-containing logging depth range and a gas-containing logging depth range according to the water-containing Poisson impedance fitting function and the gas-containing Poisson impedance fitting function; generating an actual water-bearing porosity relation curve in a water-bearing logging depth range according to a water-bearing Poisson impedance fitting function; generating an actual gas-containing porosity relation curve in a gas-containing logging depth range according to the gas-containing Poisson impedance fitting function; according to the actual water-containing porosity relation curve and the actual gas-containing porosity relation curve, the relation curve of the logging depth and the actual porosity is determined, and the accuracy of predicting the porosity of the reservoir is improved.
Description
Technical Field
The invention relates to the technical field of petroleum exploration and development, in particular to a method and a system for determining a logging porosity curve.
Background
In the oil exploration process, the physical property of the reservoir determines the scale of the trap resource amount, and the economic benefit of exploration and development is influenced. Reservoir properties include a number of aspects, conventional porosity, water saturation, formation permeability, etc., where the most significant factor in determining the amount of trapped resources is porosity, and formation porosity represents the percentage of pore space per volume. In seismic exploration, porosity is typically empirically related to other measurable or predictable attributes, which are then used to indirectly calculate the porosity distribution.
The conventional method at present is to calculate the porosity velocity volume of the whole area by using the longitudinal wave impedance attribute obtained by inversion. During logging, the porosity can be characterized by a conventional logging curve, most commonly a neutron porosity curve, which is finally converted into the characterization of the porosity by measuring the neutron number in the underground space, and the method can indirectly indicate the relative distribution of the porosity around a wellhead and has higher precision for locally predicting the porosity. In seismic exploration, prediction of reservoir porosity based on elastic information has gained many beneficial applications, however, in logging, porosity prediction is rarely developed based on elastic information due to the absence or unreliability of shear wave logging information.
The requirement on the real porosity of the well logging is higher and higher in the actual exploration process, and the relative porosity given by the conventional neutron porosity cannot meet the requirement; in the process of predicting the porosity based on the elasticity information, although the porosity is not affected by the pore fluid, the elasticity information of the reservoir is affected by the pore fluid, so that the porosity predicted based on the elasticity information is necessarily affected.
Disclosure of Invention
The embodiment of the invention mainly aims to provide a method for determining a logging porosity curve, so as to overcome the influence of pore fluid on porosity prediction and improve the precision of predicting reservoir porosity.
In order to achieve the above object, an embodiment of the present invention provides a method for determining a log porosity curve, including:
generating water-containing Poisson impedance according to pre-acquired water-containing logging forward modeling data, and generating gas-containing Poisson impedance according to pre-acquired gas-containing logging forward modeling data; the water-containing logging forward modeling data and the gas-containing logging forward modeling data correspond to historical porosity one by one;
generating a plurality of water-containing Poisson impedance coordinate points according to the water-containing Poisson impedance corresponding to the plurality of historical porosities; generating a plurality of gas-containing Poisson impedance coordinate points according to the gas-containing Poisson impedances corresponding to the plurality of historical porosities;
fitting a plurality of water-containing poisson impedance coordinate points to generate a water-containing poisson impedance fitting function; fitting a plurality of gas-containing Poisson impedance coordinate points to generate a gas-containing Poisson impedance fitting function;
determining a poisson impedance gas-water boundary coefficient according to the water-containing poisson impedance fitting function and the gas-containing poisson impedance fitting function;
determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water boundary coefficient and a pre-acquired relation curve between the logging depth and the actual Poisson impedance;
generating a relation curve between the logging depth in the water-containing logging depth range and the actual water-containing porosity according to the water-containing Poisson impedance fitting function and the relation curve between the logging depth corresponding to the water-containing logging depth range and the actual Poisson impedance; generating a relation curve between the logging depth in the gas-containing logging depth range and the actual gas-containing porosity according to the relation curve between the logging depth corresponding to the gas-containing poisson impedance fitting function and the gas-containing logging depth range and the actual poisson impedance;
and determining a relation curve of the logging depth and the actual porosity according to the relation curve of the logging depth and the actual water-containing porosity and the relation curve of the logging depth and the actual gas-containing porosity.
The embodiment of the invention also provides a system for determining a logging porosity curve, which comprises:
the poisson impedance unit is used for generating water-containing poisson impedance according to the water-containing logging forward modeling data which are obtained in advance and generating gas-containing poisson impedance according to the gas-containing logging forward modeling data which are obtained in advance; the water-containing logging forward modeling data and the gas-containing logging forward modeling data correspond to historical porosity one by one;
a coordinate point generating unit, which is used for generating a plurality of water-containing Poisson impedance coordinate points according to the water-containing Poisson impedance corresponding to the plurality of historical porosities; generating a plurality of gas-containing Poisson impedance coordinate points according to the gas-containing Poisson impedances corresponding to the plurality of historical porosities;
the fitting unit is used for fitting a plurality of water-containing Poisson impedance coordinate points to generate a water-containing Poisson impedance fitting function; fitting a plurality of gas-containing Poisson impedance coordinate points to generate a gas-containing Poisson impedance fitting function;
the gas-water boundary coefficient unit is used for determining the poisson impedance gas-water boundary coefficient according to the water-containing poisson impedance fitting function and the gas-containing poisson impedance fitting function;
the depth range unit is used for determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water boundary coefficient and a pre-acquired relation curve between the logging depth and the actual Poisson impedance;
the relation curve unit is used for generating a relation curve between the logging depth in the water-containing logging depth range and the actual water-containing porosity according to the water-containing Poisson impedance fitting function and the relation curve between the logging depth corresponding to the water-containing logging depth range and the actual Poisson impedance; generating a relation curve between the logging depth in the gas-containing logging depth range and the actual gas-containing porosity according to the relation curve between the logging depth corresponding to the gas-containing poisson impedance fitting function and the gas-containing logging depth range and the actual poisson impedance;
and the logging porosity curve unit is used for determining a relation curve between the logging depth and the actual porosity according to the relation curve between the logging depth and the actual water-containing porosity and the relation curve between the logging depth and the actual gas-containing porosity.
The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the steps of the determination method of the logging porosity curve when executing the computer program.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the method for determining a porosity curve of a well log.
The method and the system for determining the logging porosity curve firstly generate the water-containing Poisson impedance according to the water-containing logging forward modeling data, generating gas-containing Poisson impedance according to the gas-containing well logging forward modeling data, determining the gas-water boundary coefficient of the Poisson impedance according to the water-containing Poisson impedance and the gas-containing Poisson impedance, then determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water boundary coefficient, then generating a relation curve between the logging depth and the actual water-containing porosity in the water-containing logging depth range and a relation curve between the logging depth and the actual gas-containing porosity in the gas-containing logging depth range, and finally determining a relation curve between the logging depth and the actual porosity according to the relation curve between the logging depth and the actual water-containing porosity and the relation curve between the logging depth and the actual gas-containing porosity, the method overcomes the influence of pore fluid on porosity prediction and improves the precision of predicting the porosity of the reservoir.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a flow chart of a method for determining a porosity log in an embodiment of the invention.
Fig. 2 is a parameter table of water-containing logging forward modeling data and gas-containing logging forward modeling data in an embodiment of the invention.
FIG. 3 is a schematic representation of an aqueous Poisson's impedance fitting function curve and an air-containing Poisson's impedance fitting function curve in an embodiment of the present invention.
FIG. 4 is a schematic diagram of a relationship curve between a logging depth and an actual compressional velocity according to an embodiment of the present invention.
FIG. 5 is a graphical representation of the relationship between the depth of the log and the actual shear velocity in an embodiment of the present invention.
FIG. 6 is a graphical representation of a log depth versus actual density curve in an embodiment of the present disclosure.
FIG. 7 is a graphical representation of a log depth versus actual Poisson's impedance in an embodiment of the present invention.
FIG. 8 is a schematic illustration of determining an aqueous logging depth range and a gas logging depth range in an embodiment of the present invention.
FIG. 9 is a graphical representation of log depth versus actual gas porosity for an embodiment of the present invention.
FIG. 10 is a plot of log depth versus actual water porosity for an embodiment of the present invention.
FIG. 11 is a graphical representation of log depth versus actual porosity in an embodiment of the present invention.
FIG. 12 is a block diagram of a system for determining a porosity log in accordance with an embodiment of the present invention.
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.
As will be appreciated by one skilled in the art, embodiments of the present invention may be embodied as a system, apparatus, device, method, or computer program product. Accordingly, the present disclosure may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.
In view of the fact that pore fluid in the prior art can affect porosity prediction, the embodiment of the invention provides a method for determining a logging porosity curve, so as to overcome the influence of the pore fluid on the porosity prediction and improve the accuracy of predicting the reservoir porosity. The present invention will be described in detail below with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method for determining a porosity log in an embodiment of the invention. As shown in fig. 1, the method for determining the well-logging porosity curve comprises the following steps:
s101: generating water-containing Poisson impedance according to pre-acquired water-containing logging forward modeling data, and generating gas-containing Poisson impedance according to pre-acquired gas-containing logging forward modeling data; and the water-containing logging forward modeling data and the gas-containing logging forward modeling data correspond to historical porosity one to one.
S102: generating a plurality of water-containing Poisson impedance coordinate points according to the water-containing Poisson impedance corresponding to the plurality of historical porosities; and generating a plurality of gas-containing Poisson impedance coordinate points according to the gas-containing Poisson impedance corresponding to the plurality of historical porosities.
S103: fitting a plurality of water-containing poisson impedance coordinate points to generate a water-containing poisson impedance fitting function; and fitting the plurality of gas-containing Poisson impedance coordinate points to generate a gas-containing Poisson impedance fitting function.
S104: and determining the poisson impedance gas-water boundary coefficient according to the water-containing poisson impedance fitting function and the gas-containing poisson impedance fitting function.
Wherein, S104 includes: obtaining a constant term of the water-containing Poisson impedance fitting function and a constant term of the gas-containing Poisson impedance fitting function; and determining the poisson impedance gas-water boundary coefficient according to the constant term of the water-containing poisson impedance fitting function and the constant term of the gas-containing poisson impedance fitting function.
For example, the average of the constant term of the aqueous poisson impedance fitting function and the constant term of the gaseous poisson impedance fitting function may be used as the poisson impedance gas-water partition coefficient.
S105: and determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water boundary coefficient and a pre-acquired relation curve between the logging depth and the actual Poisson impedance.
Wherein, S105 includes: judging whether the actual Poisson impedance in a relation curve of the logging depth and the actual Poisson impedance is larger than a Poisson impedance gas-water boundary coefficient or not;
when the water-containing logging depth range is larger than the poisson impedance gas-water boundary coefficient, taking the logging depth range corresponding to the actual poisson impedance as the water-containing logging depth range;
and when the gas-water boundary coefficient of the Poisson impedance is smaller than or equal to the gas-water boundary coefficient of the Poisson impedance, taking the logging depth range corresponding to the actual Poisson impedance as a gas-containing logging depth range.
S106: generating a relation curve between the logging depth in the water-containing logging depth range and the actual water-containing porosity according to the water-containing Poisson impedance fitting function and the relation curve between the logging depth corresponding to the water-containing logging depth range and the actual Poisson impedance; and generating a relation curve between the logging depth in the gas-containing logging depth range and the actual gas-containing porosity according to the relation curve between the logging depth corresponding to the gas-containing Poisson impedance fitting function and the gas-containing logging depth range and the actual Poisson impedance.
S107: and determining a relation curve of the logging depth and the actual porosity according to the relation curve of the logging depth and the actual water-containing porosity and the relation curve of the logging depth and the actual gas-containing porosity.
The execution subject of the method for determining a porosity curve for well logging shown in fig. 1 may be a computer. As can be seen from the process shown in fig. 1, the method for determining a logging porosity curve according to the embodiment of the present invention first generates a water-containing poisson impedance according to water-containing logging forward modeling data, generates a gas-containing poisson impedance according to gas-containing logging forward modeling data, determines a poisson impedance gas-water boundary coefficient according to the water-containing poisson impedance gas-water boundary coefficient, determines a water-containing logging depth range and a gas-containing logging depth range according to the poisson impedance gas-water boundary coefficient, generates a relation curve between a logging depth in the water-containing logging depth range and an actual water-containing porosity, and determines a relation curve between the logging depth and an actual gas-containing porosity according to the relation curve between the logging depth and the actual water-containing porosity, and the relation curve between the logging depth and the actual gas-containing porosity, so as to overcome the influence of a pore fluid on porosity prediction, the accuracy of predicting the porosity of the reservoir is improved.
In one embodiment, the water-bearing well logging forward modeling data comprises: forward density of the water-containing reservoir, forward speed of water-containing transverse waves and forward speed of water-containing longitudinal waves; the gas-containing well logging forward modeling data comprises: the positive evolution density of the gas-bearing reservoir, the positive evolution speed of the gas-bearing transverse wave and the positive evolution speed of the gas-bearing longitudinal wave;
generating the hydrous poisson impedance comprises: establishing a water-containing Poisson impedance model; inputting the forward density, forward velocity and forward velocity of transverse wave and longitudinal wave of water-containing reservoir into a water-containing Poisson impedance model to obtain water-containing Poisson impedance;
in particular implementation, the aqueous poisson impedance model is as follows:
PI1＝Vp1*D1-1.63Vs1*D1；
wherein, PI1Is the water-containing Poisson impedance, Vp1Is the forward velocity of longitudinal wave containing water, D1Is the forward density, V, of the water-bearing reservoirs1The forward velocity of transverse wave containing water.
Generating the airborne poisson impedance includes: establishing a poisson impedance model containing gas; and inputting the forward density of the gas-containing reservoir, the forward velocity of the gas-containing transverse wave and the forward velocity of the gas-containing longitudinal wave into the gas-containing Poisson impedance model to obtain the gas-containing Poisson impedance.
In specific implementation, the air-containing poisson impedance model is as follows:
PI2＝Vp2*D2-1.63Vs2*D2；
wherein, PI2Is the air-borne Poisson impedance, Vp2Is the forward velocity of the longitudinal wave containing gas, D2Forward density, V, for gas bearing reservoirss2The forward velocity of the transverse wave containing gas is shown.
In one embodiment, the method further comprises:
establishing a water-containing reservoir forward density model, a water-containing shear wave forward velocity model and a water-containing longitudinal wave forward velocity model;
and inputting the historical porosity and the acquired water-containing density parameter into a water-containing reservoir forward density model to obtain the water-containing reservoir forward density. Wherein the water density parameters include: saturation water density and solid mineral particle density.
In specific implementation, the forward density model of the water-bearing reservoir is as follows:
D1＝ρw(1-Por)+ρm*Por；
where ρ iswFor saturated water density, Por is historical porosity, ρmIs the density of solid mineral particles.
And inputting the forward density of the water-containing reservoir and the obtained shear modulus of the rock skeleton into a water-containing transverse wave forward velocity model to obtain a water-containing transverse wave forward velocity.
In specific implementation, the forward velocity model of transverse water-containing waves is as follows:
wherein, mumAnd the shear modulus of the rock skeleton.
And inputting the shear modulus of the rock framework, the forward density of the water-containing reservoir and the obtained volume modulus of the water-containing rock into a water-containing longitudinal wave forward velocity model to obtain the water-containing longitudinal wave forward velocity.
In specific implementation, the forward velocity model of the longitudinal wave containing water is as follows:
wherein, Ksat1Is the hydrous rock bulk modulus.
Establishing a gas-bearing reservoir forward density model, a gas-bearing transverse wave forward speed model and a gas-bearing longitudinal wave forward speed model;
inputting the historical porosity and gas-containing density parameters into a gas-containing reservoir forward density model to obtain the gas-containing reservoir forward density; wherein, the gas density parameter includes: saturation air density and solid mineral particle density.
In specific implementation, the forward density model of the gas reservoir is as follows:
D2＝ρg(1-Por)+ρm*Por；
where ρ isgIs saturated air density.
And inputting the forward density of the gas-containing reservoir, the shear modulus of the rock skeleton and the forward velocity model of the gas-containing transverse wave into the forward velocity model of the gas-containing transverse wave to obtain the forward velocity of the gas-containing transverse wave.
In specific implementation, the forward velocity model of the transverse wave containing gas is as follows:
and inputting the shear modulus of the rock framework, the forward density of the gas-containing reservoir and the obtained volume modulus of the gas-containing rock into a gas-containing longitudinal wave forward velocity model to obtain the gas-containing longitudinal wave forward velocity.
In specific implementation, the forward velocity model of the airborne longitudinal wave is as follows:
wherein, Ksat2Is the gas-bearing rock bulk modulus.
In one embodiment, the method further comprises: establishing a water-containing rock volume modulus model and a gas-containing rock volume modulus model;
and inputting the obtained rock bulk modulus parameter, the frequency adjusting parameter, the saturated water rock bulk modulus and the historical porosity into a water-containing rock bulk modulus model to obtain the water-containing rock bulk modulus.
Rock bulk modulus parameters include rock matrix bulk modulus and dry rock skeleton bulk modulus. The calculation model of the bulk modulus of the hydrous rock is as follows:
wherein the content of the first and second substances,
Kms1in order to obtain the bulk modulus of the saturated water rock,
is the rate of change of the water-containing pore pressure with the confining stress, KmaIs the bulk modulus of the rock skeleton, K0Is the bulk modulus of the rock matrix, KdryVolume modulus of dry rock skeleton, delta frequency tuning parameter, J0(δ) zero order Bessel function of δ, J1(delta) is a first order Bessel function of delta, Z is the frequency scattering coefficient, f is the frequency, KwThe saturated water bulk modulus.
And inputting the obtained rock volume modulus parameter, the frequency adjusting parameter, the saturated gas rock volume modulus and the historical porosity into a gas-containing rock volume modulus model to obtain the gas-containing rock volume modulus.
The calculation model of the volume modulus of the gas-containing rock is as follows:
wherein the content of the first and second substances,
Kms2is the volume modulus of the saturated gas rock,
is the rate of change of gas-containing pore pressure with confining stress, KgIs the saturated gas bulk modulus.
Before executing S106, the method may further include: and obtaining a relation curve of the logging depth and the actual Poisson impedance according to the relation curve of the logging depth and the actual longitudinal wave velocity, the relation curve of the logging depth and the actual transverse wave velocity and the relation curve of the logging depth and the actual density. Wherein, can pass formula PI ═ Vp*D-1.63VsCalculating the actual Poisson impedance by D, and calculating the actual Poisson impedance by PIpIs the actual longitudinal wave velocity, VsD is the actual shear wave velocity and the actual density.
The specific process of the embodiment of the invention is as follows:
1. and generating water-containing Poisson impedance according to the water-containing logging forward modeling data acquired in advance, and generating gas-containing Poisson impedance according to the gas-containing logging forward modeling data acquired in advance.
Fig. 2 is a parameter table of water-containing logging forward modeling data and gas-containing logging forward modeling data in an embodiment of the invention. From the data in fig. 2, a plurality of aqueous poisson impedances and gas poisson impedances corresponding to a plurality of historical porosities, respectively, can be generated.
2. Generating a plurality of water-containing Poisson impedance coordinate points according to the water-containing Poisson impedance corresponding to the plurality of historical porosities, and fitting the plurality of water-containing Poisson impedance coordinate points to generate a water-containing Poisson impedance fitting function; and generating a plurality of gas-containing Poisson impedance coordinate points according to the gas-containing Poisson impedances corresponding to the plurality of historical porosities, and fitting the plurality of gas-containing Poisson impedance coordinate points to generate a gas-containing Poisson impedance fitting function.
FIG. 3 is a schematic representation of an aqueous Poisson's impedance fitting function curve and an air-containing Poisson's impedance fitting function curve in an embodiment of the present invention. As shown in fig. 3, the abscissa is the historical porosity and the ordinate is the poisson impedance. The dark dots are air-containing Poisson impedance, the light dots are water-containing Poisson impedance, the dark curve is a binomial fitting curve of the air-containing Poisson impedance, and the light curve is a fitting straight line of the water-containing Poisson impedance.
The aqueous poisson impedance fit function is as follows:
PI1＝4.2247*Por2+0.1084*Por+0.9076；
the air-borne poisson impedance fitting function is as follows:
PI2＝-1.9542*Por+0.8694。
3. the average value of the constant term of the water-containing poisson impedance fitting function and the constant term of the gas-containing poisson impedance fitting function is calculated, and the gas-water division coefficient is about 0.89.
4. And obtaining a relation curve of the logging depth and the actual Poisson impedance according to the relation curve of the logging depth and the actual longitudinal wave velocity, the relation curve of the logging depth and the actual transverse wave velocity and the relation curve of the logging depth and the actual density.
Fig. 4 is a schematic diagram of a relationship curve between a logging depth and an actual compressional velocity in an embodiment of the invention, fig. 5 is a schematic diagram of a relationship curve between a logging depth and an actual shear velocity in an embodiment of the invention, fig. 6 is a schematic diagram of a relationship curve between a logging depth and an actual density in an embodiment of the invention, and fig. 7 is a schematic diagram of a relationship curve between a logging depth and an actual poisson impedance in an embodiment of the invention, as shown in fig. 4-7, the vertical coordinates of fig. 4-7 are depths, and the unit is m. The abscissa of fig. 4 is the actual longitudinal wave velocity in km/s, the abscissa of fig. 5 is the actual transverse wave velocity in km/s, the abscissa of fig. 6 is the actual density in g/cc, and the abscissa of fig. 7 is the actual poisson impedance in km/s.g/cc.
5. Judging whether the actual Poisson impedance in a relation curve of the logging depth and the actual Poisson impedance is larger than a Poisson impedance gas-water boundary coefficient or not; when the water-containing logging depth range is larger than the poisson impedance gas-water boundary coefficient, taking the logging depth range corresponding to the actual poisson impedance as the water-containing logging depth range; and when the gas-water boundary coefficient of the Poisson impedance is smaller than or equal to the gas-water boundary coefficient of the Poisson impedance, taking the logging depth range corresponding to the actual Poisson impedance as a gas-containing logging depth range.
FIG. 8 is a schematic illustration of determining an aqueous logging depth range and a gas logging depth range in an embodiment of the present invention. The ordinate in fig. 8 is depth in m and the abscissa is the actual poisson impedance. As shown in FIG. 8, the logging depth range corresponding to the actual Poisson impedance greater than the Poisson impedance gas-water partition coefficient is a water-bearing reservoir, and the logging depth range corresponding to the actual Poisson impedance less than or equal to the Poisson impedance gas-water partition coefficient is a gas-bearing reservoir.
6. Generating a relation curve between the logging depth in the water-containing logging depth range and the actual water-containing porosity according to the water-containing Poisson impedance fitting function and the relation curve between the logging depth corresponding to the water-containing logging depth range and the actual Poisson impedance; and generating a relation curve between the logging depth in the gas-containing logging depth range and the actual gas-containing porosity according to the relation curve between the logging depth corresponding to the gas-containing Poisson impedance fitting function and the gas-containing logging depth range and the actual Poisson impedance.
In specific implementation, the actual poisson impedance corresponding to the water-containing logging depth range is taken as the actual water-containing poisson impedance, and the actual poisson impedance corresponding to the gas-containing logging depth range is taken as the actual gas-containing poisson impedance.
The relationship between actual aqueous poisson impedance and actual aqueous porosity is in accordance with an aqueous poisson impedance fitting function, so that actual aqueous porosity can be calculated from actual aqueous poisson impedance as follows:
wherein, PorwaterFor actual aqueous porosity, PIwaterIs the actual hydrous poisson impedance.
The relationship between the actual gas-containing poisson impedance and the actual gas-containing porosity conforms to a gas-containing poisson impedance fitting function, so that the actual gas-containing porosity can be calculated according to the actual gas-containing poisson impedance as follows:
Porgas＝(PIgas-0.8694)/(-0.19542)；
wherein, PorgasFor actual gas-containing porosity, PIgasIs the actual airborne poisson impedance.
FIG. 9 is a graphical representation of log depth versus actual gas porosity for an embodiment of the present invention. FIG. 10 is a plot of log depth versus actual water porosity for an embodiment of the present invention. The abscissa in fig. 9 is the actual gas porosity and the ordinate is the depth in m; the abscissa in fig. 10 is the actual water porosity and the ordinate is the depth in m. As shown in fig. 9-10, a coordinate point of the logging depth and the actual water-containing porosity can be obtained according to the corresponding relationship between the actual water-containing poisson impedance and the logging depth, and a relation curve between the logging depth and the actual water-containing porosity in the water-containing logging depth range can be obtained by connecting the logging depth and the actual water-containing porosity coordinate point; and obtaining a coordinate point of the logging depth and the actual gas-containing porosity according to the corresponding relation between the actual gas-containing Poisson impedance and the logging depth, and connecting the logging depth and the coordinate point of the actual gas-containing porosity to obtain a relation curve between the logging depth and the actual gas-containing porosity in the gas-containing logging depth range.
7. And determining a relation curve of the logging depth and the actual porosity according to the relation curve of the logging depth and the actual water-containing porosity and the relation curve of the logging depth and the actual gas-containing porosity.
FIG. 11 is a graphical representation of log depth versus actual porosity in an embodiment of the present invention. The abscissa in fig. 11 is the actual porosity and the ordinate is the depth in m. As shown in fig. 11, a union of a relation curve of the logging depth and the actual water-containing porosity and a relation curve of the logging depth and the actual gas-containing porosity is obtained, so as to obtain a relation curve of the logging depth and the actual porosity.
In summary, the method for determining the logging porosity curve of the embodiment of the invention firstly generates the water-containing poisson impedance according to the water-containing logging forward modeling data, generating gas-containing Poisson impedance according to the gas-containing well logging forward modeling data, determining the gas-water boundary coefficient of the Poisson impedance according to the water-containing Poisson impedance and the gas-containing Poisson impedance, then determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water boundary coefficient, then generating a relation curve between the logging depth and the actual water-containing porosity in the water-containing logging depth range and a relation curve between the logging depth and the actual gas-containing porosity in the gas-containing logging depth range, and finally determining a relation curve between the logging depth and the actual porosity according to the relation curve between the logging depth and the actual water-containing porosity and the relation curve between the logging depth and the actual gas-containing porosity, the method overcomes the influence of pore fluid on porosity prediction and improves the precision of predicting the porosity of the reservoir.
Based on the same inventive concept, the embodiment of the invention also provides a system for determining the well logging porosity curve, and as the problem solving principle of the system is similar to the well logging porosity curve determining method, the implementation of the system can refer to the implementation of the method, and repeated parts are not repeated.
FIG. 12 is a block diagram of a system for determining a porosity log in accordance with an embodiment of the present invention. As shown in fig. 12, the well porosity curve determination system includes:
the poisson impedance unit is used for generating water-containing poisson impedance according to the water-containing logging forward modeling data which are obtained in advance and generating gas-containing poisson impedance according to the gas-containing logging forward modeling data which are obtained in advance; the water-containing logging forward modeling data and the gas-containing logging forward modeling data correspond to historical porosity one by one;
a coordinate point generating unit, which is used for generating a plurality of water-containing Poisson impedance coordinate points according to the water-containing Poisson impedance corresponding to the plurality of historical porosities; generating a plurality of gas-containing Poisson impedance coordinate points according to the gas-containing Poisson impedances corresponding to the plurality of historical porosities;
the fitting unit is used for fitting a plurality of water-containing Poisson impedance coordinate points to generate a water-containing Poisson impedance fitting function; fitting a plurality of gas-containing Poisson impedance coordinate points to generate a gas-containing Poisson impedance fitting function;
the gas-water boundary coefficient unit is used for determining the poisson impedance gas-water boundary coefficient according to the water-containing poisson impedance fitting function and the gas-containing poisson impedance fitting function;
the depth range unit is used for determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water boundary coefficient and a pre-acquired relation curve between the logging depth and the actual Poisson impedance;
the relation curve unit is used for generating a relation curve between the logging depth in the water-containing logging depth range and the actual water-containing porosity according to the water-containing Poisson impedance fitting function and the relation curve between the logging depth corresponding to the water-containing logging depth range and the actual Poisson impedance; generating a relation curve between the logging depth in the gas-containing logging depth range and the actual gas-containing porosity according to the relation curve between the logging depth corresponding to the gas-containing poisson impedance fitting function and the gas-containing logging depth range and the actual poisson impedance;
and the logging porosity curve unit is used for determining a relation curve between the logging depth and the actual porosity according to the relation curve between the logging depth and the actual water-containing porosity and the relation curve between the logging depth and the actual gas-containing porosity.
In one embodiment, the water logging forward modeling data comprises: forward density of the water-containing reservoir, forward speed of water-containing transverse waves and forward speed of water-containing longitudinal waves; the gas-containing well logging forward modeling data comprises: the positive evolution density of the gas-bearing reservoir, the positive evolution speed of the gas-bearing transverse wave and the positive evolution speed of the gas-bearing longitudinal wave;
the poisson impedance unit is specifically configured to: establishing a water-containing Poisson impedance model;
inputting the forward density, forward velocity and forward velocity of transverse wave and longitudinal wave of water-containing reservoir into a water-containing Poisson impedance model to obtain water-containing Poisson impedance;
establishing a poisson impedance model containing gas;
and inputting the forward density of the gas-containing reservoir, the forward velocity of the gas-containing transverse wave and the forward velocity of the gas-containing longitudinal wave into the gas-containing Poisson impedance model to obtain the gas-containing Poisson impedance.
In one embodiment, the gas-water boundary coefficient unit is specifically configured to:
obtaining a constant term of the water-containing Poisson impedance fitting function and a constant term of the gas-containing Poisson impedance fitting function;
and determining the poisson impedance gas-water boundary coefficient according to the constant term of the water-containing poisson impedance fitting function and the constant term of the gas-containing poisson impedance fitting function.
In one embodiment, the depth range unit is specifically configured to:
judging whether the actual Poisson impedance in a relation curve of the logging depth and the actual Poisson impedance is larger than a Poisson impedance gas-water boundary coefficient or not;
when the water-containing logging depth range is larger than the poisson impedance gas-water boundary coefficient, taking the logging depth range corresponding to the actual poisson impedance as the water-containing logging depth range;
and when the gas-water boundary coefficient of the Poisson impedance is smaller than or equal to the gas-water boundary coefficient of the Poisson impedance, taking the logging depth range corresponding to the actual Poisson impedance as a gas-containing logging depth range.
In summary, the system for determining the logging porosity curve of the embodiment of the invention generates the water-containing poisson impedance according to the water-containing logging forward modeling data, generating gas-containing Poisson impedance according to the gas-containing well logging forward modeling data, determining the gas-water boundary coefficient of the Poisson impedance according to the water-containing Poisson impedance and the gas-containing Poisson impedance, then determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water boundary coefficient, then generating a relation curve between the logging depth and the actual water-containing porosity in the water-containing logging depth range and a relation curve between the logging depth and the actual gas-containing porosity in the gas-containing logging depth range, and finally determining a relation curve between the logging depth and the actual porosity according to the relation curve between the logging depth and the actual water-containing porosity and the relation curve between the logging depth and the actual gas-containing porosity, the method overcomes the influence of pore fluid on porosity prediction and improves the precision of predicting the porosity of the reservoir.
An embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor may implement all or part of the contents of the method for determining a porosity curve of a well log when executing the computer program, for example, the processor may implement the following contents when executing the computer program:
generating water-containing Poisson impedance according to pre-acquired water-containing logging forward modeling data, and generating gas-containing Poisson impedance according to pre-acquired gas-containing logging forward modeling data; the water-containing logging forward modeling data and the gas-containing logging forward modeling data correspond to historical porosity one by one;
generating a plurality of water-containing Poisson impedance coordinate points according to the water-containing Poisson impedance corresponding to the plurality of historical porosities; generating a plurality of gas-containing Poisson impedance coordinate points according to the gas-containing Poisson impedances corresponding to the plurality of historical porosities;
fitting a plurality of water-containing poisson impedance coordinate points to generate a water-containing poisson impedance fitting function; fitting a plurality of gas-containing Poisson impedance coordinate points to generate a gas-containing Poisson impedance fitting function;
determining a poisson impedance gas-water boundary coefficient according to the water-containing poisson impedance fitting function and the gas-containing poisson impedance fitting function;
determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water boundary coefficient and a pre-acquired relation curve between the logging depth and the actual Poisson impedance;
generating a relation curve between the logging depth in the water-containing logging depth range and the actual water-containing porosity according to the water-containing Poisson impedance fitting function and the relation curve between the logging depth corresponding to the water-containing logging depth range and the actual Poisson impedance; generating a relation curve between the logging depth in the gas-containing logging depth range and the actual gas-containing porosity according to the relation curve between the logging depth corresponding to the gas-containing poisson impedance fitting function and the gas-containing logging depth range and the actual poisson impedance;
and determining a relation curve of the logging depth and the actual porosity according to the relation curve of the logging depth and the actual water-containing porosity and the relation curve of the logging depth and the actual gas-containing porosity.
In summary, the computer apparatus of the embodiment of the present invention generates the water-containing poisson impedance according to the water-containing well logging forward modeling data, generating gas-containing Poisson impedance according to the gas-containing well logging forward modeling data, determining the gas-water boundary coefficient of the Poisson impedance according to the water-containing Poisson impedance and the gas-containing Poisson impedance, then determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water boundary coefficient, then generating a relation curve between the logging depth and the actual water-containing porosity in the water-containing logging depth range and a relation curve between the logging depth and the actual gas-containing porosity in the gas-containing logging depth range, and finally determining a relation curve between the logging depth and the actual porosity according to the relation curve between the logging depth and the actual water-containing porosity and the relation curve between the logging depth and the actual gas-containing porosity, the method overcomes the influence of pore fluid on porosity prediction and improves the precision of predicting the porosity of the reservoir.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, may implement all or part of the contents of the method for determining a porosity curve of a well log, for example, when the processor executes the computer program, the following contents may be implemented:
generating water-containing Poisson impedance according to pre-acquired water-containing logging forward modeling data, and generating gas-containing Poisson impedance according to pre-acquired gas-containing logging forward modeling data; the water-containing logging forward modeling data and the gas-containing logging forward modeling data correspond to historical porosity one by one;
generating a plurality of water-containing Poisson impedance coordinate points according to the water-containing Poisson impedance corresponding to the plurality of historical porosities; generating a plurality of gas-containing Poisson impedance coordinate points according to the gas-containing Poisson impedances corresponding to the plurality of historical porosities;
fitting a plurality of water-containing poisson impedance coordinate points to generate a water-containing poisson impedance fitting function; fitting a plurality of gas-containing Poisson impedance coordinate points to generate a gas-containing Poisson impedance fitting function;
determining a poisson impedance gas-water boundary coefficient according to the water-containing poisson impedance fitting function and the gas-containing poisson impedance fitting function;
determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water boundary coefficient and a pre-acquired relation curve between the logging depth and the actual Poisson impedance;
generating a relation curve between the logging depth in the water-containing logging depth range and the actual water-containing porosity according to the water-containing Poisson impedance fitting function and the relation curve between the logging depth corresponding to the water-containing logging depth range and the actual Poisson impedance; generating a relation curve between the logging depth in the gas-containing logging depth range and the actual gas-containing porosity according to the relation curve between the logging depth corresponding to the gas-containing poisson impedance fitting function and the gas-containing logging depth range and the actual poisson impedance;
and determining a relation curve of the logging depth and the actual porosity according to the relation curve of the logging depth and the actual water-containing porosity and the relation curve of the logging depth and the actual gas-containing porosity.
In summary, the computer-readable storage medium of embodiments of the present invention first generates the water-containing poisson impedance based on the water-containing well logging forward modeling data, generating gas-containing Poisson impedance according to the gas-containing well logging forward modeling data, determining the gas-water boundary coefficient of the Poisson impedance according to the water-containing Poisson impedance and the gas-containing Poisson impedance, then determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water boundary coefficient, then generating a relation curve between the logging depth and the actual water-containing porosity in the water-containing logging depth range and a relation curve between the logging depth and the actual gas-containing porosity in the gas-containing logging depth range, and finally determining a relation curve between the logging depth and the actual porosity according to the relation curve between the logging depth and the actual water-containing porosity and the relation curve between the logging depth and the actual gas-containing porosity, the method overcomes the influence of pore fluid on porosity prediction and improves the precision of predicting the porosity of the reservoir.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Those of skill in the art will further appreciate that the various illustrative logical blocks, units, and steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate the interchangeability of hardware and software, various illustrative components, elements, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design requirements of the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present embodiments.
The various illustrative logical blocks, or elements, or devices described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be located in a user terminal. In the alternative, the processor and the storage medium may reside in different components in a user terminal.
In one or more exemplary designs, the functions described above in connection with the embodiments of the invention may be implemented in hardware, software, firmware, or any combination of the three. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media that facilitate transfer of a computer program from one place to another. Storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, such computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store program code in the form of instructions or data structures and which can be read by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Additionally, any connection is properly termed a computer-readable medium, and, thus, is included if the software is transmitted from a website, server, or other remote source via a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wirelessly, e.g., infrared, radio, and microwave. Such discs (disk) and disks (disc) include compact disks, laser disks, optical disks, DVDs, floppy disks and blu-ray disks where disks usually reproduce data magnetically, while disks usually reproduce data optically with lasers. Combinations of the above may also be included in the computer-readable medium.
Claims (12)
1. A method for determining a porosity log, comprising:
generating water-containing Poisson impedance according to pre-acquired water-containing logging forward modeling data, and generating gas-containing Poisson impedance according to pre-acquired gas-containing logging forward modeling data; wherein the water-containing logging forward modeling data and the gas-containing logging forward modeling data are in one-to-one correspondence with historical porosity;
generating a plurality of water-containing Poisson impedance coordinate points according to the water-containing Poisson impedance corresponding to the plurality of historical porosities; generating a plurality of gas-containing Poisson impedance coordinate points according to the gas-containing Poisson impedances corresponding to the plurality of historical porosities;
fitting the plurality of aqueous poisson impedance coordinate points to generate an aqueous poisson impedance fitting function; fitting the plurality of gas-containing Poisson impedance coordinate points to generate a gas-containing Poisson impedance fitting function;
determining a poisson impedance gas-water boundary coefficient according to the water-containing poisson impedance fitting function and the gas-containing poisson impedance fitting function;
determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water demarcation coefficient and a pre-acquired relation curve between the logging depth and the actual Poisson impedance;
generating a relation curve between the logging depth in the water-containing logging depth range and the actual water-containing porosity according to the water-containing Poisson impedance fitting function and the relation curve between the logging depth corresponding to the water-containing logging depth range and the actual Poisson impedance; generating a relation curve between the logging depth in the gas-containing logging depth range and the actual gas-containing porosity according to the gas-containing Poisson impedance fitting function and the relation curve between the logging depth corresponding to the gas-containing logging depth range and the actual Poisson impedance;
and determining a relation curve of the logging depth and the actual porosity according to the relation curve of the logging depth and the actual water-containing porosity and the relation curve of the logging depth and the actual gas-containing porosity.
2. The method of determining a porosity curve for well logging according to claim 1, wherein the water-bearing well logging forward modeling data comprises: forward density of the water-containing reservoir, forward speed of water-containing transverse waves and forward speed of water-containing longitudinal waves; the gas-bearing well logging forward modeling data comprises: the positive evolution density of the gas-bearing reservoir, the positive evolution speed of the gas-bearing transverse wave and the positive evolution speed of the gas-bearing longitudinal wave;
generating the hydrous poisson impedance comprises:
establishing a water-containing Poisson impedance model;
inputting the forward density of the water-containing reservoir, the forward velocity of the water-containing shear wave and the forward velocity of the water-containing longitudinal wave into the water-containing Poisson impedance model to obtain water-containing Poisson impedance;
generating the airborne poisson impedance includes:
establishing a poisson impedance model containing gas;
and inputting the forward evolution density of the gas-bearing reservoir, the forward evolution speed of the gas-bearing shear wave and the forward evolution speed of the gas-bearing longitudinal wave into the gas-bearing Poisson impedance model to obtain the gas-bearing Poisson impedance.
3. The method of determining a porosity profile of a well as defined in claim 2, further comprising:
establishing a water-containing reservoir forward density model, a water-containing shear wave forward velocity model and a water-containing longitudinal wave forward velocity model;
inputting the historical porosity and the acquired water-containing density parameter into the water-containing reservoir forward density model to obtain water-containing reservoir forward density;
inputting the forward density of the water-containing reservoir and the obtained shear modulus of the rock skeleton into the forward velocity model of the water-containing shear wave to obtain the forward velocity of the water-containing shear wave;
inputting the rock skeleton shear modulus, the water-containing reservoir forward density and the obtained water-containing rock bulk modulus into the water-containing longitudinal wave forward velocity model to obtain a water-containing longitudinal wave forward velocity;
establishing a gas-bearing reservoir forward density model, a gas-bearing transverse wave forward speed model and a gas-bearing longitudinal wave forward speed model;
inputting the historical porosity and gas-containing density parameters into the gas-containing reservoir forward density model to obtain the gas-containing reservoir forward density;
inputting the forward density of the gas-bearing reservoir, the shear modulus of the rock skeleton and the forward velocity model of the gas-bearing shear wave into the gas-bearing shear wave forward velocity model to obtain a gas-bearing shear wave forward velocity;
and inputting the shear modulus of the rock framework, the forward density of the gas-bearing reservoir and the obtained volume modulus of the gas-bearing rock into the gas-bearing longitudinal wave forward velocity model to obtain the gas-bearing longitudinal wave forward velocity.
4. The method of determining a well-logging porosity curve of claim 3, further comprising:
establishing a water-containing rock volume modulus model and a gas-containing rock volume modulus model;
inputting the obtained rock volume modulus parameter, the frequency adjusting parameter, the saturated water rock volume modulus and the historical porosity into the water-containing rock volume modulus model to obtain the water-containing rock volume modulus;
and inputting the obtained rock volume modulus parameter, the frequency adjusting parameter, the gas saturation rock volume modulus and the historical porosity into the gas-containing rock volume modulus model to obtain the gas-containing rock volume modulus.
5. The method of determining a well-logging porosity curve of claim 1, wherein determining a poisson's impedance gas-water boundary coefficient comprises:
obtaining a constant term of the water-containing Poisson impedance fitting function and a constant term of the gas-containing Poisson impedance fitting function;
and determining the poisson impedance gas-water boundary coefficient according to the constant term of the water-containing poisson impedance fitting function and the constant term of the gas-containing poisson impedance fitting function.
6. The method of determining a well porosity curve according to claim 1, wherein determining a water-bearing well logging depth range and a gas-bearing well logging depth range comprises:
judging whether the actual Poisson impedance in the relation curve of the logging depth and the actual Poisson impedance is larger than the gas-water boundary coefficient of the Poisson impedance;
when the water-containing logging depth range is larger than the poisson impedance gas-water boundary coefficient, taking the logging depth range corresponding to the actual poisson impedance as a water-containing logging depth range;
and when the gas-water boundary coefficient of the Poisson impedance is smaller than or equal to the gas-water boundary coefficient of the Poisson impedance, taking the logging depth range corresponding to the actual Poisson impedance as a gas-containing logging depth range.
7. A system for determining a porosity curve for well logging, comprising:
the poisson impedance unit is used for generating water-containing poisson impedance according to the water-containing logging forward modeling data which are obtained in advance and generating gas-containing poisson impedance according to the gas-containing logging forward modeling data which are obtained in advance; wherein the water-containing logging forward modeling data and the gas-containing logging forward modeling data are in one-to-one correspondence with historical porosity;
a coordinate point generating unit, which is used for generating a plurality of water-containing Poisson impedance coordinate points according to the water-containing Poisson impedance corresponding to the plurality of historical porosities; generating a plurality of gas-containing Poisson impedance coordinate points according to the gas-containing Poisson impedances corresponding to the plurality of historical porosities;
a fitting unit for fitting the plurality of water-containing poisson impedance coordinate points to generate a water-containing poisson impedance fitting function; fitting the plurality of gas-containing Poisson impedance coordinate points to generate a gas-containing Poisson impedance fitting function;
a gas-water boundary coefficient unit for determining a poisson impedance gas-water boundary coefficient according to the water-containing poisson impedance fitting function and the gas-containing poisson impedance fitting function;
the depth range unit is used for determining a water-containing logging depth range and a gas-containing logging depth range according to the Poisson impedance gas-water demarcation coefficient and a relation curve between the pre-acquired logging depth and the actual Poisson impedance;
the relation curve unit is used for generating a relation curve between the logging depth in the water-containing logging depth range and the actual water-containing porosity according to the water-containing Poisson impedance fitting function and the relation curve between the logging depth corresponding to the water-containing logging depth range and the actual Poisson impedance; generating a relation curve between the logging depth in the gas-containing logging depth range and the actual gas-containing porosity according to the gas-containing Poisson impedance fitting function and the relation curve between the logging depth corresponding to the gas-containing logging depth range and the actual Poisson impedance;
and the logging porosity curve unit is used for determining a relation curve between the logging depth and the actual porosity according to the relation curve between the logging depth and the actual water-containing porosity and the relation curve between the logging depth and the actual gas-containing porosity.
8. The well-logging porosity curve determination system of claim 7, wherein the water-bearing well-logging forward performance data comprises: forward density of the water-containing reservoir, forward speed of water-containing transverse waves and forward speed of water-containing longitudinal waves; the gas-bearing well logging forward modeling data comprises: the positive evolution density of the gas-bearing reservoir, the positive evolution speed of the gas-bearing transverse wave and the positive evolution speed of the gas-bearing longitudinal wave;
the poisson impedance unit is specifically configured to: establishing a water-containing Poisson impedance model;
inputting the forward density of the water-containing reservoir, the forward velocity of the water-containing shear wave and the forward velocity of the water-containing longitudinal wave into the water-containing Poisson impedance model to obtain water-containing Poisson impedance;
establishing a poisson impedance model containing gas;
and inputting the forward evolution density of the gas-bearing reservoir, the forward evolution speed of the gas-bearing shear wave and the forward evolution speed of the gas-bearing longitudinal wave into the gas-bearing Poisson impedance model to obtain the gas-bearing Poisson impedance.
9. The system for determining a porosity profile for logging of claim 7, wherein the gas-water cut coefficient unit is specifically configured to:
obtaining a constant term of the water-containing Poisson impedance fitting function and a constant term of the gas-containing Poisson impedance fitting function;
and determining the poisson impedance gas-water boundary coefficient according to the constant term of the water-containing poisson impedance fitting function and the constant term of the gas-containing poisson impedance fitting function.
10. The system of claim 7, wherein the depth range unit is specifically configured to:
judging whether the actual Poisson impedance in the relation curve of the logging depth and the actual Poisson impedance is larger than the gas-water boundary coefficient of the Poisson impedance;
when the water-containing logging depth range is larger than the poisson impedance gas-water boundary coefficient, taking the logging depth range corresponding to the actual poisson impedance as a water-containing logging depth range;
and when the gas-water boundary coefficient of the Poisson impedance is smaller than or equal to the gas-water boundary coefficient of the Poisson impedance, taking the logging depth range corresponding to the actual Poisson impedance as a gas-containing logging depth range.
11. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program implements the steps of the method of determining a well porosity curve according to any one of claims 1 to 6.
12. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of determining a log porosity curve according to any one of claims 1 to 6.
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