Method and device for modeling pvt-parameters

FIELD: creation of machine models, at output of which calculated data is received about properties of fluids contained in oil and gas bearing collector beds.

SUBSTANCE: method and device are used for transformation of data of pressure gradient, formation pressure and formation temperature, measured by logging device on cable, to evaluation data of PVT-properties of hydrocarbon fluid, which do not depend on presence of drill mud on hydrocarbon base, without necessary taking of physical fluid samples from the well for laboratory analysis on the surface.

EFFECT: increased statistical precision of PVT-properties of formation fluids.

5 cl, 9 dwg

 

Background of invention

The present invention relates to a method for the simulated parameters defined by the relationships between pressure, volume and temperature (PVT), according to well logging data without selection of physical samples from oil and gas reservoirs. In particular, the invention relates to a computing device that receives the measurement results of the pressure and temperature produced by the descent on the cable of the hoist device, and depending on the depth of the borehole, and which generates simulated PVT parameters. In particular, the invention relates to improving the statistical accuracy of the PVT parameters with known geochemical characteristics of the fluid reservoir, through which the well.

Description of the prior art,

It is known that contained in geological reservoirs hydrocarbon fluids (liquid and gas) under high pressure (relative to atmospheric pressure), and usually have a high temperature (compared to the air temperature). At this pressure wireline fluid is initially single-phase fluid, which then releases the dissolved gas with the subsequent formation of two-phase fluid with separate gas and oil components, provided that the source pressure is their formation fluid sufficiently decreased to close to atmospheric pressure. After retrieval from the well formation fluid with a sufficiently high initial temperature with decreasing temperature and its approximation to the temperature also decreases the volume of a given mass of fluid.

Usually after drilling exploratory oil wells and found in hydrocarbon fluids carry out testing of the downhole fluid. This test usually involves the flow of well fluid to the surface, the division of oil and gas in the separator and the measurement of the flow rate of oil and gas separately and then flaring.

Samples of oil and gas also necessary for carrying out chemical and physical analysis. Such samples of formation fluids taken at the earliest possible stage of operation of the productive formation and analysis in specialized laboratories. This information is necessary for planning and development of oil fields, as well as evaluation of their productivity and control performance.

There are two ways of selecting samples:

1. Directly from the reservoir by a method of sampling fluid from downhole uncased wells and

2. Sampling fluid from the surface by means of surface recombination.

When sampling with bottom open hole wells in the well is lowered special sampler with caupolicana under excessive pressure of the sample of formation fluid, present in the wellbore. In the process of sampling the pressure support level pressure in the wellbore at which it was received from the rock surrounding the wellbore. If the pressure in the borehole at the depth of sampling exceeds the saturation pressure of the reservoir fluid, the sample will be a single-phase fluid reflecting layer fluid, i.e. aliquot part.

The selection method of surface recombination involves the selection of individual samples of oil and gas from land-based operational object (for example, gas separator). In analytical laboratories carry out the recombination of such samples in the correct proportions in order to obtain a composite fluid, which should display the layer of fluid, that represent the converted aliquot part.

Currently, the number of samplers for sampling with bottom uncased borehole, the basis of which put the total Princip includes modular dynamic plastoispytatelya (MDT) of Schlumberger, the device RCI Baker Atlas" and the device RDT company Halliburton. In General, these samplers are often called cable probowalismy layers. In a single run into the well such samplers can select multiple samples (e.g. different productive zones in squag is not).

Conventional cable aprooval layers down into the well for sampling formation fluid at the required depth, while its inner chamber opens, letting in wireline fluid, after which the chamber containing the specified volume of sample fluid, is sealed. Then aprooval raise from wells, extract a sample and send it to the analytical laboratory. Then determine the PVT properties of each sample of the fluid in the well environment.

Cable probovatel layers allow you not only to select high-quality samples to determine the PVT properties on the most promising intervals of the well, but also to receive wireline logs of the pressure gradient and the temperature profile of the well. The pressure gradient is used to determine the level mefluidide contact, the density of the formation fluid and strategies of the reservoir. As indicated above, samples of fluid taken with the help of cable oprobivala layers come in analytical laboratories for the measurement according to the method of PVT (ratios of the pressure-volume-temperature).

The current practice of logging provides a measure of pressure profiles in the set of potentially hydrocarbon-bearing zones and the selection of high-quality samples, showing the PVT properties, only the most promising intervals. The number selected is Rob is limited by the following factors:

1. the drilling time (costs)associated with the descent and ascent of the cable probovatel reservoirs;

2. the time required to reduce the amount of drilling fluid hydrocarbon-based contaminating samples and altering PVT properties; and

3. the number of available cameras probovatel for sampling.

In the past there was not an acceptable system or method that allows the results of the profile measurements of pressure and temperature, obtained by the method of logging cable probovatel layers, to predict by theoretical calculations PVT properties for samples taken in the process of logging.

The objective of the invention

The main object of the invention is the creation of an automated analytical device and method for obtaining PVT characteristics of fluids from oil and gas reservoirs according to the depth of the well based on the results of measurements of the profiles of pressure and temperature obtained with the logging device, without the need for fluid sampling.

Another object of the invention is the creation of an automated analytical device and method for obtaining PVT characteristics of fluids from oil and gas reservoirs according to the depth of the well based on the results of the measurements logging device reservoir is Alenia and temperature, as well as the pressure gradient calculated from measurements of reservoir pressure.

An additional object of the invention is to obtain PVT characteristics of formation fluids based on measured data logging device reservoir pressure, reservoir temperature and reservoir pressure gradient and data about the physical location of the well, allowing to determine the relevant geochemical parameters, thereby increasing the statistical accuracy of the PVT characteristics.

Summary of the invention

In the present invention, a method for detection and quantification or prediction of PVT properties of reservoir (i.e. properties that are defined by the relationships between pressure, volume and temperature), allowing mainly to do without sampling and analysis samples of reservoir fluids. In one embodiment, the method for determining the PVT properties of reservoir first create a model based on a set of previously received data, including the results of a number of measurements of pressure, temperature and geochemical parameters related to the various layers of the reservoir. In the wellbore passing through the investigated reservoir, carry out a number of field measurements, for example, by taking the logs of such parameters as temperature, pressure and the pressure gradient. Data such MEAs the rhenium is then combined with the model, in order to predict or determine the set of PVT parameters (characteristics of the fluid from the selected reservoir. Other parameters that can be used to determine the PVT properties or create models that are not limited to, the density of the fluid, the parameters of the parent rock, thermal maturity, biochemical degradation, viscosity, chemical properties of reservoir fluids, chemical composition.

In addition, the above tasks, as well as other features and advantages of the invention are included in the method of computing modules, the input of which data is received, reservoir pressure, reservoir temperature and reservoir pressure gradient depending on the depth of the well, and the output of which get data from any or all of many parameters such as the molecular mass of formation fluid (RF, MW), the saturation pressure (Psatand so the First module, called PVT MOD includes the equations that describe the output parameters in the form of functional dependence only on reservoir pressure, reservoir temperature and reservoir pressure gradient. The second module, called PVT MOD PLUS includes equations that describe the output parameters in the form of functional dependence not only on the reservoir pressure, reservoir temperature and reservoir pressure gradient, but also g is khimicheskikh parameters displays the type of parent rock (aromaticity), thermal maturity and biochemical degradation. To determine these geochemical parameters in the database indicating a relationship of geochemical parameters with the location of the wells, enter information about the physical location of the well. Thus, when using the PVT module MOD PLUS it as a function of depth impose six parameters, and the output as a function of depth receive any or all of the many above-mentioned parameters. For variables PVT output module PVT MOD PLUS statistical accuracy is improved compared with the parameters at the output of the PVT module MOD.

Brief description of drawings

1 shows a diagram of a sequence of operations generating modules of equations (called equations PVT MOD)assigns any or all of the parameters such as the viscosity of the formation fluid, with input parameters, reservoir pressure, reservoir temperature and reservoir pressure gradient.

figure 2 - diagram of the sequence of operations to develop a global database of the characteristics of the crude product with the aim of identifying the parameters of the aromaticity of the parent rock, thermal maturity and biodegradation depending on the location of the well,

figure 3 - chart with what the actual content of methane in the reservoir fluid, depending on the density of the formation fluid, which illustrates one of the steps of the method of obtaining the equations according to figure 1,

figure 4 - diagram illustrated in figure 3 parameters with the difference that the data point or "sample" denotes various geometric figures, depending on the type of parent rock,

figure 5 is a repetition of figure 4 except that the shading of the character indicated, thermal maturity, and it is shown that more Mature samples (indicated by darker shading) are grouped near the lower end of the curve, which proves that thermal maturity is an essential option to create an equation that establishes the relationship between the content of methane in the reservoir fluid and the formation fluid density

figure 6 is another diagram of the methane content in the reservoir fluid in the form of functional dependencies directly from the oil reservoir, which is subjected to biochemical decomposition of the samples are grouped in the area of the right lower section of the chart that proves that the equation can be further improved by including data of biochemical decomposition in equation, which relates the content of methane in the reservoir fluid and the formation fluid density

7 is a sequence diagram of an implementation of the claimed method for determining the PV parameters of hydrocarbon fluids in the rocks (formations), surrounding the borehole, using the data logging device, such as cable aprooval layers, using equation PVT MOD, created on the basis of these samples,

on Fig is a sequence diagram of an implementation of the claimed method of determination of PVT parameters of hydrocarbon fluids in the rocks (formations)surrounding the borehole, using in addition to the input parameters, is illustrated in Fig.7, also geochemical parameters obtained from the global database of the characteristics of the crude product with indication of location data and geochemical parameters according to figure 2 using equation PVT MOD PLUS created on the basis of the data samples with the addition of geochemical data, and

figure 9 schematically illustrates a system for obtaining PVT parameters of fluids solely on the basis of the data cable probovatel layers or on the basis of the data cable probovatel layers and geochemical information obtained from the location of the studied wells.

Description of the invention

The present invention relates to the creation of machine models, the output of which get calculated data about the properties of fluids contained in the oil and gas reservoirs (PVT-PVT parameters or the characteristics) without the need for laboratory analysis of samples of fluids and phase behaviour is depending on the input data. In the first module, referred to as PVT MOD, as input parameters used three types of data, each of which is determined depending on the depth of the wellbore measured spokeman on cable logging device, such as a cable aprooval layers. The second module, called PVT MOD PLUS, allows to obtain the specified output the calculated PVT data parameters through input into the equations describing the model, one or several geochemical parameters, and the proposed method assumes the use of input PVT-options MOD plus the location of the wells on the basis of which through the database get the geochemical parameters of the equation. In the preferred case in PVT module MOD PLUS use three geochemical parameters: the type of parent rock (aromaticity), thermal maturity and biochemical degradation.

Three preferred options, which are determined by the results of reservoir testing cable probowalem layers are the formation fluid density, pressure and temperature of the reservoir. The density of the formation fluid is determined by the results of measurement of the pressure gradient in the well:

where ΔR/Δz means the pressure gradient (z indicates the depth), ρfmeans the formation fluid density and g means gravitate is nnow constant. If to determine the density of the formation fluid using equation (1), the result is not affected by the presence of drilling mud oil based, which pollutes the actual samples, taken to determine the PVT parameters, and is the cause of the receipt of erroneous PVT parameters measured in laboratory conditions. In the presence of independently obtained data density of the drilling fluid hydrocarbon-based density of the formation fluid is also determined on the basis of data of a hydrostatic pressure gradient of the drilling fluid:

where ρfmean density of the formation fluid without mud,

ρmmean density of the drilling fluid hydrocarbon-based,

Δρfmean gradient formation pressure,

Δρmmeans the hydrostatic pressure gradient.

The main parameter used in computing PVT modules MOD and PVT MOD PLUS is the density of the formation fluid ρf(from equation (1)) or ρf(from equation (2)). As described below with reference to figure 1, to obtain equations PVT MOD was used based on the results of 145 report about the research in the area of the Gulf of Mexico set of PVT parameters of reservoir fluids that display a wide range of coal types is Ogorodnik fluids. In equation PVT MOD PLUS described with reference to figure 2, in addition, used geometrical parameters obtained from 3700 oil wells located around the world. Samples taken from each of those 3700 wells associated with three major geochemical parameters:

SRA - aromaticity maternal breed

TM - thermal maturity

BIO - biochemical decomposition.

Equation PVT MOD PLUS increase the statistical accuracy of the equation PVT MOD.

Figure 1 presents a diagram illustrating the sequence of the method of creating equations module PVT MOD to predict the PVT parameters. First, as shown by a rectangle 10 create a database containing the results of measurements of the PVT parameters, which ideally represent a wide range of types of fluids - from condensates of dry natural gas to heavy crude oil. After creating this database for each significant PVT parameters are correlated by means described below standard procedures.

This selects the mapped parameter for mapping, as illustrated by the rectangle 12, and "render" it via software rendering (as defined in the rectangle 14) depending on other parameters available in the database PVT. For example, if the parameter is represented in the Cartesian system the coordinates as a function of any one parameter, the importance of the additional parameters is manifested by adjusting the size, shape, color, orientation, etc. of the data points of additional parameters. The result estimates on what parameters are correlated with the variable under consideration. In the process of rendering appropriate, as indicated in box 16, divide the value of a variable into several groups in order to specify the dependencies between the correlated parameters.

After selecting the likely parameters using the software package build linear/nonlinear three-dimensional regression, as indicated in box 18, to select a specific type of correlation between the variable and the first two parameters on the results of visualization. The accuracy of the resulting equation increases by alternating additional parameters and build new regressions, as indicated by the rectangle 20. The final result of this operation is an equation with many members (parameters and coefficients), correlated with this parameter, or property.

Using this new equation, obtained at the stage indicated by the rectangle 20, create a dynamic spreadsheet data PVT properties, to calculate the parameter of interest, as indicated in box 22. the beside medium error, calculated for each data point, for the complete data set, calculate the total average absolute percentage error and the ratio of the smallest quadratic regression. To improve the final accuracy of the equations use a subroutine linear/nonlinear solutions (such as solver Solver™ company Excel), as indicated in box 24, which corrects the coefficients, which reduces the mean absolute percentage error and provides the highest regression coefficient.

All other parameters are calculated according to the similar procedures. In the calculations get a group of equations (called equations PVT MOD), in which each output parameter or to consider the option presented in the form of functional dependence on the input data, reservoir pressure, reservoir temperature and reservoir pressure gradient (on the basis of which you can calculate the density of the formation fluid ρf.).

Figure 2 presents a diagram illustrating the sequence of carrying out the proposed method of obtaining geochemical parameters improves prediction accuracy equations PVT MOD. Three preferred geochemical parameters that receive according to the present invention, are the aromaticity of the parent rock,thermal maturity, and biochemical degradation. Can be used one, two or all three geochemical parameter.

As indicated in the rectangle 26, was formed database containing 3700 results of geochemical analysis of the characteristics of crude oil around the world, including data on biomarkers of sterane and terpane, stable isotopes of carbon and oil properties. Using such data on the basis of the geological structure of each basin, from which were selected oil were formed sub-bases data specific parameters of the parent rocks (rectangle 28) and thermal maturity (30). Indicators that best describe the aromaticity of the parent rocks are the ratios of tricyclic Taranov, such as C19/C23, C24/C23, C/C25, and Pyh of Taranov, such as C31/C30 and s/C30. Indicators of thermal maturity, include the relative content of diasteranes and diahopane, as well as the ratio of tronolane. For each data set was used multivariate statistical technique, illustrated by the rectangle 32, which formed the "main component", which is a linear combination of each of these indicators. As for the aromaticity of the parent rocks, and thermal maturity of the principal components normalized to range from 0 to 1.

p> To display the biochemical decomposition of samples was obtained third geochemical parameter, as indicated in box 34. Because this option is less predictive power than the aromaticity of the parent tree or thermal maturity for presentation to use the binary system, i.e. either 0 or 1.

Named three geochemical parameter included in the database, also including PVT parameters, which are used to obtain equations PVT MOD PLUS is illustrated in figure 1 by the way. All three geochemical parameter included in the database of samples, showing the PVT parameters, indicated by the rectangle 36 figure 2.

Obtaining equations using six parameters described above demonstrated on the example of the first equation to determine the output variable of the content of methane in the reservoir fluid. The method of obtaining the equations illustrated in figure 3-6.

Figure 3 illustrates the diagram of the methane content in reservoir fluid (molar concentration) depending on the density of the reservoir oil (g/CC) results 145 lab reports research PVT parameters of the samples taken in the Gulf of Mexico. As follows from figure 3, between the content of methane in the reservoir fluid and the formation fluid density there is a General attitude that especially uragano at high methane content. However, more appropriate to consider the available data to determine whether additional parameters to improve this correlation.

Figure 4 presents the data and the scale shown in figure 3, with the difference that in this diagram the symbols of the data points marked depending on the type of parent rock. For example, the sample group SE1 (selected from marine marl bedrock) are grouped at the top of the curve.

From this observation it follows that the type of parent rock has no effect on the ratio of methane in the reservoir fluid and the density of the layer; however, to determine the reason why the characters in some samples taken from marine marl bedrock, grouped in different parts of the curve, it is required to conduct additional analysis.

Figure 5 repeats figure 4 with the difference that the characters have a hatch depending on thermal maturity. From figure 5 it follows that samples with greater maturity (indicated by symbols with the darkest shading) are grouped near the lower end of the overall curve. From this observation it follows that thermal maturity is a valuable parameter for predicting the methane content in reservoir fluid density of reservoir fluid.

Figure 6 presents the latest diagra the mA showing the proportion of methane in the reservoir fluid and the density of the formation fluid, where the largest symbols indicate samples showing biochemical decomposition. From Fig.6, it follows that samples showing biochemical decomposition, grouped in the area of the right lower lobe of the data set; this gives grounds to assume that due to the inclusion in the final equation of the member showing the biochemical decomposition, it is possible to obtain a slight improvement of the correlation.

From the foregoing it is possible using the method illustrated in figure 1, to derive a set of equations, in which the output parameters associated with the measurement results of the input parameters of the pfPresand Tres, resulting in a system of equations of the PVT module MOD. In the following next, table 1 shows the functional relationship of the input and output parameters for each equation of the system PVT MOD. It is important that each output parameter can be determined by one of the input parameters or in the form of the functional dependence of one or more input parameters and one or more previously defined output PVT parameters.

Table 1
The output PVT-Input(s) parameter(s)
The viscosity of the formation fluid (μ)ρf
The content of methane in the reservoir fluid (C1)ρfPresand Tres
The content of heptane and higher hydrocarbons in reservoir fluid (C7+)ρf
The molecular mass of formation fluid (RFMW)ρfPresand Tres
Gas-oil ratio (GOR) in single-stage instantaneous evaporationRFMW, Tres
The sulfur content in the product oil (% S)RFMW
The nitrogen content of the reservoir fluid (N2)RFMW
The volume ratio of the saturated layer (FVF)RFMW, Tres
Molecular weight of heptane and higher hydrocarbons in reservoir fluid (C7+MW)% S
Unit weight of heptane and higher hydrocarbons in reservoir fluid (C7+SG)% S
The saturation pressure (Psat)C1C7+MW; Tres
The density of the crude product in degrees American petroleum Institute (API)C7+SG
The content of ethane in reservoir fluid (C2)C1C7+
With the actual content of propane in reservoir fluid (C 3)C1C7+
The content of n-butane in reservoir fluid (nC4)C1, C7+
Table of contents i-butane reservoir fluid (iC4)nC4
The content of n-pentane in reservoir fluid (nC5)C1C7+
The content of i-pentane in reservoir fluid (iC5)nC5
The content of the hexane in reservoir fluid (C6)C1C7+
Density instantly dissolved gas (gas density)C1With2With3iC4that nC4
Gross calorific value instantly dissolved gas (BTU/standard cu.ft)Density instantly dissolved gas

In the following table 2, each output PVT-parameter is shown in the form of dependence not only on such input parameters as the pressure gradient (converted to ρf), Presand Tresbut also from geochemical parameters such as the type of parent rock (SRA), thermal maturity (TM) and biochemical decomposition of (BIO).

Table 2
The output PVT-Input(s) parameter(s)
The viscosity of the formation fluid (μ)ρf
The content of methane in the reservoir fluid (C1)ρfPresand Tres, SRA, TM, BIO
The content of heptane and higher hydrocarbons in reservoir fluid (C7+)ρf, SRA, TM

The output PVT-Input(s) parameter(s)
The molecular mass of formation fluid (RFMW)ρf, SRA, TM, Pres, Tres
Gas-oil ratio (GOR) in single-stage instantaneous evaporationRFMW, BIO
The sulfur content in the product oil (% S)RFMW, SRA, BIO
The volume ratio of the saturated layer (FVF)RFMW, Tres
The nitrogen content of the reservoir fluid (N2)RFMW, SRA
Molecular weight of heptane and higher hydrocarbons in reservoir fluid (C7+MW)% S, SRA
Unit weight of heptane and higher hydrocarbons in reservoir fluid (C7+SG)% S, SRA
The saturation pressure (Psat)C1, SRA, TM, C7+MW, Tres
The density of the crude product in degrees American petroleum and the Institute (API) C7+SG, SRA
The content of ethane in reservoir fluid (C2)C1C7+
The content of propane in reservoir fluid (C3)C1C7+
Table of contents i-butane reservoir fluid (iC4)nC4, SRA
The content of n-butane in reservoir fluid (nC4)C1C7+
The content of i-pentane in reservoir fluid (iC5)nC5, SRA
The content of n-pentane in reservoir fluid (nC5)C1C7+
The content of the hexane in reservoir fluid (C6)C1C7+
Density instantly dissolved gas (gas density)C1C2With3iC4that nC4, SRA
Gross calorific value instantly dissolved gas (BTU/standard cu.ft)Density instantly dissolved gas

Functional equations the correlation presented in table 2 are derived from the relationships given in table 1. To obtain the relationship shown in table 1, were used parameters reservoir pressure (Pres), temperature (Tres) and density (ρf), obtained on the rez is LatAm individual research reports hydrocarbon fluids of various types in the Gulf of Mexico. As indicated above, figure 3-6 clearly shows that the content of methane in the reservoir fluid (C1) not only depends on the density of the formation fluid (ρf), but also from the aromaticity of the parent tree (SRA), thermal maturity (TM) and biodegradation (BIO).

To create the equation of the relationship between C1and ρfPres, Tres, SRA, TM and BIO (for example) all the data on C1that ρfand SRA loaded into the software system with the aim of obtaining multi-component regression, called JANDEL Scientific Table Curve 3D™. Using this software get two equations (one for samples of lung formation fluid with a molecular weight of <50 g/mol, and the other for heavy samples of formation fluids with molecular weight of >50 g/mol), in which C1means a functional relationship between two main options: ρfand SRA. Then the values of the methane content in reservoir fluid C1and density ρfagain enter into the program Table Curve, this time along with the parameters of thermal maturity (TM). The resulting model provides equations containing member, showing thermal maturity (TM). The procedure is carried out again with the purpose of receiving members, showing the influence of biodegradation (BIO). Similar methods have the member is, taking into account reservoir pressure (Presand the temperature of the layer (Tres).

In addition members receive the General format of two equations for calculating the methane content in reservoir fluid (C1depending on ρfPres, Tres, SRA, TM and BIO resembles the following:

where C1means the content of methane in the reservoir fluid,

ρfmeans the formation fluid density

Presmean reservoir pressure,

Tresmean temperature of the layer,

SRA means the aromaticity of the parent tree,

TM means of thermal maturity,

BIO means the biochemical decomposition,

k1...k11mean constant values.

Then equations (3) and (4) is injected into the spreadsheet program Microsoft Excel™allowing to calculate the methane content in reservoir fluid C1for each point of the input data set, the original set of regular values take k1...k11. After calculating these values define the overall mean absolute percentage error by averaging the individual errors for each point. In addition, for a set of data to determine the regression coefficient R2using the following equation:

where C1MEAs.- the measured value of the methane content in the reservoir fluid,

With1est.- the calculated value of the content of methane in the reservoir fluid,

C1cf.- the average content of methane in the reservoir fluid.

Then using Excel solver Solver constant values of k1...k11correct, therefore, to ensure optimal matching of the experimental data up until the overall mean absolute error percentage will not be minimized, and the regression coefficient R2from equation (5) will not be maximized.

As described above have the equation PVT MOD in accordance with the functional relationship given in table 1. Input variables ρfPres, Tresand the weekend PVT-variables are assigned solely on the basis of the relationship between geochemical parameters 145 samples of reservoir oil from the Gulf of Mexico and PVT-data of reservoir fluid.

In equation PVT MOD PLUS additionally been introduced indicators of aromaticity of the parent rock, thermal maturity and biodegradation each of the 145 samples and equations are obtained in accordance with the functional relationships shown in table 2.

In Annex 1 to the description disclosed each equation, such as the present the th above equation (3), designed for PVT MOD (table 1), and PVT MOD PLUS (table 2). To determine the numerical values of each of the constant values are selected statistically significant set of samples from a given area, such as the fields of the Gulf of Mexico, and determine the constant values as described above with reference to equation (5). Based on the database GeoMarkOILS™ company GeoMark Research, Inc. (Houston, Texas) create a database of geochemical parameters depending on the location.

Figure 7 illustrates the proposed method of producing simulated PVT-based parameters data logging chart depending on the depth of the pressure gradient, Plast pressure and temperature of the reservoir. Based on the above equations PVT MOD get output parameters.

On Fig illustrated by the claimed invention is a method of obtaining the logs PVT-based parameters data logging, similar to the illustrated in figure 7, but differs in that it additionally uses information about the location of the well. To obtain values SRA, TM BIO and location of the wells is injected into a database containing geochemical parameters.

Figure 9 schematically illustrates a cable aprooval layers, such as system testing of formations cable probowalem layers productions the Schlumberger Well Services and other companies. With this logging system receive wireline logs 110 wells with known locations, information about which is conventionally denoted by the rectangle 112. Logging chart includes presented as a function of depth data, such as Pres, Tresand ρfafter calculating the density change Presdepending on the depth. Provided by computer system 120 that includes at least one (or both) of the above-described module PVT MOD (item 122) or PVT MOD PLUS (item 124). The computing system also includes in-memory database 130 data in which the location of any wells on the earth associated with at least one of the three fundamental geochemical oil parameters such as the type of parent rock (SRA), thermal maturity (TM) and biochemical decomposition of (BIO).

Entering data logging module 122 PVT MOD, get the PVT parameters of the fluid depending on the depth without the use of geochemical parameters. PVT-parameters of the fluid depending on the depth also receive by entering the data logging module 124 PVT MOD PLUS and enter at least one geochemical parameter from the group including SRA, TM, BIO, base 130 geochemical data pre-enter information about the location of the well.

In summary, what you can say, the invention relates to a method and system for predicting PVT properties of fluids and the parameters of the phase behavior or condition according to the results of standard downhole measurements using cable probovatel layers. Such measurements include measurement of reservoir pressure, reservoir temperature and pressure gradient. To the output PVT properties of fluids and the parameters of the phase behavior associated with the results of measurements of input parameters in the above system of equations PVT MOD, include one or more of the following options:

saturated pressure (point initial boiling point and point condensation, or dew);

- gas factor (GOR) in single-stage instantaneous evaporation;

- the volume ratio of the saturated layer (FVF) for single-stage instantaneous evaporation;

- the density of the formation fluid;

the viscosity of the formation fluid;

molecular mass of formation fluid;

- the composition of the formation fluid (C1-C7+N2, CO2);

- characteristics of heavy fractions of reservoir fluid (molecular weight and specific gravity7+);

- density commercial oil in degrees American petroleum Institute (API) in a single-stage instantaneous evaporation;

the sulfur content in the product oil at one stage instantaneous evaporation;

- the density of instant widelyused the gas at one stage instantaneous evaporation;

higher calorific value instantly dissolved gas.

The proposed method also provides for the prediction of PVT properties of reservoir fluid and the parameters of the phase behavior on the results of standard downhole measurements, as described above, and additionally based on the input data of geochemical parameters estimated hydrocarbon fluid. These inputs include the aromaticity of the parent rock, thermal maturity, and biochemical degradation.

The above method was used during the interpretive research with the aim of creating equations PVT MOD PLUS on the basis of geochemical parameters of reservoir oil and PVT data-properties 145 reservoir fluid samples collected in the Gulf of Mexico, as described above. According to the results of 45 regional studies were obtained indicators of aromaticity of the parent rock, thermal maturity and biodegradation, which were included in the database 3700 samples called GeoMarkOILS™ company GeoMark Research, Inc. (Houston, Texas). In other words, at a known location of the wells in the database you can find information that is specific to this location from the point of view of the above-mentioned three geochemical parameters.

PVT-settings and information about the location of the wells were centuries is found in the module 124 PVT MOD PLUS and base 130 geochemical data to obtain the PVT properties of reservoir fluid, as shown in Fig.9. Many of the samples taken cable probowalismy layers, parameters, predicted or calculated based on downhole measurements, compared with actual laboratory results of surface studies at a certain depth. Were conducted similar studies in order to compare data obtained using the method and device for predicting PVT properties of reservoir fluid, with a set of PVT parameters/geochemical parameters of samples from the offshore oil fields located to the East of Canada. Comparison results speak in favor of the data obtained during the study in the Gulf of Mexico.

APPLICATION

I. EQUATIONS CORRESPONDING to TABLE 1

The viscosity of the formation fluid μ

where k1...k6mean constant values;

the content of methane in the reservoir fluid, C1

where k7...k14mean constant values;

the content of heptane and higher hydrocarbons (heptane+) in reservoir fluid, With7+

where k15...k16mean constant values;

the molecular mass of the reservoir fluid is, RFMW

where k17...k21mean constant values;

gas-oil ratio, GOR

where k22...k25mean constant values;

the sulfur content in the product oil, % S

where k26...k27mean constant values;

the volume ratio of the saturated layer, FVF

where k28...k29mean constant values;

the nitrogen content of the reservoir fluid, N2

N2=k30+k31(RFMW)ln(RFMW),

where k30...k31mean constant values;

the content of carbon dioxide in reservoir fluid, CO2

CO2=k32+k33ρf,

where k32...k33mean constant values;

molecular weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid, With7+MW

C7+MW=k34+k35ln(% S)

where k34...k35mean constant values;

unit weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid, With7+SG

C7+SG=k36+k37(% S)0,5,

where k36...k37mean constant values;

the saturation pressure, Psat

where k38...k49mean constant values;

the density of the crude product in degrees American petroleum Institute, API

where k50...k51mean constant values;

the content of ethane in reservoir fluid, With2

where k52...k54mean constant values;

the content of propane in reservoir fluid, With3

where k55...k57mean constant values;

the content of i-butane in the reservoir fluid, iC4

iC4=k58+k59(nC4)0,5,

where k58...k59mean constant values;

the content of n-butane in reservoir fluid nC4

where k60...k62mean constant values;

the content of i-pentane in reservoir fluid, iC5

iC5=exp(k63+k64ln(nC5)),

where k63...k64mean constant values;

the content of n-pentane in reservoir fluid nC5

where k65...k67mean constant values;

the content of hexanal in reservoir fluid, With6

where k68...k70mean constant values;

density instantly dissolved gas, FGG

where

* humidity,

a k71...k72mean constant values;

gross calorific value instantly dissolved gas, FGGHV

where k73...k75mean constant values.

II. EQUATIONS CORRESPONDING to TABLE 2

The viscosity of the formation fluid μ

where k76...k81mean constant values;

the content of methane in the reservoir fluid, C1

where k82...k93mean constant values;

the content of heptane and higher hydrocarbons (heptane+) in reservoir fluid, With7+

where k94...k97mean constant values;

the molecular mass of formation fluids, RFMW

where k98...k105mean constant values;

gas-oil ratio, GOR

where k107...k112mean constant values;

sumerianasoma in commercial oil, %S

where k113...k116mean constant values;

the volume ratio of the saturated layer, FVF

FVFRFMW>50 g/mol=(k117+k118exp(ρf)+k119(SRA)3)-1,

where k117...k119mean constant values;

the nitrogen content of the reservoir fluid, N2

N2=k120+k121(RFMW)ln(RFMW)+k122ln(SRA),

where k120...k122mean constant values;

the content of carbon dioxide in reservoir fluid, CO2,

where k123...k126mean constant values;

molecular weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid, With7+MW

C7+MW=k127+k128ln(% S)+k129(SRA)0,5,

where k127...k129mean constant values;

unit weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid, With7+SG

C7+SG=k130+k131(%S)0,5+k132(SRA)3,

where k130...k132mean constant values;

the saturation pressure, Psat

where k133...k145mean constant values;

the density of commodity n the PTI in degrees American petroleum Institute, API

where k146...k148mean constant values;

the content of ethane in reservoir fluid, With2

where k149...k151mean constant values;

the content of propane in reservoir fluid, With3

where k152...k154mean constant values;

the content of i-butane in the reservoir fluid, iC4,

iC4=k155+k156(nC4)0,5+k157(SRA)0,5ln(SRA),

where k155...k157mean constant values;

the content of n-butane in reservoir fluid nC4

where k158...k160mean constant values;

the content of i-pentane in reservoir fluid, iC5

iC5=exp(k161+k162ln(nC5)+k163(SRA)0,5ln(SRA)),

where k161...k163mean constant values;

the content of n-pentane in reservoir fluid nC5

where k164...k166mean constant values;

the content of hexanal in reservoir fluid, With6

where k167...k169mean constant values;

density instantly dissolved gas, FGG

where

* humidity,

a k170...k172mean constant values;

gross calorific value instantly dissolved gas, FGGHV

where k173...k175mean constant values.

1. A method for predicting PVT properties of fluids, namely, that:

based on the results of laboratory measurements of PVT parameters corresponding to Plast pressure, the temperature of the reservoir and the density of the formation fluid, form a system of equations

created equations remain in the memory of the computing system,

receive data logging of the borehole at a particular depth, showing the reservoir pressure Presthe temperature of the reservoir Tresand the pressure gradient ΔR,

the measured pressure gradient is converted into the density of the formation fluid ρf,

in equation stored in the memory of the computing system, enter the dataset Pres, Tresand ρffor the above-mentioned depth of wells with receiving the set of data characterizing the PVT properties of the fluid, and to a certain depth of any particular well this dataset, describing the PVT properties of the fluid, form without sampling the studied fluid.

2. The method according to claim 1, wherein the set of data characterizing PVT-its the tion of the fluid, includes at least one of the following options:

the viscosity of the formation fluid (μ),

the content of methane in the reservoir fluid (C1),

the content of heptane and higher hydrocarbons (heptane+) in reservoir fluid

(C7+),

the molecular mass of formation fluid (RFMW),

gas-oil ratio (GOR) in single-stage instantaneous vaporization,

the sulfur content in the product oil (% S)

the nitrogen content of the reservoir fluid (N2),

the content of carbon dioxide in reservoir fluid (CO2),

the volume ratio of the saturated layer (FVF),

molecular weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid (C7+MW),

unit weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid (C7+MW),

the saturation pressure (Psat),

the density of the crude product in degrees American petroleum Institute (API),

the content of ethane in reservoir fluid (C2),

the content of propane in reservoir fluid (C3),

the content of n-butane in reservoir fluid (nC4),

table of contents i-butane reservoir fluid (iC4),

the content of n-pentane in reservoir fluid (nC5),

the content of i-pentane in reservoir fluid (iC5),

density instantly dissolved gas (FGG),

gross calorific value instantly dissolved gas (FGGHV).

3. The method according to claim 1, in which the PVT properties is obtained by solving at least one of the following equations:

the viscosity of the formation fluid, μ

where k1...k6mean constant values;

the content of methane in the reservoir fluid, C1

where k7...k14mean constant values;

the content of heptane and higher hydrocarbons (heptane+) in reservoir fluid, With7+

where k15...k16mean constant values;

the molecular mass of formation fluids, RFMW

where k17...k21mean constant values;

gas-oil ratio, GOR

where k22...k25mean constant values;

the sulfur content in the product oil, % S

where k26 ...k27mean constant values;

the volume ratio of the saturated layer, FVF

FVFRFMW>50 g/mol=(k28+k29exp(ρf))-1,

where k28...k29mean constant values;

the nitrogen content of the reservoir fluid, N2

N2=k30+k31(RFMW)ln(RFMW),

where k30...k31mean constant values;

the content of carbon dioxide in reservoir fluid, CO2

CO2=k32+k33ρf,

where k32...k33mean constant values;

molecular weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid, With7+MW

C7+MW=k34+k35ln(% S)

where k34...k35mean constant values;

unit weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid, With7+SG

With7+SG=k36+k37(% S)0,5,

where k36...k37mean constant values;

the saturation pressure, Psat

where k38...k49mean constant values;

the density of commercial oil in the castle is Mar American petroleum Institute, API

where k50...k51mean constant values;

the content of ethane in reservoir fluid, With2

where k52...k54mean constant values;

the content of propane in reservoir fluid, With3

where k55...k57mean constant values;

the content of i-butane in the reservoir fluid, iC4

iC4=k58+k59(nC4)0,5,

where k58...k59mean constant values;

the content of n-butane in reservoir fluid nC4

where k60...k62mean constant values;

the content of i-pentane in reservoir fluid, iC5

iC5=exp(k63+k64ln(nC5)),

where k63...k64mean constant values;

the content of n-pentane in reservoir fluid nC5

where k65...k67mean constant values;

the content of hexanal in reservoir fluid, With6

where k68...k70mean constant values;

the density you instantly what elawshea gas, FGG

where

* humidity,

a k71...k72mean constant values;

gross calorific value instantly dissolved gas, FGGHV

where k73...k75mean constant values.

4. A method for predicting PVT properties of fluids for a particular well, namely, that:

based on the results of laboratory measurements of fluids parameters corresponding to Plast pressure, the temperature of the reservoir, the density of the formation fluid, and at least one geochemical parameter corresponding to a location of the borehole, creating a system of equations

created equations remain in the memory of the computing system,

for the above wells receive data logging at a certain depth, showing the reservoir pressure Presthe temperature of the reservoir Tresand the pressure gradient ΔR,

the measured pressure gradient is converted into the density of the formation fluid ρf,

enter the information describing the location of the wells in the database, built with the possibility of relating the above geochemical parameter data about the location from the curse of samples of hydrocarbon fluids from wells, located at any point on the Earth, obtaining at least one geochemical parameter corresponding to a location of the well,

in equation stored in the memory of the computing system, enter the dataset Pres, Tresand ρfand the aforementioned at least one geochemical parameter for the above-mentioned depth of wells with receiving the set of data characterizing the PVT properties of the fluid, and to a certain depth of any particular well this dataset, describing the PVT properties of the fluid, form without sampling the studied fluid.

5. The method according to claim,4 in which geochemical parameter is the aromaticity of the parent tree (SRA).

6. The method according to claim 4, in which the location of the wells correspond to at least two of geochemical parameter, including the aromaticity of the parent tree (SRA) and thermal maturity (TM), and together with Pres, Tresand ρfin equations impose at least the parameters of the SRA and TM.

7. The method according to claim 4, in which the location of the wells correspond to at least three geochemical parameter, including the aromaticity of the parent tree (SRA), thermal maturity (TM) and biochemical decomposition of (BIO), and with Pres, Tresand ρfin equations impose at least the parameters is s SRA, TM and BIO.

8. The method according to claim 7, in which the set of data characterizing the PVT properties of the fluid, choose from the following options:

the viscosity of the formation fluid (μ),

the content of methane in the reservoir fluid (C1),

the content of heptane and higher hydrocarbons (heptane+) in reservoir fluid (C7+),

the molecular mass of formation fluid (RFMW),

gas-oil ratio (GOR) in single-stage instantaneous vaporization,

the sulfur content in the product oil (% S)

the volume ratio of the saturated layer (FVF),

the nitrogen content of the reservoir fluid (N2),

the content of carbon dioxide in reservoir fluid (CO2),

molecular weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid (C7+MW),

unit weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid (C7+SG),

the saturation pressure (Psat),

the density of the crude product in degrees American petroleum Institute (API),

the content of ethane in reservoir fluid (C2),

the content of propane in reservoir fluid (C3),

table of contents i-butane reservoir fluid (iC4),

the content of n-butane in reservoir fluid (nC4),

the content of i-pentane in reservoir fluid (iC5),

content-pentane in reservoir fluid (nC 5),

the content of hexanal in reservoir fluid (C6),

density instantly dissolved gas (FGG),

gross calorific value instantly dissolved gas (BTU/standard CFM).

9. The method according to claim 7, in which the PVT properties is obtained by solving at least one of the following equations:

the viscosity of the formation fluid μ

where k76...k81mean constant values;

the content of methane in the reservoir fluid, C1

where k82...k93mean constant values;

the content of heptane and higher hydrocarbons (heptane+) in reservoir fluid, With7+

where k94...k97mean constant values;

the molecular mass of formation fluids, RFMW

where k98...k105mean constant values;

gas-oil ratio, GOR

where k107...k112mean constant values;

the sulfur content in the product oil, % S

where k113...k116mean constant values;

the volume ratio of the saturated layer, FVF

FVFRFMW>50 g/mol=(k117+k118exp(ρf)+k119(SRA)3)-1,

where k117...k119mean constant values;

the nitrogen content of the reservoir fluid, N2

N2=k120+k121(RFMW)ln(RFMW)+k122ln(SRA),

where k120...k122mean constant values;

the content of carbon dioxide in reservoir fluid, CO2

where k123...k126mean constant values;

molecular weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid, With7+MW

C7+MW=k127+k128ln(% S)+k129(SRA)0,5,

where k127...k129mean constant values;

unit weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid, C7+SG

C7+SG=k130+k131(% S)0,5+k132(SRA)3,

where k130...k132mean constant values;

the saturation pressure, Psat

where k133...k145mean constant values;

the density of the crude product in degrees American petroleum Institute, API

where k146...k148mean constant values;

the content of ethane in reservoir fluid, C2

where k149...k151mean constant values;

the content of propane in reservoir fluid, With3

where k152...k154mean constant values;

the content of i-butane in the reservoir fluid, iC4

iC4=k155+k156(nC4)0,5k157(SRA)0,5ln(SRA),

where k155...k157mean constant values;

the content of n-butane in reservoir fluid nC4

where k158...k160mean constant values;

the content of i-pentane in reservoir fluid, iC5

iC5=exp(k161+k162ln(nC5)+k163(SRA)0,5ln(SRA)),

where k161...k163mean constant values;

the content of n-pentane in reservoir fluid nC5

where k164...k166mean constant values;

the content of hexanal in reservoir fluid, With6

where k167...k169mean constant values;

density instantly dissolved gas, FGG

where

* humidity,

a k170...k172mean constant values;

gross calorific value instantly dissolved gas, FGGHV

where k173...k175mean constant values.

10. A computer system containing

a storage device that stores the system of equations is created based on the data from laboratory measurements of PVT parameters corresponding to Plast pressure, the temperature of the reservoir and the density of the formation fluid, and

the input tool data logging, obtained at a certain depth of the well and showing the reservoir pressure Presthe temperature of the reservoir Tresand the density of the formation fluid ρfin equation stored in the storage device, receiving a set of data characterizing the PVT properties of fluids

moreover, the system is arranged to generate an output display of a set of data characterizing the PVT properties of the fluid for measuring the certain depth of any particular well without sampling the studied fluid.

11. Computing system of claim 10, in which the set of data characterizing the PVT properties of the fluid includes at least one of the following options:

the viscosity of the formation fluid (μ),

the content of methane in the reservoir fluid (C1),

the content of heptane and higher hydrocarbons (heptane+) in reservoir fluid (C7+),

the molecular mass of formation fluid (RFMW),

gas-oil ratio (GOR) in single-stage instantaneous vaporization,

the sulfur content in the product oil (% S)

the nitrogen content of the reservoir fluid (N2),

the content of carbon dioxide in reservoir fluid (CO2),

the volume ratio of the saturated layer (FVF),

molecular weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid (C7+MW),

unit weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid (C7+MW),

the saturation pressure (Psat),

the density of the crude product in degrees American petroleum Institute (API),

the content of ethane in reservoir fluid (C2),

the content of propane in reservoir fluid (C3),

the content of n-butane in reservoir fluid (nC4),

table of contents i-butane reservoir fluid (iC4),

the content of n-pentane in a formation f is the trpo (nC 5),

the content of i-pentane in reservoir fluid (iC5),

the content of the hexane in reservoir fluid (C6)

density instantly dissolved gas (FGG),

gross calorific value instantly dissolved gas (FGGHV).

12. A computer system containing

the first storage device in which is stored the system of equations, based on data of laboratory measurements of fluids parameters corresponding to Plast pressure, the temperature of the reservoir, the density of the formation fluid, and at least one geochemical parameter corresponding to a location of the well,

a second storage device that stores a database that establishes a relationship between the above geochemical parameter and the location of the selected samples of hydrocarbon fluids from wells located in any point of the Earth,

the input means into the second storage device information describing the location of a particular well, obtaining values of at least one geochemical parameter corresponding to a location of the well,

the input tool data logging, obtained at a certain depth of the well and showing the reservoir pressure Presthe temperature of the reservoir Tresand p is otnesti formation fluid ρ fand the above values of geochemical parameter in equation stored in the first storage device, receiving the set of data characterizing the PVT properties of fluids

moreover, the system is arranged to generate an output display of a set of data characterizing the PVT properties of the fluid, for a certain depth of any particular well without sampling the studied fluid.

13. The computing system according to item 12, in which geochemical parameter is the aromaticity of the parent tree (SRA).

14. The computing system according to item 12, in which the location of the wells correspond to at least two of geochemical parameter, including the aromaticity of the parent tree (SRA) and thermal maturity (TM), and together with Pres, Tresand ρfin the equations are entered at least the parameters of the SRA and TM.

15. The computing system according to item 12, in which the location of the wells correspond to at least three geochemical parameter, including the aromaticity of the parent tree (SRA), thermal maturity (TM) and biochemical decomposition of (BIO), and with Pres, Tresand ρfin the equations are entered at least the parameters SRA, TM and BIO.

16. The computing system according to item 15, in which the set of data characterizing the PVT properties of the fluid in the bran of the following options:

the viscosity of the formation fluid (μ),

the content of methane in the reservoir fluid (C1),

the content of heptane and higher hydrocarbons (heptane+) in reservoir fluid (C7+),

the molecular mass of formation fluid (RFMW),

gas-oil ratio (GOR) in single-stage instantaneous vaporization,

the sulfur content in the product oil (% S)

the volume ratio of the saturated layer (FVF),

the nitrogen content of the reservoir fluid (N2),

the content of carbon dioxide in reservoir fluid (CO3),

molecular weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid (C7+MW),

unit weight of heptane and higher hydrocarbons (heptane+) in reservoir fluid (C7+SG),

the saturation pressure (Psat),

the density of the crude product in degrees American petroleum Institute (API),

the content of ethane in reservoir fluid (C2),

the content of propane in reservoir fluid (C3),

table of contents i-butane reservoir fluid (iC4),

the content of n-butane in reservoir fluid (nC4),

the content of i-pentane in reservoir fluid (iC5),

the content of n-pentane in reservoir fluid (nC5),

the content of hexanal in reservoir fluid (C6),

the density of giovanno dissolved gas (FGG),

gross calorific value instantly dissolved gas (BTU/standard cubic foot).

17. The way to determine the PVT properties of the selected reservoir, namely, that:

(a) based on a set of previously received data, including the results of measurements of the PVT parameters appropriate Plast pressure and temperature of the reservoir, creating the model

(b) receive parameters of the reservoir, including at least the measurement results of the pressure and temperature at one or more selected depths in the wellbore corresponding to the selected reservoir, and,

(C) using the obtained parameters of the reservoir and the model, determine at least one PVT-property of the selected reservoir.

18. The method according to 17, in which the parameters of the reservoir include the density of the formation fluid.

19. The method according to 17, in which the set of previously received data additionally includes the measurement result corresponding to at least one geochemical parameter.

20. The method according to 17, in which at least one PVT-property is selected reservoir determined without sampling fluid.

21. The method according to 17, in which by combining at least one particular PVT properties and the additional reservoir model call is ktora determine a property of the formation fluid, related to the selected reservoir.

22. The method according to 17, in which the parameters of the reservoir include the pressure gradient.

23. The method according to claim 19, in which the above-mentioned at least one geochemical parameter correlated with the geographical location of the selected reservoir.



 

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1 tbl

FIELD: lubricants.

SUBSTANCE: invention relates to the field of testing petroleum derivatives, in particular to testing hygroscopicity of aviation synthetic oils, and can be utilized in institutions engaged in development and application of lubricating oils for aircraft techniques and for estimating changes in quality conditions of aviation synthetic oils from tendency of oils to water absorption under operation conditions. In a method of estimating hygroscopicity of oils from amount of absorbed water, including sampling oil, keeping sample at specified relative humidity and temperature in presence of distilled water, and then calculating amount of absorbed water using thus obtained dependence, additionally calculating content of water in initial sample (C0), specifying keeping time (t) for sample of oil at specified relative humidity and temperature, and calculating amount of absorbed water (C1) in oil sample from mathematic dependence taking into consideration experimentally found maximum water solubility constant (Cmax) and constant coefficient (ka) for particular kinds of aviation synthetic oils.

EFFECT: reduced determination time and labor expenditure for determination, increased sensitivity of method under oil operation conditions without losses in accuracy and reproducibility.

1 dwg, 3 tbl

FIELD: measurement engineering.

SUBSTANCE: method and device can be used in systems for survey, transportation and preparation of oil. Continuous and simultaneous measurement of volumetric discharge Q1 and Q2 is performed in two points standing apart along flow travel in pipeline; the measurements are carried out by means of two flowmeters. Behind the first point Q1, the local hydrodynamic disturbance is generated in flow by means of expansion of cross-section of flow. Second measurement is carried out at expanded part of flow. Availability of gas is judged from excess in setting relatively current values Q1 and Q2, which value is specified in controller to which controller the both flowmeters are connected. Device for realization of the method is made in form of insertion n the pipeline.

EFFECT: improved reliability of measurement.

2 cl, 1 dwg

FIELD: technology for diagnosing status of motor oil, possible use for determining quality of motor oil during operation and its fitness for further use.

SUBSTANCE: in accordance to method for determining content of liquid in motor oil, motor oil is heated up and by intensiveness of characteristic air bubbles, presence of liquid is evaluated, while firstly a template made of wire in form of mesh is applied to crucible of Cleveland machine, heated up with heating speed 6°C per 1 min up to 100°C, in range of temperatures 120-140°C heating is decreased down to 2°C per 1 minute, then position of cells in contour, formed by air bubbles in template, is visually memorized, further, contour is transferred over a squared paper, by squares, value of area of contour surface is calculated by its value, percentage of liquid is determined using standard depending on base for motor oil.

EFFECT: increased precision of detection of presence of cooling liquid in oils and its percentage.

3 tbl, 2 dwg

FIELD: power engineering.

SUBSTANCE: method involves 1) measuring n physical properties φi of given gas mixture at temperature T and/or single physical property φi at n different temperature values; 2) determining gas composition comprising n+1 ingredients on basis of mentioned physical properties, that is to be equivalent to the given gas mixture; 3) deducing power properties of the given mixture from given known composition of the equivalent gas.

EFFECT: simplified method; higher information capacity of property definition.

12 cl, 3 dwg, 1 tbl

FIELD: mechanical engineering.

SUBSTANCE: invention can be used for estimating contamination of diesel oil with particles of soot for replacement of oil in due time. Level of oil contamination is estimated by change of intensity of optical radiation passing through optical rod owing to complete internal reflection on interface of sensitive cylindrical surface - oil. Change of intensity is measured caused both by change of absorption in layer of penetration of radiation into oil and change of refraction index of oil at increase of concentration of soot particles in oil. Optical rod is made of optical material whose refraction index of which is greater than refraction index of engine oil under testing, ratio of length of rod to its diameter being not less than 10:1. first end face of rod square to optical axis is in contact with source and receiver of optical radiation, and second end face of rod square to optical axis is provided with reflecting mirror coating. Cleaning of sensitive surface of optical element is done by means of electrostatic field. Concentration of soot particles in oil is evaluated basing on change of measured signal relative to signal received at testing of clean oil with use of calibration relationship.

EFFECT: provision of high accuracy and reliability of evaluation of contamination of diesel oil with particles and replacement of contaminated oil in due time.

11 dwg

FIELD: measuring technique.

SUBSTANCE: method comprises steps of introducing analyzed sample in measuring cell 4 placed into cryostat-provided chamber 1; turning on laser irradiator 6 and corresponding to it optical detector 7 for passing optical beam through analyzed sample; storing intensity values of light received by optical detector 7; gradually lowering temperature in chamber 1 and then again increasing it for registering curve showing change of intensity values of light received by detector 7 as temperature function. According to registered curve crystal disappearance point is determined.

EFFECT: enhanced accuracy and reliability of measurement results.

7 cl, 4 dwg

FIELD: oil industry.

SUBSTANCE: device comprises standard tank (1) transparent for visible and microwave radiation, microwave chamber (2) made of a rectangular hollow parallelepiped, source of microwave radiation (3), illuminator (4), TV camera (5), two solenoid-operated valves (6) and (7), weight pickup (8), measuring converter (9), electronic commutator (10), analogue-digital converter (11), interface (12), and computer (13). The walls of microwave chamber (2) are provided with holes (18)-(23) for introducing and recording the radiation from microwave source (3) and for filling and empting tank (1) with the crude oil. Standard tank (1) is formed by two straight hollow cylinders of different diameters. Illuminator (4) is made of a cylindrical luminescence arc-discharge lamp mounted inside the cylinder of smaller diameter so that the cylinder and standard tank are axially aligned. The cylinder is secured from outer side of bottom (17) and top (16) walls of microwave chamber (2). Solenoid-operated valves (6) and (7) are locked.

EFFECT: enhanced precision.

6 dwg

FIELD: creation of machine models, at output of which calculated data is received about properties of fluids contained in oil and gas bearing collector beds.

SUBSTANCE: method and device are used for transformation of data of pressure gradient, formation pressure and formation temperature, measured by logging device on cable, to evaluation data of PVT-properties of hydrocarbon fluid, which do not depend on presence of drill mud on hydrocarbon base, without necessary taking of physical fluid samples from the well for laboratory analysis on the surface.

EFFECT: increased statistical precision of PVT-properties of formation fluids.

5 cl, 9 dwg

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