RU2432450C2 - Procedure for development of non-uniform massive or multipay gas-oil or oil-gas-condensate field - Google Patents

Abstract

FIELD: oil and gas production.

SUBSTANCE: procedure consists in drilling boreholes, in recovery of core, in geophysical survey, in testing and in hydro-dynamic survey of separate intervals by thickness of cross-section. According to the inventions database is created on results of measurements of various geo-physical parametres accepted for each region for each 0.05-0.15 m of pay thickness. Parameters with asymmetrical logging normal distribution are converted to normal distribution; all parametres are standardised by subtraction of average and by division to mean square deviation. There is made hierarchic procedure of classes arrangement consisting in successive interlayers uniting in such a way that obtained classes have minimal parametres spread around centre - dispersion. Ranges of changes and average values of these parametres for each singled out class of pays are calculated. There is determined nature of lithology, filtration-capacitive properties and fluid saturation of each class on qualitative level with consideration of fundamental links of these parametres and mineral element composition of rock. There are additionally used results of core analysis, of tests and hydro-dynamic survey in intervals of separate classes-pays; the said characteristics are determined at quantitative level. Singled out classes between boreholes are correlated. There is built geological-hydrodynamic model of producing deposit on base of which there is evaluated efficiency of system of development for various versions of inclusion of singled out classes into operational objects. There are made calculations of process indices of development with determination of levels of hydrocarbon extractions under various modes and there are evaluated prognosis coefficients of oil extraction for separate operational objects and field in whole. The best version is realised in practice.

EFFECT: differentiation of non-uniform massive or multi-pay producing cross section represented with non-collectors and collectors with various lithology and fluid saturation into typical intervals - classes-pays in each borehole using data of all performed complex of survey.

2 cl, 1 ex, 8 tbl, 10 dwg

Description

The invention relates to the oil and gas industry and may find application in the development and development of heterogeneous massive or multi-layer gas-oil or oil-gas condensate fields.

There is a method of developing heterogeneous massive or multi-layer gas-oil or oil and gas condensate fields by creating independent production facilities, including reservoir reservoirs with "close" reservoir properties and saturated with hydrocarbons with "close" characteristics, using data from geophysical surveys (GIS), geological -technological studies (GTI), core analysis, formation fluids, reservoir test results and their hydrodynamic studies (GDI) (RF Patent No. 2346148, published. 02.10.2009).

The known method does not allow to formalize the process of partitioning the section and objectively distinguish in the section of the deposit formations with "close" FES and saturated hydrocarbons with "close" characteristics, because:

1. A definition with “close” properties is of a qualitative nature;

2. Often, certain geophysical research methods are ineffective for geological and technological reasons (dense rocks with high resistance, fractured and cavernous rocks, strong absorption of flushing fluid, etc.);

3. The core is not selected from each well; its removal is often insufficient;

4. Tests and hydrodynamic studies cover in different cases different intervals and thicknesses of the reservoir and average filtration characteristics of the entire test (research) interval are evaluated;

5. The results of solving the problem of partitioning a section depend on the professionalism of the performers.

Therefore, at the initial stage of field development, when basic decisions are made that determine the principles of development for the entire period, such as the allocation of production facilities and the creation of systems for their development, information support is inadequate to the complexity of heterogeneous massive or multi-layer deposits. The consequence is incomplete coverage of the displacement process in terms of thickness and volume of production facilities and the entire field, low hydrocarbon recovery rates.

Closest to the proposed invention in technical essence is a method that includes drilling wells with coring and conducting a standard GIS complex for a given geological section, analyzing the core and creating a database for the porosity and permeability for the core of the field, identifying geological objects by the percolation index with a high degree of correlation for groups of reservoirs having some structural features of the pore space structure, and determination of reservoir permeability, using zuya resistivity diagrams resistivity logging (RF patent №2211329, publish 27.08.2003, the -. the prototype).

The known method does not allow to differentiate the section of each well drilled in the field with heterogeneous massive or multilayer productive deposits, but serves only to increase the accuracy of determining one parameter - permeability coefficient from the logging results using petrophysical dependencies constructed with preliminary identification of reservoir groups that differ in structure pore space. The known method cannot be applied to fractured and cavernous reservoirs, because for them, core parameters of porosity and permeability do not adequately characterize the capacitive and filtration characteristics of the entire reservoir. In addition, the known method is not focused on using the full potential of the currently available GIS methods.

The proposed method solves the problem of differentiating a heterogeneous massive or multi-layer productive section, represented by non-reservoirs and reservoirs with different lithology and fluid saturation into characteristic intervals-classes of formations in each well, using data from the entire well logging system performed.

The problem is solved in that in a method for developing heterogeneous massive and multi-layer gas-oil or oil-gas condensate fields, including drilling wells, conducting a complex of geophysical surveys, according to the invention, a database is created by measuring various geophysical parameters adopted for each region, for example, electrical, radioactive, wave , gas logging for each 0.05-0.15 m of formation thickness, parameters with asymmetric (lognormal) distribution are converted to normal Allocation of the parameters is standardized by subtracting the mean and dividing by the standard deviation, after which they perform a hierarchical class construction procedure consisting in sequentially combining interlayers in such a way that the resulting classes have a minimum dispersion of parameters around the center (variance), highlighting the sharpness of dispersion that is natural for a given section number of classes, which, depending on the heterogeneity, total thickness and multi-layer nature of the section and the number of fluid phases, can be up to 8-10 s geophysical parameters differing for them, calculate the ranges of variation and average values of these parameters for each selected class of formations and, taking into account the fundamental relationships of these parameters with the mineral and elemental composition of rocks, determine the nature of lithology, filtration-capacitive properties and fluid saturation at a qualitative level using additional data according to the core, tests and hydrodynamic studies performed in the intervals of certain distinguished classes - at a quantitative level, conduct to correlation of distinguished classes between wells, a geological and hydrodynamic model of a productive reservoir (field) is built, on which the effectiveness of the development system is assessed for various options for incorporating the distinguished classes into production facilities by calculating technological development indicators with determining hydrocarbon production levels at depletion and injection modes of displacing agents with an estimate forecast oil recovery coefficients of individual production facilities and the field as a whole and the best option p Alize in practice.

SUMMARY OF THE INVENTION

In well-known technical solutions for the exploration of a section of a field, the core analysis results, as a rule, taken during drilling of the first exploratory wells, are used as basic information. The volume of core samples is almost always limited not only by the number of wells, but also by section because of its poor removal. The results of the determination of reservoir properties by core do not adequately reflect the characteristics of the rocks in the reservoir conditions, especially in the presence of fracturing, because there is a change in its properties during sampling, removal to the surface in connection with a change in thermobaric conditions, as well as the preparation of samples for analysis. However, the data obtained on such distorted material are then used to construct the petrophysical dependences of “core-core” and “core-GIS” and subsequent interpretation of the data of geophysical studies of wells (GIS) of the entire field or even a group of fields. According to a well-known solution, the porosity-permeability dependences constructed for such individual information bases for individual groups of reservoirs contain the above errors and do not allow obtaining adequate parameter values for specific wells and reasonably combine them into production facilities for independent development, which leads to reduce the coverage of formations by the process of displacement of hydrocarbons in thickness and area and to reduce the coefficient of hydrocarbon recovery.

In the known technical solutions, there is no formalized integrated use of all measurement data by geophysical methods in the well. Meanwhile, direct readings of the readings of electrical, radioactive, nuclear-physical, geological and technological measurements carry multiparameter information about the structural features of the reservoirs, their filtration-capacitive properties and the nature of fluid saturation.

In the proposed method, all parameters of geophysical measurements in the well are comprehensively analyzed over the entire productive section of the field with a step of 0.05-0.15 m with the allocation of interval classes that differ in their physical properties and the nature of fluid saturation. The subsequent use of these results in the identification of independent production facilities and their development by the most optimal impact methods for the characteristics of each of these production facilities allows increasing the hydrocarbon recovery coefficient in comparison with the known technical solutions. This goal is achieved by the fact that, in contrast to the known method of developing heterogeneous massive or multi-layer gas and oil and oil and gas condensate fields by drilling wells, conducting a complex of geophysical surveys, selective coring, testing and hydrodynamic studies of individual intervals along the thickness of the section of the wells and identifying production facilities with "close »Characteristics, create a database of parameters of all performed geophysical measurements in the well with their quantitative values with increments of 0.05-0.15 m along the section. These parameters can be the results of electrical measurements (apparent resistance - CS, natural potential - PS, induction resistance - IR, etc.), radioactive (gamma-ray log - GC, neutron gamma-ray log - NGC, spectral gamma-ray log - GC, content radioactive elements - potassium, thorium, uranium, etc.), wave (interval travel times of longitudinal and transverse waves - DTP and DTS and Lamb-Stoneley waves - DTST, attenuation coefficients of longitudinal, transverse and Lamb-Stoneley waves - ALPHAP, ALPHAS, ALPHAST etc.), gas logging (content H _4, C ₂ H _6, C ₃ H _8, C ₄ H _10, C ₅ H _12, C ₆ H ₁₄ and the total gas content), as well as modern nuclear physics (pulsed neutron-gamma logging - INGK, the carbon - oxygen logging - s / o, etc.). The distribution of each parameter is checked for normality, and those that have an asymmetric distribution are converted to normal, for example, by logarithm, standardize all parameters by subtracting the mean and dividing by the standard deviation, and then perform a hierarchical class construction procedure consisting in sequentially combining layers, starting with their minimum number, so that the classes obtained have a minimum spread of parameters around the center (variance), highlighting in sharp Ost natural dispersion for a given number of classes of the section, which, depending on the inhomogeneity and the total thickness of the multilayered and the number section of the fluid phases may amount to 8-10 with differing for their geophysical parameters. The accuracy of classifying individual layers with a thickness of 0.05-0.15 m to one or another class is up to 95% or more. The ranges of variation and the average values of these parameters for each selected class of formations are calculated. A comparative analysis of the average values of geophysical parameters for the selected classes and, taking into account the fundamental relationships of these parameters with the mineral and elemental composition of rocks, the nature of fluid saturation, determine the lithology, structure and reservoir properties of reservoirs, types of fluid-saturated reservoirs at a qualitative level using limited core data, tests and hydrodynamic studies carried out in the intervals of certain distinguished classes of formations - at a quantitative level. Correlation of the identified and qualitatively and quantitatively stratified formations in the form of classes between the wells is performed, which provides a reliable basis for constructing a 3D geological and hydrodynamic model of the field, filling it with the physicochemical properties of the fluids according to PVT studies, on which variant calculations of technological parameters are performed field development under various schemes for the formation of production facilities, i.e. with different compositions of production facilities, including in different combinations these or those classes of formations in the context of the field. The number of filtration intervals - classes allocated during multidimensional classification - depends on the heterogeneity, total thickness and multilayerness of the section and the phase state of the formation fluid, and the number of production facilities depends on the expected oil recovery coefficients. The best combinations of formations in production facilities by their number, characteristics, as well as technological indicators - oil recovery coefficients - are put into practice.

Concrete example

Oil and gas condensate field N is at the exploration and development stage. The productive section is characterized by a complex geological structure. The main productive Riphean deposits from the point of view of obtaining reliable results with a comprehensive interpretation of well logging data also belong to the category of complex ones, which is due to the multicomponent composition of the rock skeleton, the complex structure of the capacitive space, and the low values of the filtration-capacitive properties (FES): extremely low range of variation of the coefficient of total porosity (0.1-3%) is commensurate with the absolute error in determining this parameter by radioactive and acoustic methods (2-2.5%).

The lithological composition of Riphean reservoirs is heterogeneous (dolomite-quartz-clay). The structure of voids is complex (pores, cavities, cracks). The reservoirs are hydrophobic, which leads to their high electrical resistance - up to 5000 Ohm · m according to lateral logging. In this context, the electric GIS methods are practically ineffective - PS, MK, BMK, BKZ, IK, DK. In the intervals of the reservoirs, a clay crust does not form during drilling.

There is a complex filtration system of collectors. Macrocracks that provide the highest flow rates of wells cannot be taken into account when constructing a reservoir model from core data. In such conditions, well-known methods of well logging and core analysis practically do not allow differentiating a well section. The geophysical characteristics of the rocks often look quite homogeneous and do not reflect changes in their real properties.

Some characteristics of one of the deposits of the field are given in Table 1.

According to the proposed method, using parameter readings for a complex of geophysical research methods, the results of some of their transformations, as well as GTI data obtained from the TK-505 well, a database was created to perform multi-parameter classification of the well section. The database used included more than 2000 rows in depth over 29 variables (Table 2).

The main characteristics of the distribution of parameters are given in table.3.

A number of parameters, the distribution of which did not obey the normal law, were converted to bring them to a lognormal form, and were standardized by subtracting the mean and dividing by the standard deviation (Table 4).

One of the statistical methods, the hierarchical classification method, was applied to the obtained standardized values. The well classification tree is shown in FIG.

The method consists in hierarchical pairwise merging of classes (clusters), starting with classes consisting of a single element (in our case, a set of parameters related to the same depth). Classes for merging are chosen so that the variance (scatter around the average obtained by merging the class) is minimal. The method assumes the same distribution of all parameters and is sensitive to the presence of large values (asymmetric distribution), so all parameters are first converted to a symmetric distribution that is closest to normal, for example, logarithm. The natural number of classes for this section, corresponding to the selection of parameters that are approximately the same in characteristics and differ from each other in the set of parameters, is selected based on the analysis of the merger tree, on which the vertical axis corresponds to the variance: the number of classes at which a sharp increase in dispersion begins, means a merger of dissimilar the aggregate characteristics of the classes and can be clearly seen in figure 1: when divided into 5 or fewer classes, the variance increases.

Classification options were considered with a separation from 2 to 8 classes. Below, we illustrate the application of the method using an example with the allocation of 8 classes. A description of each class is carried out according to the parameters used for classification. An example of such a description is given for the option with the allocation of 8 classes and a limited number (9 of 29) of the parameters (figure 2).

In the drawing, the lower and upper boundaries of the rectangle correspond to 25% and 75% of the quantiles of the distribution (the rectangle contains 50% of the sample), the point in the rectangle shows the median as the most reliable estimate of the true average, horizontal lines (to which the dashed lines go) show confidence boundaries for the sample corresponding to standard deviation; anything that goes beyond confidence limits is considered outliers and is shown with round icons. Below are the numbers of classes for which an estimate was constructed for the corresponding variables. The analysis of this information allows us to assess the degree of difference of various parameters between classes, the scatter of these parameters, etc.

Figure 3 shows the results of the breakdown of the section of the well TK-505, in table 5 - the average values used in the classification of parameters for each class with different options for their allocation (from 2 to 8).

Taking into account the fundamental relationships of these parameters with the mineral and elemental composition of the rocks, a semantic interpretation of the selected classes (intervals) along the TK-505 well section is performed. We give as an example the option of allocating 8 classes (figure 4).

Vendian deposits (up to 2340 m), represented by the Katanga (interval 2256-2316 m) and Oskobin formations (depth interval 2316-2340 m), belong to classes 1.5 and a little 2. In terms of material composition (the ratio of the main rock-making components: calcite, dolomite, inorganic residue - clay, quartz) rocks belonging to class 1, are clay with carbonate cement (7: 17: 51.8); class 5 is similar to 1 and is represented by the ratio (1.6: 1.2: 20.4). The rocks of class 2 (4.9: 44.2: 19.1) have high carbonate content. The high clay content of classes 1 and 5 is also confirmed by the maximum (among the classes) content of potassium, thorium and uranium (K = 1.195 ÷ 1.895, Th = 2.026 ÷ 3.365, U = 2.39 ÷ 2.814).

The rocks belonging to class 2 are less radioactive (K = 0.1917, Th = 0.5868, U = 0.5843) (see Table 5).

The values of total hydrogen content (W) in classes 1, 5 are maximum and correlate with the concentrations of Th and K, the minimum values of IR (electrometry) indicate the presence of clay in the classes under consideration.

It is characteristic that the angles of incidence of clay deposits (classes 1, 5 have values of 10.73 ÷ 12.9 °, dolomites of class 2 - 30.76 ° (they have angular disagreement inherited from Riphean deposits).

According to the total gas indication, the rocks belonging to class 5 are the worst. The rocks of classes 1 and 2 have approximately equal indicators, an order of magnitude higher than class 5. The latter can be interpreted as gas-bearing deposits.

Riphean deposits (below 2340 m) are represented by classes 2, 3, 4, 6, 7, 8. Deposits of class 6 (interval 2467-2500 m) in terms of the content of the main mineral components (6.5: 84.6: 8.3) are to the purest dolomites. Class 4 rocks (intervals 2405-2435 and 2445-2451) can be attributed to calcareous silicified dolomites (33.2: 60.3: 6.4). The intervals of the rocks of class 8 (intervals 2433-2446 and 2450-2457 m) have the ratio (9.1: 59.2: 31.7) - bitumen (or quartz-containing) dolomite differences. Deposits of classes 3 (intervals 2340-2360 m with the inclusion of rocks of class 2, and 2385-2396 m) and 7 (interval 2358-2405 with the inclusion of class 3) have comparable amounts of calcite and dolomite, but differ in inorganic residue - possibly the ratios are represented by dolomites high in quartz. According to the description of the samples of stone material, deposits of classes 3, 7 are dolomites, broken by a network of cracks and caverns. There are breccias healed with iron hydroxides and secondary dolomite, as well as black carbonaceous matter.

In this case, deposits of classes 3 and 7 are confined to the roofing part of the Riphean, where they practically dominate to a depth of 2405 m. Deposits of classes 4 and 8 prevail in the depth range of 2405-2458 m. Below to a depth of 2468 m - class 2. In the depth range of 2467 -2500 - Class 6 sediments.

Classes 7 and 3 are located above the oil-saturated part and are characterized as gas-saturated. Class 6 rocks have the lowest resistivity values, from which mineralized water with a significant flow rate was obtained.

The maximum Est values characteristic of compacted carbonates (9.18 ÷ 9.22 * 10 ⁵ n.m.) are confined to classes 4 and 8 and the minimum values Δtp and Δts (138.4 ÷ 138.3 μs) belong to them. / m and 258.3 ÷ 258.4 μs / m), which also indicates the very low reservoir properties of these classes; judging by the value of W (2.11-2.14%), rocks of classes 4 and 8 correspond to the cavernous-fractured type, because a sharp azimuthal disagreement (almost 180 °) of the underlying rocks of class 8 with class 4 (DA varies from 63.4 to 215.1 °) at close angles of incidence of 25.86 ÷ 26.89 ° is a prerequisite for the destruction of the rock monolith; according to the values of the total gas indication, the carrier of hydrocarbons and reservoir properties are most likely to be deposits of class 4 rather than 8, in which case the water occupying the fissure-cavernous space of rocks of class 6 is blocked at the depths of 2456 due to the angular disagreement of deposits of classes 8-4 and the presence of dense dolomites of class 2 -2468 m; rocks of classes 3, 4, 7 are clearly oil and gas containing strata. Class 6 rocks are water saturated.

Kern characterized a relatively small part of the SLE section. TK-505 (see figure 4). As can be seen, core porosity is very poorly differentiated. Only on the border of the Vendian and Riphean deposits is a layer of highly heterogeneous rocks classified as class 1 distinguished - clay with carbonate cement (calcite: dolomite: inorganic residue - clay, quartz - in the ratio of 7: 17: 51.8). These or those classes of formations are described by the content of mineral components, using core analysis data, where it is selected.

Tests and field-hydrodynamic studies of 5 intervals were carried out, which coincide with different distinguished classes of formations (see figure 4). According to their results, a quantitative characteristic of these classes of formations is obtained: class 6 — water-saturated reservoirs; class 1 - non collectors without inflow; classes 3 and 7 are oil and gas saturated with different gas contents and classes 4 and 8 are mainly oil saturated. Filtration characteristics are also determined (Table 6).

The resolution of the proposed classification method is clearly demonstrated with a sequential increase in the number of distinguished classes (see figure 3). So, when distinguishing 2 classes, the Riphean and Vendian deposits were clearly separated (section at a depth of 2340 m); 3 classes - the Riphean was divided into the oil and gas condensate part (2340-2454) and water-saturated (2454-2500); 4 classes - gas-saturated and oil-saturated intervals (2440-2407 and 2407-2454) were divided. Note that there is a transition zone between parts of the section with different fluid saturation, where adjacent classes overlap. This is another confirmation of the reliability of the section of the well. With an increase in the number of classes, structural features of collectors, etc., begin to appear. It is clear that each option can be analyzed, as described above with the option of distinguishing 8 classes.

In the composite model of the TK-505 well section for lithology and fluid saturation (see Fig. 4), columns 1-4 present the results of standard well logging and core analysis. It can be seen that the dismemberment of the section in terms of parameters and fluid saturation is very uncertain. The section differentiation according to the proposed method is clearer both in terms of fluid saturation and reservoir characteristics (columns 5-7) (a detailed description was above). Such information obtained from a group of wells allows us to correlate between them by classes (formations) and build a geological and hydrodynamic model of the field to perform multivariate technological calculations of development indicators for the forecast.

The most important advantage of the proposed method lies in the fact that the results confirmed by tests and hydrodynamic studies on the nature of fluid saturation and productive characteristics in small intervals of a section can be extended to large thicknesses assigned to one or another class of formations, including productive formations and interlayers that were missing in the standard interpretation .

In the given execution example, having the classification results for only one well, the constructed geological and hydrodynamic model is conditional.

Other initial data for modeling, including the properties of the fluids, are accepted by the subsoil user.

The hydrodynamic model was built using the Eclipse 2003A simulator based on the geological model created in the Petrel 2005 package. The mesh of cells has a dimension of 17 × 10 × 30. The total number of cells is 5100. The simulation grid is described using corner point geometry. The mesh sizes in the horizontal plane are 100 m. The grid is divided into 30 layers, the vertical mesh size is 5.4 m (FIG. 5). When creating the model, a set of functions of pseudo-compositional modeling was used:

- PVTG (PVT condensate properties),

- PVTO (PVT properties of gas dissolved in oil),

- BOGI (dependence of the volumetric coefficient of gas saturated oil on pressure),

- RSGI (dependence of the gas factor on pressure),

- BGGI (dependence of the volumetric coefficient of the condensate on pressure),

- RVGI (dependence of the amount of condensate on pressure).

The initial distribution of model properties was calculated by the method of sequential Gaussian modeling (Sequential Gaussian Simulation).

VNK was adopted at a depth of 2458 m. GOC at a depth of 2404 m. The initial reservoir pressure was 21.9 MPa.

3 modeling options are considered:

- option 1 - the selection of oil from the oil-saturated part of the reservoir with the simultaneous injection of gas into the gas cap above the mark of the GOC;

- option 2 - the selection of oil from the oil-saturated part of the reservoir with the simultaneous injection of water into the aquifer below the VNK mark;

- option 3 - selection of oil from the oil-saturated and gas from the gas-saturated part with the injection of water below the BHC and dry gas above the BHC (cycling process).

The classes of formations involved in these options and the intervals of their occurrence are given in Table 7. 6 is a resulting graph showing the dynamics of the oil recovery coefficient for different development options: at the end of the billing period, the oil recovery coefficient values for options 1, 2 and 3 are, respectively, 0.360; 0.237 and 0.414. Worst development result for option 2 with water injection; the best one, according to option 3, by separating the oil-saturated and gas (condensate) -saturated sections of the section into separate operating facilities. Condensate production volumes are not shown. They still improve the performance of 3 options. It is assumed that after the depletion of oil reserves, gas will begin to exhaust gas.

However, the most effective will be the implementation of the 3rd option by drilling horizontal wells (horizontal wells) in the intervals of the reservoir classes (Table 8). Since the location of the wellbore from the water and gas-oil contacts and reservoir properties of the formations along which the horizontal wellbore is of prime importance when conducting a wellbore, the use of the results of multi-parameter classification of the section plays a huge role in optimizing the well profile. A comparison of the simulation results of the development process with vertical or horizontal wells in the conditions of the analyzed field N showed that the oil recovery coefficient can be up to 20 points higher than vertical ones. In these calculations, it was assumed that the length of the well is 700 m, the wellbore is oriented perpendicular to the main direction of fracture of the reservoirs. The oil recovery coefficient calculated in the project document for the development of the field is 38.9%, which is significantly lower than the value achieved by the proposed method (41.4 + 20 = 61.4%).

Table 1 Indicators Value Average depth, m 2008 The average effective gas-saturated thickness, m 97.8 Porosity,% 0.97-1.37 The average oil saturation of the reservoir, the share of units 0.512-0.890 Permeability, mdarsi 1.7-8.4 Sandiness coefficient, fractions of units 0.57 The coefficient of dissection, the share of units 42.0 Initial reservoir temperature, ° C 30,0 Initial reservoir pressure, MPa 21.1 Oil viscosity in reservoir conditions, MPa · s 1.34 The density of oil in reservoir conditions, kg / m ³ 0.713 Saturation pressure of oil with gas, MPa 21.1 Gas content of oil, m ³ / t 174

table 2 No. p / p Title Units rev. Description one Dtp μs / s Longitudinal Wavelength 2 ALPHADIP1 1m Dipole longitudinal wave attenuation coefficient 1 3 ALPHADIP2 1m Dipole longitudinal wave attenuation coefficient 2 four DTS μs / m Shear Wave Interval 5 ALPHAP 1m Longitudinal wave attenuation coefficient 6 ALPHAS 1m Shear wave attenuation coefficient 7 DTST μs / m Lamb-Stoneley Wave Interval Run Time 8 Est conv. units Lamb-Stoneley Wave Energy 9 ALPHAST 1m Lamb-Stoneley wave attenuation coefficient 10 Pota % Potassium concentration eleven Thor PPM Thorium concentration 12 URAN PPM Uranium concentration 13 Dtsf μs / m Shear Wave Interval Time fourteen DTLM μs / m Interval travel time of the model wave fifteen W % Total hydrogen content,% 16 DTDIP1 μs / m Shear Wave Interval DIP1 17 DTDIP2 μs / m Shear Wave Interval DIP2 eighteen Dip GRAD Angle of incidence, degrees 19 DA GRAD Azimuth of a fall, degrees twenty ADIP GRAD Apparent angle of incidence, degrees 21 AZAP GRAD Apparent azimuth of fall, degrees 22 Methan % rel Methane 23 Ethan % rel Ethane 24 Propan % rel Propane 25 Butan % rel Butane 26 Penthan % rel Pentane 27 Gexan % rel Hexane 28 Gasum % Total gas 29th IK Ohm m Induction Logging

Table 4 Parameter Average SKO Parameter Average SKO Dtp 0.881 0.006 DTDIP1 1.969 0.057 ALPHADIP1 2.489 1.64 DTDIP2 2.109 0.055 ALPHADIP2 2.637 1.884 Dip 3.137 0.709 DTS 1.802 0.065 DA 159.868 95.747 ALPHAP 1.995 0.909 ADIP 3.155 0.685 ALPHAS 2.312 1.933 AZAP 181.839 105.873 DTST 704.607 11.129 Methan -4.552 1.529 Est 450.326 71.808 Ethan -6.653 1.112 ALPHAST 3.362 0.58 Propan -8.7 1.563 Pota -1.27 0.815 Butan -7.771 0.943 Thor -0.263 0.881 Penthan -5.863 0.665 URAN -0.401 0.827 Gexan -4.236 0.515 Dtsf 1.924 0.07 Gasum -3.32 0.742 DTLM 706.711 9.302 IK 82.885 32.398 W 1.091 0.727

Table 7 Option Technology Classes Cut Intervals one oil extraction 4.8 2404-2434; 2446-2451; 2434-2446; 2451-2458 gas injection 3 2341-2359 2 oil extraction 4.8 2404-2434; 2446-2451; 2434-2446; 2451-2458 water injection 6 2468-2500 3 gas extraction 3,7 2386-2396; 2359-2386 oil extraction 4.8 2404-2434; 2434-2446 gas injection 3 2341-2359 water injection 6 2468-2500

Table 8 Well designation Formation class Perforation interval, m Gas producing 7 2359-2386 Gas injection 3 2341-2359 Oil producing four 2404-2434 Water injection 6 2468-2500

Claims (2)

1. A method of developing a heterogeneous massive or multi-layer gas-oil or oil-gas condensate field, including drilling wells, coring, conducting a complex of geophysical studies, tests and hydrodynamic studies of individual intervals along the thickness of the section, characterized in that they create a database of different measurement results accepted for each region of geophysical parameters for each 0.05-0.15 m of formation thickness, parameters with asymmetric lognormal distribution transform to distribution, standardize all parameters by subtracting the mean and dividing by the standard deviation, and then perform a hierarchical class construction procedure consisting in sequentially combining interlayers in such a way that the resulting classes have a minimum dispersion of parameters around the center - variance, highlighting a sharp increase in variance that is natural for a given section number of classes with different geophysical parameters, calculate the ranges of variation and average values of these parameters for I of each selected class of formations, taking into account the fundamental relationships of these parameters with the mineral and elemental composition of rocks, determine the nature of lithology, filtration-capacity properties and fluid saturation of each class at a qualitative level, additionally use the results of core analysis, tests and hydrodynamic studies in the intervals of individual classes of formations and the indicated characteristics are determined at a quantitative level, the selected classes are correlated between wells, geological and hydrodynamic are built a model of a productive reservoir, on which the effectiveness of the development system is assessed for various options for incorporating the allocated classes into production facilities by calculating technological development indicators with determining hydrocarbon production levels in various modes with estimating the predicted oil recovery coefficients of individual production facilities and the field as a whole and the best option is implemented in practice . 2. The method according to claim 1, characterized in that when developing a field by horizontal wells, they optimize the profile of their shafts using data on the productivity of the selected reservoir classes and the distance to the gas-oil or water-oil contacts.

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