RU2504654C1 - Method of determination of oil extraction factor at nonlinear filtration - Google Patents

Abstract

FIELD: oil-and-gas industry.

SUBSTANCE: proposed method comprises lab and geophysical studies of rock porosity, permeability, oil saturation and oil displacement and determination of pressure gradient field over the deposit area. Note here that collector and filtration-capacitive properties are defined in expanded pressure range and linear speed to make 1*10^-4 MPa/m and 1*10-4 m/days. Defined are statistic porous hydrodynamic and energy structure of rock including reserves of hydrocarbons in the filed of pressure gradients while said factor is calculated as the portion of threshold deposit volume per one producing well.

EFFECT: higher accuracy, reliability and accelerated determination.

1 ex, 3 tbl, 3 dwg

Description

The invention relates to the development of hydrocarbon deposits of complex geological structure with heterogeneous, including low permeable reservoirs. The effectiveness of the oil field development process is determined by the oil recovery factor (CIN). The reliability of the method for determining the oil recovery factor makes it possible to select effective technological solutions that ensure the completeness of the extraction of geological oil reserves.

In the 50s, Academician A.P. Krylov proposed the following simple formula for calculating the SIN value [1. Krylov A.P. The state of theoretical work on designing the development of oil fields and the task of improving these works. // Experience in developing oil fields and tasks to improve these works. - M. Gostoptekhizdast, 1957. - S.116-139.],

where the coefficient of oil displacement by water K _in reflects the efficiency of the displacement process at the micro level, and the coverage factor by displacement K _ooh - the efficiency of the water flooding process at the macro level. In theory and practice of oil field development, this formula and its numerous refinements [2. Zakirov I.S., Korpusov V.I. Correction of the structure of the formula for CIN. // Oil industry. - 2006. - 1. - P.66-68.] Began to be used to establish the attainable value of K _OHM , since knowledge of K _OHM allows you to adjust the number, density, location of drilled or design production and injection wells. It is assumed that K _in is a constant in time, which is not confirmed in practice. K _in depends on many factors: permeability, porosity, initial oil saturation, sandiness, dissection, etc. [3. Zakirov S.N. and other new ideas about the factors of displacement, coverage and oil recovery // Theory and practice of applying methods of increasing oil recovery .// Reports ||| International Scientific Symposium - M. 2011. - P.117-122; 4. Lebedinets NP, Yusupov PM Expert analysis of oil recovery coefficients. // Theory and practice of applying oil recovery enhancement methods. // Reports ||| International Scientific Symposium - M. 2011. - S.133-137].

Practice shows that the higher the heterogeneity of the reservoir, its anisotropy, the lower the reliability of the SIF estimates. In most cases, the State Committee for Reserves (GKZ) reviews and approves the numerical value of oil recovery factor, justified using software systems. The latter include geological and hydrodynamic modeling. Modern software allows you to build a geological model with a high degree of detail (up to a resolution of 0.2 m vertically - at the level of logging resolution) and fully take into account all the features of the geological structure of deposits in three-dimensional three-phase hydrodynamic models. The method for determining the oil recovery factor of deposits involves the creation of a three-dimensional geological and then hydrodynamic model of the reservoir. They incorporate the coefficients of porosity, permeability, initial oil saturation, sandiness, dissection, and oil displacement according to laboratory studies of core filtration-capacity properties (FES). The model is adapted by reproducing the history of development or testing previously drilled wells, and then the forecast of the technological parameters of the simulated development system for a given layout of wells and their operating modes. Oil recovery factor is defined as the ratio of the volume of oil extracted by wells at economically viable production rates to the volume of geological reserves.

The most fully possible hydrodynamic assessment of the efficiency of oil recovery by rational development schemes is described in the RF patent “Method for developing an oil field with artificial maintenance of reservoir pressure” [5. RF patent No. 2190761, 7 ЕВВ 43/20, 2002], which is taken as a prototype. Based on the analysis of the geological and physical conditions of field development (laboratory and geophysical studies), the dependence of the residual oil saturation on the pressure gradient between the lines of injection of displacing agents and the selection of reservoir fluids is determined. Using the obtained dependence, they vary the location of injection and production wells depending on the distribution of the zones of residual oil saturation and the categories of these wells.

The disadvantages of the prototype are the inability to use a method that takes into account the non-linear dependence of the residual oil saturation on the pressure gradient at the initial stage of designing a reservoir development project and the high degree of uncertainty of the desired dependence at the development stage due to the lack of methods for determining the actual distribution of residual reserves over the area of the developed reservoir.

Methods and means for determining the rock structure of reservoirs and FES used in hydrodynamic models are regulated by state and industry standards. In particular, GOST 26450.1-85 and OST 39-181-85 regulate the determination of porosity coefficient, GOST 26450.2-85 and OST 39-235-89 - absolute and phase permeability coefficient of reservoir rock, OST 39-195-86 - oil displacement coefficient by water . According to the FES standards of the reservoir, it should be determined: “at a linear filtration rate of 1-5 m per day, if the oil saturation is less than 20% and the permeability of the reservoir is less than 10 ^-3 μm ² , at a linear velocity of 0.1-1.0 m per day, if the oil saturation and permeability is greater than the specified values.

The disadvantage of the regulations and the corresponding hydrodynamic models is the limitation of the domain of determination by the pressure drop 1 * 10 ^-3 -3 * 10 ^-1 MPa. This pressure drop across a single core sample ~ 30 mm long is achieved with a minimum pressure gradient of about 0.03 MPa / m. Compliance with the requirements of regulatory documents to ensure a linear filtration rate of 0.1-5.0 m / day on a different type of collector is provided with pressure gradients of more than 0.1 MPa / m.

Such high values of the pressure gradient are characteristic of the bottomhole formation zone. At a distance from the wellbore in the body of the reservoir, the pressure gradients are orders of magnitude smaller. In this area, permeability and FES core studies are extremely limited. A drawback of the standards is the general methodological approach: a core sample or a reservoir model composed of several samples is characterized by a specific value of porosity, permeability and residual oil saturation.

Thus, already at the initial stage of obtaining initial data for geological and hydrodynamic models of the formation, the complex structure of the reservoir rock is artificially smoothed. High pressure gradients exclude the manifestation of nonlinear effects and formally ensure the applicability of Darcy's linear hydrodynamics and its modifications. This, for example, is associated with a satisfactory coincidence of the oil recovery factor accepted at the GKZ with the actual one for deposits with homogeneous high-permeability reservoirs of the Martymya-Teterevskaya type and an overflow factor of 1.5-3 times higher for heterogeneous complex-built deposits of the Ketovskaya and Talinskaya type.

The challenge facing the invention is to increase the reliability and reduce the complexity of determining the recovery factor in the development of heterogeneous complex deposits.

The problem is solved in that in addition to laboratory and geophysical studies of the reservoir properties of the rock and the determination of pressure gradients by area of the deposit:

1. Extend the range of research of the collector properties of core samples in terms of pressure drop towards its minimum values to 1 * 10 ^-4 MPa / m and in linear filtration rate to 1 * 10 ^-4 m / day.

2. Determine the distribution density of reservoir properties in the core volume (porosity, permeability and fraction of the first volume with a mobile fluid) in the entire range of pressure gradients and linear filtration rate.

3. Based on the results of laboratory and geophysical studies (GIS), statistical pore, hydrodynamic (permeability) and energy structure of hydrocarbon reserves (HC) are built. In this case, the energy structure characterizes the fraction of the pore volume of the reservoir of a given permeability with a moving fluid at an appropriate pressure gradient.

4. Build a field of pressure gradients typical for the adopted development technology over the area and reservoir power.

5. The numerical value of oil recovery factor is determined as the fraction of mobile reserves in the development area per typical well-deposit (C-3) in the pressure gradient energy field created by the project, provided that the geological model of the reservoir rock assigned to the typical well corresponds to the average on the deposits.

The invention is illustrated by drawings, where Fig. 1 shows a statistical pore structure of a reservoir, Fig. 2 shows a hydrodynamic structure of a reservoir, and Fig. 3 shows the proportion of mobile reserves in pore channels.

The basis of the invention is the idea of the random nature of the distribution of independent reservoir characteristics, such as porosity, permeability, geometry of the pore channels, in an arbitrarily small volume of rock. As the volume of the rock increases, randomness turns into its opposite - a statistical regularity, which allows the reservoir or its part to be represented as a single well.

The well-well (С-3) is endowed with the average, per well, size, hydrocarbon reserves, water saturation, statistical pore, hydrodynamic and energy structure per well, as well as the pressure gradient field typical for the technology adopted for development, by area and thickness of the reservoir.

The probability of the presence of moving reserves dW _i in the reservoir volume dV _j is defined as the product of the probabilities of the ith event for porosity K _pi , permeability K _pri and pressure gradient F _dpi , providing fluid mobility

Where

.

.

p (Kп), p (Kпр), p (K _ohw)) is the distribution density of the corresponding characteristics.

Integration of dW _ij over the oil-saturated porosity interval and reservoir volume determines the fraction of the C-3 feather volume with a mobile hydrocarbon fluid. Obviously, in the field of pressure gradients, which is due to the corresponding development technology, only moving oil reserves can be extracted. Accordingly, the moving share of hydrocarbon reserves in the supply zone of a typical well can be considered the technological coefficient of oil recovery from the oil recovery factor of the reservoir. Calculation of mobile hydrocarbon reserves by the described method is carried out on modern PVEM using the developed software.

An example of the oil recovery factor for the Krasnoleninsky field.

Talinskaya area of the Krasnoleninsky field, block 46,

Object of development - SC _10-11 ,,

Development system - in-line with maintaining reservoir pressure,

The average supply area per 1 well is 25 ha,

Oil-saturated power - 21 m,

Formation conditions: temperature - 99 ° С, pressure - 22.3 MPa.

Characterization of FES rock.

Average permeability coefficient - K _ave = 184 mD

The average coefficient of porosity - K _p = 0,16

Oil saturation coefficient - K _n = 0.85

The residual coefficient of oil saturation - K _he = 0,32

The oil recovery factor of the Talinskaya area of the Krasnoleninsky deposit, UK _{10-11 was} approved by the GKZ repeatedly, dropping from a value of more than 0.4 to the current 0.257.

The technology for determining CIN by the claimed method. According to the results of existing laboratory studies of core and well logs, a statistical pore and hydrodynamic structure of the reservoir of Figs. 1 and 2 is built.

Additional studies of the reservoir properties of core samples are carried out at low pressure gradients up to 1 * 10 ^-4 MPa / m and a linear filtration rate up to 1 * 10 ^-4 m / day. Taking into account additional studies, the energy structure of the collector is determined Figure 3, Table 1. It reflects the nonlinear properties of the fluid filtration process in heterogeneous complex reservoirs. Shear stress F (K _ol ) in Tab. 1 describes the energy consumption for moving fluid 1 m in the pore channels of a reservoir with i-permeability. The graph in FIG. 3 characterizes the proportion of mobile reserves in the pore channels of the reservoir of average statistical permeability in the field of applied forces. Obviously, the integral share of mobile stocks is nothing but the displacement coefficient in the interpretation of A.P. Krylov In contrast to the latter and from the prototype in the proposed method, the share of mobile reserves is a function of porosity, permeability, fluid properties and the magnitude of the pressure gradient at each point of the rock formations.

The pore volume and geological oil reserves attributable to a typical S-Z well are determined, to which the statistical structure of the rock of the deposit is attributed. 2.

In a simplified version for clarity, we divide the collector of the SZ well into three types: the supercollector, the collector, and the non-collector in terms of average permeability, and the feed zone of the SZ well into three sections according to the radii of remoteness from the bottom. This allows you to move from integration to summation over the arguments.

The pressure field and the pressure gradients corresponding to the selected areas are determined by the solution of the generalized Darcy equation for both the S-3 well and its sections.

The necessary initial data for the calculations and the results of determining the oil recovery factor by deposits, by sites and by selected types of reservoirs are given in Table 1, 2.

Table 1 The characteristic of the reservoir attributed to the well S-Z Collector type Permeability, mV The share of the collector,% Shear stress, MPa / cm ² Non collector 13 45 0,02300 Collector 166 35 0.00220 Super collector 600 twenty 0,00061 Well collector S-3 184 one hundred -

table 2 CIN determination results one Well-deposit, NW, radis, m 0.2-50 50-166 166-282 Geological reserves of oil, thousand m3 including: 22.4 224.7 466.0 2 1. Super collector 4.48 44.9 197,2 2. The collector 7.74 78.6 163.1 3. Non-collector 10.08 101,2 209.7 3 Field of pressure gradients, MPa / m 0.0149 0.00465 0.00310 four The share of mobile stocks, including: 0.234 0.152 0.123 1. Super collector 0.495 0.343 0.291 2. The collector 0.391 0.279 0.187 3. Non-collector 0,000 0 0,000 5 Recoverable oil reserves, oil recovery factor 0.135

The CIN value in the simplified version of the method is 0.135 when actually achieved 0.11 with a water cut of 0.95. Calculation of oil reserves recovered over 5 years using the Eclipse software package using the statistical pore, hydrodynamic, and energy structure gives an oil recovery factor = 0.105 at a water cut of 85%

The table below shows for comparison the results of the calculation of the SIF of deposits developed in the mode of maintaining reservoir pressure (RPM). The calculations were performed using hydrodynamic (GD) models and accepted by the GKZ. It also shows the actual oil recovery factor for deposits with a water cut of more than 95% and the oil recovery factor obtained by the proposed method taking into account non-linear filtering based on the statistical pore, hydrodynamic and energy structure of the reservoirs.

Table 3 CIN of deposits in the RPM mode by the methods of DG modeling and taking into account nonlinear filtering (CIN-NL) in the reservoir of a typical well S-Z Jurassic deposits CIN,% Fact on 1.01.04 By DG models KIN-NL * VGF ± ΔKIN% By ∇P ΔKIN% Mortymya-Teterevskaya 0.508 0.515 1.8 0.498 1,6 South Teterevskaya 0.396 0.406 2,5 0.435 9.8 East Teterevskaya 0.427 0.433 1.4 0.421 1.4 Talinskaya 0,110 0.257 134 0.105 4,5 Ketovskaya 0,098 0.320 226 0,094 4.1 * - excluding oil recovery enhancement methods used

The proposed method for calculating the oil recovery factor based on the statistical structure of the reserves of the Talinskaya area YuK10-11 and Ketovskoye YuV1 field without adaptation gives the oil recovery factor in the RPM mode of 10.9 and 10.0%, respectively, in accordance with the actual - 11 and 9.8%. The recoverable oil reserves approved by the GKZ for these deposits are 25.7 and 32%, respectively, performed using the most modern GD - reservoir models, overstate the oil recovery factor by 2 times or more. For deposits with a relatively homogeneous structure of the Martymya-Teterevskaya reservoir, the calculated oil recovery factor according to the DG model and the proposed method are in good agreement with the actual oil recovery achieved.

Therefore, the proposed method for determining the recovery factor of complex deposits with a heterogeneous reservoir structure in accordance with the task simplifies and increases the reliability of the oil recovery forecast. At the same time, the use of the well-reservoir model not only reduces the time for calculating oil recovery factor by an order of magnitude, but also gives the distribution of mobile reserves over the area of the reservoir and the hydrodynamic type of reservoirs. This allows you to make effective geological and technical decisions to improve oil recovery.

Claims (1)

A method for determining the oil recovery coefficient in non-linear filtration, including laboratory and geophysical studies of the reservoir properties of the rock, including porosity, permeability, oil saturation and oil displacement factors, determining the field of pressure gradients by the area of the reservoir, characterized in that the reservoir and filtration capacitive properties are determined in an expanded pressure range, and the linear velocity of 1 × 10 ^-4 MPa / m and 1 x 10 ^-4 m / day, based on the received data and Res GIS ltats, the statistical pore hydrodynamic and energy structure of the rock of the reservoir is determined, including the moving (recoverable) hydrocarbon reserves in the field of pressure gradients, and the oil recovery factor is calculated as the fraction of the pore volume of the reservoir with moving hydrocarbon (oil) reserves in the field of pressure gradients of the average statistical section per per production well, which has the average FES parameters of rock formations with a typical field of pressure gradients of the considered technological circuit Development topics.

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