SAGD-developed methods, applications, media, and equipment for determining the activation status of bottom-water heavy oil reservoirs.

Abstract

This invention discloses a method, application, medium, and equipment for determining the activation status of oil layers in bottom-water heavy oil reservoirs developed using SAGD (Super Aquaculture Diversion). The method includes: measuring the formation resistivity of the original reservoir, the formation resistivity after activation, and the sonic transit time using a series of well logs; determining the reservoir porosity based on the sonic transit time; determining the numerical value of the reservoir's rock-electric coefficient; determining a preset model of resistivity and saturation based on the rock-electric coefficient value, and then determining the bound water resistivity in the original reservoir formation; determining the formation water resistivity after activation based on the preset model of fluid resistivity and temperature; and determining the oil saturation after activation based on the preset model of resistivity and saturation, the determined formation water resistivity after activation, and other known parameters. This technology can quantitatively determine the activation status of oil layers below SAGD production wells in bottom-water reservoirs, providing a basis for determining the detailed locations of potential tapping wells in bottom-water reservoirs.

Description

Technical Field

[0001] This invention relates to the field of petroleum exploration technology, specifically to a method, application, medium, and equipment for determining the activation status of oil layers in bottom-water heavy oil reservoirs developed by SAGD. Background Technology

[0002] SAGD (Steam Assisted Gravity Drainage) is a cutting-edge technology for developing extra-heavy oil. Its principle was initially based on water injection for salt production. This technology involves injecting steam into the reservoir from a vertical or horizontal well above a horizontal production well located near the reservoir bottom. The heated crude oil and steam condensate are then produced from the horizontal well at the reservoir bottom. This technology has become mature. Since its introduction to China in 1997, it has formed the largest SAGD production base in the Liaohe Oilfield, developing a unique Liaohe technology adapted to terrestrial sedimentary formations using a combination of vertical and horizontal SAGD. After more than 20 years of development, the SAGD steam chamber has been formed, and the Xing VI Formation in the Liaohe D84 block has risen to the top of the oil layer. After experiencing the steam chamber formation and lateral steam expansion stages, it is currently entering the steam chamber descent stage. Traditional thinking holds that during SAGD development, steam overlap creates a steam cavity around the injection well above the horizontal production well, primarily utilizing the oil layer above the horizontal production well, while the lower oil layer is utilized less. Temperature curves show varying degrees of temperature increase below the horizontal production well, exhibiting a "slope zone." This could be due to heat conduction causing the temperature increase without oil layer utilization, or steam overlap causing the temperature increase and oil layer utilization. Currently, it is impossible to determine whether the oil layer below the SAGD production well in a bottom-water heavy oil reservoir has been utilized.

[0003] Patent document CN106442757A discloses a method for determining oil-water layers. This method identifies oil and gas showing layers using data from rock cuttings, core samples, wellbore coring, and gas logging. It then determines the relative percentage content of C8-C37 n-alkanes, Pt, and Ph, and calculates the positions of Pr / C17, Ph / C18, ∑C21- / ∑C22+, and C21+C22 / C28+C29 on a rock pyrolysis gas chromatography characteristic parameter chart to determine the reservoir fluid properties. This invention expands the application range of parameters and improves the accuracy of oil-water layer interpretation from logging. However, this method is only applicable to oil-water layer identification in the original reservoir state and cannot determine the situation after the thermal recovery of heavy oil reservoirs has been utilized.

[0004] Patent document CN108894778B discloses a method for identifying the fluid properties of oil and gas reservoirs using gas logging data. In this method, gas logging data at the corresponding depth of the fluid sample is used to obtain the gas logging identification parameters Bh*10+sz-wh, c1 / (c2+c3+c4+c5) of the oil and gas reservoir; a gas logging identification chart is constructed: c1 / (c2+c3+c4+c5) is selected as the abscissa and Bh*10+sz-wh as the ordinate, and plotted on a coordinate graph. This method can quickly identify oil and gas reservoirs without downhole fluid sampling, reducing exploration and development costs, but it cannot determine the reservoir activation status of SAGD-developed reservoirs.

[0005] Patent document CN102518424A discloses a combined fluid resistivity and temperature measurement device. This device is a well logging measurement device for downhole fluid resistivity and temperature parameters, comprising: a pressure-bearing body, a composite sensor, and a safety protection plug. The pressure-bearing body includes an upper pressure-bearing end cap, a lower pressure-bearing end cap, and a pressure-bearing outer shell, with the upper and lower pressure-bearing end caps connected to the pressure-bearing outer shell. The composite sensor includes a set of resistivity sensors, a temperature sensor, and a composite sensor body, with the temperature sensor located between the set of resistivity sensors. The set of resistivity sensors and the temperature sensor are pressure-sealed connected to the composite sensor. The composite sensor and the safety protection plug are connected to the pressure-bearing body through mounting holes, and the safety protection plug is connected to the composite sensor. This device is not yet in industrial production, and due to limited investment, with thousands of development wells in oilfield blocks, daily monitoring of each well is not feasible, thus delaying oilfield production.

[0006] Patent document CN105649588A discloses a method for developing heavy oil reservoirs using SAGD (Super Aquaculture Diversion). This method optimizes the setup of multiple vertical wells to assist in steam injection, selects the optimal injection timing and key production parameters, and achieves uniform development of the SAGD steam chamber to maximize the utilization of the oil layer and improve the recovery rate. However, this method does not mention a quantitative method or a method for judging the decline in oil saturation in the already utilized reservoir, and therefore cannot guide the later-stage potential tapping and adjustment of SAGD development.

[0007] Among the currently available technologies related to SAGD (Super Aquatic Oil Depletion), none involve a method for determining the activation status of oil layers in reservoirs that have already been activated by SAGD. Summary of the Invention

[0008] This invention provides a method, application, medium, and equipment for determining the activation status of bottom water heavy oil reservoirs developed by SAGD, in order to solve at least one of the above-mentioned technical problems existing in the prior art.

[0009] To achieve the above-mentioned technical objectives, the technical solution adopted by the present invention is as follows:

[0010] According to one aspect of the present invention, a method for determining the activation status of bottom-water heavy oil reservoirs developed by SAGD is provided, comprising the following steps:

[0011] Step 1: Measure the formation resistivity R of the original reservoir in the target layer using a series of well logging operations. t1 Formation resistivity R after reservoir activation t2 Acoustic wave time difference Δt;

[0012] Step 2: Determine the reservoir porosity value Φ based on the acoustic transit time Δt. t The porosity value Φ t Including the original reservoir porosity value Φ t1 and the porosity value Φ after reservoir activation t2 ;

[0013] Step 3: Determine the value of the reservoir's lithoelectric coefficient;

[0014] Step 4: Determine the preset model of resistivity and saturation based on the numerical value of the rock electrical coefficient. This is done according to the preset model of resistivity and saturation, the original reservoir oil saturation S1, and the original reservoir porosity value Φ. t1 and the formation resistivity R of the original oil reservoir t1 Determine the resistivity R of bound water in the original oil reservoir strata. w1 ;

[0015] Step 5: Based on the preset model of fluid resistivity and temperature, the original reservoir state formation temperature t1, and the bound water resistivity R in the original reservoir formation. w1 Determine the formation water resistivity R after reservoir activation based on the formation temperature t2. w2 ;

[0016] Step 6: Based on the preset model of resistivity and saturation, and the porosity value Φ after reservoir activation... t2 Formation resistivity R after reservoir activation t2 and the formation water resistivity R after reservoir activation determined in step 5. w2 Determine the oil saturation S2 after reservoir activation.

[0017] According to one embodiment of the present invention, in step 2, the reservoir porosity value Φ is determined based on the acoustic transit time Δt. t This includes using core pressure tests to analyze the relationship between porosity and acoustic transit time regression to determine the reservoir porosity value Φ. t .

[0018] According to one embodiment of the present invention, the reservoir porosity value Φ is obtained by analyzing the relationship between porosity and acoustic transit time regression using core pressure test analysis. tOverburden correction was performed on the core pressure test data to correct the core analysis porosity to the formation porosity.

[0019] According to one embodiment of the present invention, the core pressure test data includes porosity and permeability obtained by core drilling.

[0020] According to one embodiment of the present invention, in step 2, the reservoir porosity value Φ is determined based on the acoustic transit time Δt. t This includes calculating the reservoir porosity value Φ based on the following formula (1). t :

[0021] Φ t =(Δt-Δt) ma ) / (Δt f -Δt ma )*1 / C p -V sh *(Δt sh –Δt ma ) / (Δt f -Δt ma )……(1)

[0022] In the formula:

[0023] Φ t —Porosity calculated using acoustic wave analysis;

[0024] Δt — Sonic transit time logging value of the target layer;

[0025] Δt ma —Sound wave transit time of the rock skeleton;

[0026] Δt f —Sound transit time of formation fluids;

[0027] C p — Acoustic compaction correction coefficient;

[0028] V sh —Sedimentary clay content;

[0029] Δt sh —Sonic transit time value of pure mudstone.

[0030] According to one embodiment of the present invention, the lithological electrical coefficient of the reservoir determined in step 3 includes a lithology-related coefficient a, a lithology-related constant b, a cementation index m, and a saturation index n.

[0031] According to one embodiment of the present invention, in step 3, the rock electrical coefficients a, b, m, and n of the reservoir are determined by core experiments.

[0032] According to one embodiment of the present invention, if the experimental analysis data of rock resistivity is incomplete in step 3, the saturation coefficient is derived from the saturation, porosity and rock resistivity of the core analysis.

[0033] According to one embodiment of the present invention, the rock resistivity is obtained by deep lateral logging at the repositioning point.

[0034] According to an embodiment of the present invention, the preset model of resistivity and saturation in step 4 is determined based on Archie's formula, and the preset model is the following formula (2):

[0035]

[0036] According to one embodiment of the present invention, the oil saturation S1 of the original reservoir in step 4 is determined by core experiments.

[0037] According to an embodiment of the present invention, the preset model of fluid resistivity and temperature in step 5 is determined based on the Aps formula, and the preset model of fluid resistivity and temperature is the following formula (3):

[0038] R w2 =R w1 ((t1+21.5) / (t2+21.5)) (3)

[0039] According to one embodiment of the present invention, the formation temperature t1 in the original reservoir state and the formation temperature t2 after reservoir activation are obtained by well temperature logging.

[0040] According to one embodiment of the present invention, the oil saturation S2 after reservoir activation in step S6 is determined by the following formulas (4) and (5):

[0041]

[0042]

[0043] According to one embodiment of the present invention, the formation resistivity R after reservoir activation in step S6 t2 It is the deep-direction resistivity value measured in the well logging series in the later stage of SAGD development.

[0044] According to another aspect of the present invention, a method for determining the utilization of oil reservoirs in bottom water heavy oil reservoirs developed by SAGD as described above is provided for application during bottom potential tapping in the later stages of SAGD development.

[0045] According to one embodiment of the present invention, the method for determining the activation status of bottom water heavy oil reservoirs developed by SAGD is used to determine the detailed deployment location of potential tapping wells.

[0046] According to one embodiment of the present invention, the oil saturation value of each point from below the SAGD production horizontal well to the original oil-water interface is determined according to the method for judging the oil layer utilization of the bottom water heavy oil reservoir developed by SAGD, and the oil saturation value of the lower limit of reservoir deployment >35% is used as the basis for determining the specific deployment location of the bottom tapping well of SAGD.

[0047] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, it performs the steps of the method for determining the activation status of bottom water heavy oil reservoirs developed by SAGD as described above.

[0048] According to another aspect of the present invention, a computer device is provided, comprising:

[0049] at least one processor; and

[0050] The memory stores a computer program that can run on the processor, and when the processor executes the program, it performs the steps of the bottom water heavy oil reservoir activation determination method developed by SAGD as described above.

[0051] Due to the adoption of the above technical solutions, the methods, applications, media, and equipment provided by this invention have the following beneficial effects compared with the prior art: Using the technical solutions described in this invention, the utilization status of the oil layer below the activated bottom-water extra-heavy oil SAGD production horizontal well can be accurately determined, and detailed well placement locations can be provided for bottom tapping during the later stages of SAGD development. This method has been successfully implemented in the bottom-water extra-heavy oil reservoir of Xing VI Group in Block D84, accurately identifying the oil-water layer below the SAGD production horizontal well and deploying tapping wells in the oil layer, with a daily production of more than 10t / d. Attached Figure Description

[0052] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the present invention but do not constitute a limitation of the present invention. In the accompanying drawings:

[0053] Figure 1 A schematic diagram of uniaxial correction of porosity and permeability according to an embodiment of the present invention is shown;

[0054] Figure 2 A schematic diagram showing the resistivity relationship of fully saturated water in rock according to an embodiment of the present invention is shown.

[0055] Figure 3 A schematic diagram showing the relationship between the increasing resistivity of rock saturated oil according to an embodiment of the present invention is shown. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0057] Steam-assisted gravity drainage (SAGD) is a technology for developing extra-heavy crude oil. For high-viscosity crude oil that has no flowability under original formation conditions, a preheating stage of the oil reservoir is required to achieve thermal connectivity between injection and production wells. After thermal connectivity is established, the injected steam overflows into the formation to form a steam chamber. The steam chamber moves upward and laterally, exchanging heat with the crude oil in the oil reservoir. The heated crude oil and steam condensate are then discharged into the production well below by gravity.

[0058] Identifying oil-water layers is one of the core issues in petroleum reservoir geology research. This invention analyzes the relationship between resistivity and dissolved salt concentration by examining the conductivity of substances, the multiplier for converting ion concentration into equivalent sodium chloride concentration, and using the Arps and Archie equations to jointly derive the relationship between fluid resistivity, salinity, and temperature. This allows for the determination of the matching relationship between the heat generated by injected steam and resistivity during SAGD development, quantitatively assessing the degree of oil layer activation in bottom-water reservoirs, and solving practical oilfield production problems.

[0059] In one embodiment of the present invention, a method for determining the utilization status of bottom-water heavy oil reservoirs developed by SAGD is provided. The method generally includes the following steps:

[0060] Step 1: Measure the formation resistivity R of the original reservoir in the target layer using a series of well logging operations. t1 Formation resistivity R after reservoir activation t2 Acoustic wave time difference Δt;

[0061] Step 2: Determine the reservoir porosity value Φ based on the acoustic transit time Δt. t The porosity value Φ t Including the porosity value Φ of the original oil reservoir t1 and the porosity value Φ after reservoir activation t2 ;

[0062] Step 3: Determine the value of the reservoir's lithoelectric coefficient;

[0063] Step 4: Determine the preset model of resistivity and saturation based on the numerical value of the rock electrical coefficient. This is done according to the preset model of resistivity and saturation, the original reservoir oil saturation S1, and the original reservoir porosity value Φ. t1 and the formation resistivity R of the original oil reservoir t1 Determine the resistivity R of bound water in the original oil reservoir strata. w1 ;

[0064] Step 5: Based on the preset model of fluid resistivity and temperature, the original reservoir state formation temperature t1, and the bound water resistivity R in the original reservoir formation. w1 Determine the formation water resistivity R after reservoir activation based on the formation temperature t2. w2 ;

[0065] Step 6: Based on the preset model of resistivity and saturation, and the porosity value Φ after reservoir activation... t2 Formation resistivity R after reservoir activation t2 and the formation water resistivity R after reservoir activation determined in step 5. w2 Determine the oil saturation S2 after reservoir activation.

[0066] The following is a detailed explanation of each step.

[0067] In step S1, the formation resistivity R of the original reservoir in the target layer is measured using a series of well logging operations. t1 Formation resistivity R after reservoir activation t2 The sonic transit time Δt. These parameters can be measured using appropriate logging series according to the conventional technical requirements of this field, and will not be elaborated further here.

[0068] In step 2, the porosity value Φ of the reservoir is calculated. t Porosity value Φ t Including the porosity value Φ of the original oil reservoir t1 and the porosity value Φ after reservoir activation t2 The reservoir porosity value Φ can be obtained using various methods. t In some embodiments, the reservoir porosity value Φ is obtained by analyzing the relationship between porosity and acoustic transit time regression using core pressure testing. t In this case, since core analysis is generally conducted under normal surface pressure (or a specific pressure), the pores will expand, so the measured core porosity and permeability will be greater than the porosity under formation conditions. Therefore, it is necessary to correct them by performing overburden pressure correction on the core pressure test data to correct the core analysis porosity to the formation porosity. The specific correction operation will be described in the specific examples below. In some other embodiments, the reservoir porosity value Φ is obtained based on the following formula (1). t :

[0069] Φ t =(Δt-Δt) ma ) / (Δt f -Δt ma )*1 / C p -V sh *(Δt sh –Δt ma ) / (Δtf -Δt ma )……(1)

[0070] In the formula Φ t The porosity is calculated using acoustic wave propagation, and Δt is the acoustic time-of-flight logging value for the target layer. ma It is the time difference of sound waves in the rock skeleton, Δt f It is the acoustic transit time of formation fluids, C p It is the acoustic compaction correction factor, V sh It is the clay content of the formation, Δt sh This is the acoustic transit time value for pure mudstone. In other embodiments, the reservoir porosity value Φ can be obtained simultaneously using both of the above methods. t Then, the results of the two methods are compared for correction.

[0071] In step 3, the numerical values ​​of the reservoir's lithological electrical coefficients are determined. The determined lithological electrical coefficients include a lithology-related coefficient (a), a lithology-related constant (b), a cementation index (m), and a saturation index (n). The lithological electrical coefficients a, b, m, and n of the reservoir can be determined through core experiments. If the rock resistivity experimental analysis data is incomplete, the saturation coefficient is derived using the saturation, porosity, and rock resistivity from the core analysis. The rock resistivity can be obtained through deep lateral logging at the repositioning point.

[0072] In step 4, a preset model for resistivity and saturation is first determined based on the values ​​of rock electrical coefficients a, b, m, and n. The preset model for resistivity and saturation is determined based on Archie's formula, and the preset model is the following formula (2):

[0073]

[0074] The original reservoir oil saturation S1 and the original reservoir porosity value Φ are used to determine the oil saturation S1 and porosity value Φ of the original reservoir. t1 and the formation resistivity R of the original oil reservoir t1 Substituting into formula (2) above, the resistivity R of bound water in the formation under the original reservoir condition can be determined. w1 The oil saturation S1 of the original reservoir was determined by core experiments.

[0075] The relationship between fluid resistivity and temperature is as follows: as the formation temperature increases, the activity of fluid ion movement increases, the conductivity of the fluid (formation water in the reservoir) increases, and the resistivity in the reservoir decreases. This is reflected in the fact that the resistivity actually measured in the well logging series is lower than the resistivity under the original reservoir conditions. Therefore, in step 5, a preset model of fluid resistivity and temperature is determined based on the Aps formula. This preset model is shown in the following formula (3):

[0076] R w2 =R w1((t1+21.5) / (t2+21.5)) (3)

[0077] The original reservoir temperature t1 and the bound water resistivity R in the original reservoir state determined in step 4 are used as the reference values. w1 Substituting the formation temperature t2 after reservoir activation into formula (3), the formation water resistivity R after reservoir activation is determined. w2 The original reservoir temperature t1 and the reservoir activation temperature t2 were obtained by well temperature logging.

[0078] In step S6, based on the preset model of resistivity and saturation determined by Archie's formula, the oil saturation S2 after reservoir activation can be deduced to conform to the following formula (4):

[0079]

[0080] After sorting, we get:

[0081]

[0082] The porosity value Φ after reservoir activation t2 Formation resistivity R after reservoir activation t2 and the formation water resistivity R after reservoir activation determined in step 5. w2 Substituting into formula (5), determine the oil saturation S2 after reservoir activation. The formation resistivity R after reservoir activation... t2 This resistivity, obtained through a series of well logs, can be the deep-directional resistivity value measured in the well log series during the later stages of SAGD development. The porosity value Φ after reservoir activation. t2 You can determine this by following the method provided in step 2.

[0083] This invention also provides an application of the above-mentioned method for determining the utilization status of bottom-water heavy oil reservoirs developed by SAGD in bottom tapping during the later stages of SAGD development. This method provides a basis for determining the detailed deployment locations of tapping wells. Based on this method, the oil saturation values ​​at various points from below the SAGD production horizontal well to the original oil-water interface are determined, and an oil saturation value >35% (the lower limit of reservoir deployment) is used as the basis for determining the specific deployment location of bottom tapping wells in SAGD. When it is desired to determine the oil saturation at a certain point in the target layer during the later stages of SAGD development, this method is used to calculate the oil saturation values ​​at various points from below the SAGD production horizontal well to the original oil-water interface. Based on the oil saturation value >35% (the lower limit of reservoir deployment), the specific deployment location of bottom tapping wells in SAGD is determined, fully utilizing the reserves below the SAGD production horizontal well.

[0084] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the SAGD-developed method for determining the activation status of bottom-water heavy oil reservoirs as described above.

[0085] The present invention also provides a computer device, which includes at least one processor and a memory. The memory stores a computer program that can run on the processor. When the processor executes the program, it performs the steps of the bottom water heavy oil reservoir oil layer activation determination method developed by SAGD as described above.

[0086] The implementation scheme of the present invention will be described below with reference to specific application examples.

[0087] The D84 block Xing VI Formation bottom-water extra-heavy oil reservoir began steam injection development in 1997 and transitioned to SAGD development in 2006, where it has been thermally exploited for over two decades. The oil layer thickness between the oil and water interface below the SAGD horizontal well is 15-35 meters. Taking the D84-Ping 44 to D84-Ping 47 well group as an example, this example calculates the current oil saturation, or remaining oil saturation, at a point below the D84-Ping 44 to D84-Ping 47 well group. In this example, the remaining oil saturation is calculated 10 meters directly below well D84-Ping 45 within the D84-Ping 44 to D84-Ping 47 well group.

[0088] Based on well logging data, the resistivity of the deep lateral formation 10m directly below well D84-Ping45 under the original reservoir condition was determined to be R. t1 =78Ω·m, the formation resistivity R of the reservoir after SAGD development was measured in the well logging series. t2 It is 1.272414.

[0089] Determining the reservoir porosity value Φ t In this example, the reservoir porosity value Φ is directly obtained by using the relationship between core analysis porosity and acoustic transit time regression. t Since core sampling analysis is generally conducted at atmospheric pressure (or a specific pressure) at the surface, the pores will expand. Therefore, the measured core porosity and permeability will be greater than the porosity under formation conditions, necessitating correction. After measuring the core porosity and permeability, the experimental data are processed and statistically analyzed to derive the following correction formula for porosity as a function of pressure:

[0090] Φ c =Φ0*P e -0.06

[0091] K c =K0^P e -0 .75

[0092] Where: Φ0—Ground porosity (%)

[0093] K0—Surface permeability (mD)

[0094] P e —Net overburden pressure (MPa).

[0095] Core pressure tests are conducted to analyze porosity under triaxial loading, while actual formation conditions can be considered as uniaxial deformation. Therefore, the porosity measured in the laboratory needs to be converted and corrected to porosity under uniaxial compression. The specific conversion formula is as follows:

[0096] Φ f =Φ s -(Φ s -Φ z )r(S-1)

[0097] Where: Φ f —Converted uniaxial porosity (%)

[0098] Φ s —Ground porosity (%)

[0099] Φ z —Triaxial porosity (%) as measured in the laboratory

[0100] r—conversion factor, which is related to the Poisson's ratio of the rock, and is taken as 0.619.

[0101] By dividing the triaxial porosity and permeability measured in the laboratory by the ground porosity and surface permeability, respectively, the porosity variation coefficient Φ is plotted in the same coordinate system. i / Φ0, coefficient of change of permeability K i The relationship curve between / K0 and overlying rock pressure is shown in the attached figure. Figure 1 As shown. Uniaxial correction is performed on porosity and permeability. The correction steps are as follows:

[0102] a) Calculate the net overlying pressure of the sample based on the sample depth and reservoir pressure, and then... Figure 1 Determine the position of A on the x-axis;

[0103] b) Obtain the triaxial porosity variation coefficient Φ by perpendicularly intersecting curve 1 at point B from position A. zr , using Φ zr Multiply by the surface porosity to obtain the triaxial porosity.

[0104] c) Calculate the uniaxial porosity Φ according to formula S-1. f ;

[0105] d)Φ fDividing by the surface porosity yields the uniaxial porosity variation coefficient Φ. fk Find the corresponding point C on curve 1;

[0106] e) The curve intersects curve 2 vertically downwards from point C at point D. The intersection point is the uniaxial permeability variation coefficient K. fr ;

[0107] f) with K fr Multiplying by the surface permeability gives the uniaxial permeability value.

[0108] The definition of net overburden is:

[0109] P e =P s -P f

[0110] Among them, P s For the overlying formation pressure, P f This represents the pore fluid pressure, expressed in MPa.

[0111] The above method is used to calculate and restore the formation porosity and permeability data obtained from the experiment to the porosity and permeability values ​​under formation conditions.

[0112] Calculate the clay content according to formula S-2:

[0113]

[0114] Wherein, GCUR—regional empirical coefficient, is taken as 3.7;

[0115]

[0116] SHH—Mud quality indicator curve (conditional unit);

[0117] SHMN—SHH value in pure sandstone, generally taken as 0 (conditional unit);

[0118] SHMX—SHH value of pure mudstone, generally taken as 40 (conditional unit).

[0119] In this example, most wells in the block used domestically produced CNC logging systems. Therefore, porosity was calculated using sonic transit time and neutron gamma curves. However, the measured values ​​of neutron gamma curves are relatively small and greatly affected by the environment. Furthermore, the measurement depth of neutron gamma curves in some wells was insufficient. Therefore, sonic transit time was used to calculate porosity in this area. The total formation porosity was calculated using formula S-3.

[0120] Sonic stratigraphic factors method

[0121] The effective porosity of the formation was calculated using the acoustic clay correction method, and the formula is shown in Formula S-4.

[0122] In the formula:

[0123] V SH - Clay content;

[0124] t sh - Acoustic transit time value for pure mudstone;

[0125] t ma - Sonic transit time skeleton value for pure sandstone.

[0126] In this example, due to incomplete well data for the neutron-gamma curve and the small range of numerical values, the relationship with clay content and median particle size is not very good. Therefore, permeability is calculated using only clay content and porosity, as shown in Formula S-5.

[0127]

[0128] In the formula:

[0129] P-Porosity index;

[0130] R w - Formation water resistivity;

[0131] S w -Water saturation;

[0132] R t -Deep lateral resistivity;

[0133] R o - Rock resistivity with water saturation;

[0134] K-penetration rate;

[0135] F - Stratigraphic factors;

[0136] P f - Pore structure comprehensive index and formation factor conversion coefficient.

[0137] Conclusion:

[0138] PERM=0.162*exp(0.3522*PORR) (S-6)

[0139] Where: PORR - effective porosity (%);

[0140] PERM - Permeability (md).

[0141] Determine the value of the reservoir's rock-electric coefficient. Since the rock resistivity test analysis data in this example is not systematic, the saturation coefficient is derived based on the saturation, porosity, and rock resistivity (deep lateral at the infill location) obtained from core analysis. First, the relationship between R0 and porosity is found based on the core resistivity analysis data, and then m = 1.75 and a = 1 are calculated (see Appendix). Figure 2 Then, based on this relationship and the porosity and saturation from the core analysis, n = 1.9 and b = 1 were calculated (see appendix). Figure 3 ).

[0142] The pre-defined model for resistivity and saturation is determined based on the values ​​of rock electrical coefficients a, b, m, and n, as shown below:

[0143]

[0144] R t1 =78Ω.m, Φ t1 Substituting S1 = 0.347 and S2 = 0.65 into formula S-7, we obtain R. w1 =2.1.

[0145] R w1 Substituting the values ​​of t1 = 40 and t2 = 80 into the preset model of fluid resistivity and temperature, as shown below:

[0146] R w2 =R w1 ((t l +21.5) / (t2+21.5)) (S-8)

[0147] Calculate the current formation water resistivity R w2 =2.1*[(40+21.5) / (80+21.5)]=1.272414.

[0148] The current oil saturation S2 is then calculated using the following formula S-8:

[0149]

[0150] Where a = 1, b = 1, m = 1.75, n = 1.9, R t2 =25, Φ t2 =0.347, R w2 =1.272414. The current oil saturation S2 is calculated to be 0.50, which means the current oil saturation is 50%. The current oil saturation of each point below the D84-Ping44 to D84-Ping47 well group is calculated using the above method.

[0151] During the later stages of SAGD development in the Xing VI Formation of Block D84, the oil saturation within 10 meters below the wells in the D84-Ping 44 to D84-Ping 47 well groups all met the requirement of an oil saturation level greater than 35% for well placement. Therefore, the potential-tapped horizontal well D84-Xing H56 was deployed below the SAGD production horizontal wells in the D84-Ping 44 to D84-Ping 47 well groups. This potential-tapped well has been implemented in the field and has been in production for more than 5 years, with an average daily oil production of more than 15 tons per well and a cumulative oil production of more than 23,000 tons. Another potential-tapped horizontal well at the bottom of the SAGD, D84-Xing H62-1, has also been in production for more than 3 months, with an average daily oil production of more than 10 tons per well. The production effect of the potential-tapped wells at the bottom of the SAGD is very good, indicating that the invented method can serve actual production.

[0152] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

[0153] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any appropriate manner without contradiction. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0154] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed by the present invention.

Claims

1. A method for determining the activation status of bottom-water heavy oil reservoirs developed using SAGD, characterized in that, Includes the following steps: Step 1: Measure the formation resistivity R of the original reservoir in the target layer using a series of well logging operations. t1 Formation resistivity R after reservoir activation t2 Acoustic wave time difference Δt; Step 2: Determine the reservoir porosity value Φ based on the acoustic time difference Δt. t The porosity value Φ t Including the porosity value Φ of the original oil reservoir t1 and the porosity value Φ after reservoir activation t2 ; Step 3: Determine the value of the lithological electrical coefficient of the reservoir. The determined lithological electrical coefficient of the reservoir includes the lithology-related coefficient a, the lithology-related constant b, the cementation index m, and the saturation index n. Step 4: Determine the preset model of resistivity and saturation based on the numerical value of the rock electrical coefficient, and according to the preset model of resistivity and saturation, the oil saturation S1 of the original reservoir, and the porosity value Φ of the original reservoir. t1 and the formation resistivity R of the original oil reservoir t1 Determine the resistivity R of bound water in the original oil reservoir strata. w1 ; Step 5: Based on the preset model of fluid resistivity and temperature, the original reservoir state formation temperature t1, and the bound water resistivity R in the original reservoir formation... w1 Determine the formation water resistivity R after reservoir activation based on the formation temperature t2. w2 ; Step 6: Based on the preset model of resistivity and saturation, and the porosity value Φ after reservoir activation... t2 Formation resistivity R after reservoir activation t2 and the formation water resistivity R after reservoir activation determined in step 5. w2 Determine the oil saturation S2 after reservoir activation; In step 2, the porosity value Φ of the reservoir is determined based on the acoustic time difference Δt. t This includes calculating the reservoir porosity value Φ based on the following formula (1). t : F t =(Δt-Δt ma ) / (Δt f -Δt ma )*1 / C p -V sh *(Δt sh –Δt ma ) / (Δt f -Δt ma ) ……(1) Where: Φ t —Porosity value; Δt — sound wave time difference; Δt ma —Sound wave transit time of the rock skeleton; Δt f —Sound transit time of formation fluids; C p — Acoustic compaction correction coefficient; V sh —Sedimentary clay content; Δt sh —Sonic transit time value of pure mudstone.

2. The method according to claim 1, characterized in that, In step 2, the porosity value Φ of the reservoir is determined based on the acoustic time difference Δt. t This includes using core pressure tests to analyze the relationship between porosity and acoustic transit time regression to determine the reservoir porosity value Φ. t .

3. The method according to claim 2, characterized in that, The porosity value Φ of the reservoir is obtained by analyzing the relationship between porosity and acoustic transit time regression using core pressure testing. t Overburden correction was performed on the core pressure test data to correct the core analysis porosity to the formation porosity.

4. The method according to claim 3, characterized in that The core pressure test data includes porosity and permeability measured through core drilling.

5. The method according to claim 1, wherein In step 3, the rock electrical coefficients a, b, m, and n of the reservoir are determined through core experiments.

6. The method according to claim 5, characterized in that, If the experimental data on rock resistivity is incomplete in step 3, the saturation coefficient is derived from the saturation, porosity, and rock resistivity obtained from the core analysis.

7. The method according to claim 6, characterized in that, The rock resistivity was obtained through deep lateral logging at the repositioning point.

8. The method according to claim 1, characterized in that, The preset model of resistivity and saturation mentioned in step 4 is determined based on Archie's formula, and the preset model is the following formula (2): （2）； The original reservoir oil saturation S1 and the original reservoir porosity value Φ are used to determine the oil saturation S1 and porosity value Φ of the original reservoir. t1 and the formation resistivity R of the original oil reservoir t1 Substituting into the above formula (2), the resistivity R of bound water in the formation under the original reservoir condition is determined. w1 .

9. The method according to claim 8, characterized in that, The oil saturation S1 of the original reservoir mentioned in step 4 was determined by core experiments.

10. The method according to claim 8, characterized in that, The preset model of fluid resistivity and temperature in step 5 is determined based on the Aps formula, and the preset model of fluid resistivity and temperature is the following formula (3): （3）。 11. The method according to claim 10, characterized in that, The original reservoir temperature t1 and the reservoir activation temperature t2 were obtained by well temperature logging.

12. The method according to claim 10, characterized in that, The oil saturation S2 after reservoir activation in step 6 is determined by the following formulas (4) and (5): （4）； Simplifying formula (4), we get: （5）。 13. The method according to claim 12, characterized in that, The formation resistivity R after reservoir activation in step 6 t2 It is the deep-direction resistivity value measured in the well logging series in the later stage of SAGD development.

14. The application of the method for determining the utilization of bottom water heavy oil reservoirs developed by SAGD as described in any one of claims 1-13 during bottom potential tapping in the later stage of SAGD development.

15. The application according to claim 14, characterized in that, The method for determining the activation status of bottom water heavy oil reservoirs developed using the aforementioned SAGD is used to determine the detailed locations for tapping wells.

16. The application according to claim 15, characterized in that, The oil saturation value of each point from below the SAGD production horizontal well to the original oil-water interface is determined according to the method for judging the oil layer activation of the bottom water heavy oil reservoir developed by SAGD. The oil saturation value of the lower limit of reservoir deployment >35% is used as the basis for determining the specific deployment location of the bottom tapping well of SAGD.

17. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it performs the steps of the method for determining the activation status of bottom water heavy oil reservoirs developed by SAGD as described in any one of claims 1-13.

18. A computer device, comprising: At least one processor; as well as A memory storing a computer program executable on the processor, characterized in that, when the processor executes the program, it performs the steps of the method for determining the activation status of bottom-water heavy oil reservoirs developed by SAGD as described in any one of claims 1-13.

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