A low-contrast reservoir fluid identification method, system, device and medium

Abstract

The present invention discloses a method, system, device, and medium for identifying fluids in low-contrast reservoirs, including: obtaining the true formation resistivity RT1D based on the resistivity curve from array sensing; obtaining the ratio coefficient Br of the true formation resistivity RT1D and the deep lateral resistivity RT; determining oil and gas layers and water layers by intersecting the logging acoustic wave time difference curve, porosity curve, and the ratio coefficient; obtaining the movable fluid T2 geometric mean based on the long nuclear magnetic resonance echo interval; and identifying the oil, gas, and water layers of the fluid based on the ratio coefficient Br and the movable fluid T2 geometric mean. The present invention uses the array sensing inversion formation resistivity and deep lateral ratio coefficient method, and the intersection diagram of the movable fluid T2 geometric mean and the array sensing inversion formation resistivity to comprehensively identify fluid properties, effectively solving the problem of identifying fluid properties in low-contrast reservoirs in coastal areas. The method of the present invention is simple, practical, highly operational, and has good application effects.

Description

Technical Field

[0001] The present invention belongs to the technical field of petroleum geological exploration reservoir evaluation and relates to a low-contrast reservoir fluid identification method, system, device and medium. Background Art

[0002] In coastal areas, where lithology is fine and pore structure is complex, high-salinity mud filtrate intrudes deeply, and the salinity differs significantly from that of formation water, the dual lateral resistivity is significantly affected by the intrusion zone and surrounding rock, resulting in a significant decrease in dual lateral resistivity and the formation of low-contrast reservoirs. Traditional porosity-resistivity relationships are ineffective in identifying fluid properties, making multiphase fluid identification even more challenging. Existing methods have poor adaptability and are difficult to identify fluid properties in low-contrast reservoirs. Summary of the Invention

[0003] The purpose of the present invention is to solve the problems in the prior art that the porosity-resistivity relationship cannot effectively identify fluid properties, making multiphase fluid identification more difficult; and the existing methods have poor adaptability and are difficult to identify low-contrast reservoir fluid properties, and to provide a low-contrast reservoir fluid identification method, system, device and medium.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions:

[0005] A low-contrast reservoir fluid identification method comprising:

[0006] Step 1: Based on the resistivity curve in array sensing, obtain the true resistivity RT1D of the formation;

[0007] Step 2: Based on the formation true resistivity RT1D and the deep lateral resistivity RT, obtain the ratio coefficient Br between the two;

[0008] Step 3: Intersect the logging acoustic wave time difference curve, porosity curve and ratio coefficient to determine the oil and gas layer and water layer;

[0009] Step 4: Obtain the T2 geometric mean of the movable fluid based on the long NMR echo interval;

[0010] Step 5: Based on the ratio coefficient Br and the geometric mean of the movable fluid T2, identify the oil, gas and water layers of the fluid.

[0011] A further improvement of the present invention is:

[0012] Furthermore, based on the resistivity curve in array sensing, the true resistivity RT1D of the formation is obtained. Specifically, the array sensing curve, deep lateral curve (RT), time difference curve (AC), neutron curve (CN), density curve (DEN) and natural gamma ray (GR) are input, and the input resistivity curve is inverted in one dimension to obtain the porosity and true resistivity RT1D curve of the formation.

[0013] Further, based on the true formation resistivity RT1D and the deep lateral resistivity RT, the ratio coefficient Br of the two is obtained, specifically:

[0014]

[0015] where Br is the ratio coefficient and the ratio is a decimal.

[0016] Further, the acoustic travel time curve, porosity curve, and ratio coefficient are cross-plotted to judge the oil and gas layers and water layers. Specifically: using the acoustic travel time curve and porosity curve as the abscissa respectively, and the ratio coefficient as the ordinate to judge the oil and gas layers and water layers; among them, for oil and gas layers: RT1D > RT, Br > 1.4; for water layers: RT1D > RT, 1 < Br < 1.4; RT1D is the true formation resistivity inverted by array induction.

[0017] Further, the geometric mean of the mobile fluid T2 is obtained based on the nuclear magnetic resonance long echo interval, specifically:

[0018]

[0019] where T i , 2i , 2i , i , 2i is the transverse relaxation time of nuclear magnetic resonance logging, T 2i = 2 i ms, i = 1, 2, 3…10; P i is the amplitude corresponding to T 2i of nuclear magnetic resonance logging.

[0020] Further, based on the ratio coefficient Br and the geometric mean of the mobile fluid T2, the oil, gas, and water layers of the fluid are identified. Specifically: the geometric mean of T2 in the oil layer is greater than that in the water and gas layers. Using the ratio coefficient Br as the abscissa and the geometric mean of the mobile fluid T2 as the ordinate to make a cross-plot to identify the oil, gas, and water layers of the fluid.

[0021] A low-contrast reservoir fluid identification system includes:

[0022] A first acquisition module, which obtains the true formation resistivity RT1D based on the resistivity curve in array induction;

[0023] A second acquisition module, which obtains the ratio coefficient Br of the two based on the true formation resistivity RT1D and the deep lateral resistivity RT;

[0024] A judgment module, which cross-plots the acoustic travel time curve, porosity curve, and ratio coefficient to judge the oil and gas layers and water layers;

[0025] a calculation module, wherein the calculation module obtains a T2 geometric mean of the movable fluid based on a long nuclear magnetic resonance echo interval;

[0026] The identification module identifies the oil, gas and water layers of the fluid based on the ratio coefficient Br and the geometric mean of the movable fluid T2.

[0027] A terminal device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0028] A computer-readable storage medium stores a computer program, wherein the computer program implements the steps of the above method when executed by a processor.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The present invention obtains the true resistivity RT1D of the formation based on the resistivity curve in array sensing; obtains the ratio coefficient Br of the true resistivity RT1D and the deep lateral resistivity RT; determines the oil and gas layer and the water layer by intersecting the logging acoustic wave time difference curve, porosity curve, and the ratio coefficient; obtains the movable fluid T2 geometric mean based on the long echo interval of nuclear magnetic resonance; identifies the oil, gas, and water layers of the fluid based on the ratio coefficient Br and the movable fluid T2 geometric mean; and comprehensively analyzes the fluid properties based on the obtained oil, gas, and water layers. The present invention uses the array sensing inversion formation resistivity and deep lateral ratio coefficient method, and the intersection diagram of the movable fluid T2 geometric mean and array sensing inversion formation resistivity to comprehensively identify fluid properties, effectively solving the problem of identifying fluid properties in low-contrast oil reservoirs in coastal areas. The method of the present invention is simple, practical, highly operational, and has good application effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0032] Figure 1 A flow chart of the low-contrast reservoir fluid identification method of the present invention;

[0033] Figure 2 is a structural diagram of the low-contrast reservoir fluid identification system of the present invention;

[0034] Figure 3 Another flow chart of the low-contrast reservoir fluid identification method of the present invention;

[0035] Figure 4 is a schematic diagram of the relationship between the ratio coefficient Br and the logging acoustic time difference curve and porosity curve; Figure 4 (a) is the intersection diagram of ratio coefficient Br and porosity; Figure 4 (b) is the intersection diagram of the ratio coefficient Br and the logging acoustic wave time difference;

[0036] Figure 5 Schematic diagram of the relationship between the ratio coefficient Br and the T2 geometric mean of the oil layer, water layer and gas layer;

[0037] Figure 6 This is a schematic diagram of the analysis results taking Well X1 as an example;

[0038] Figure 7 This is a schematic diagram of the analysis results taking Well Y1 as an example. DETAILED DESCRIPTION

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0040] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0041] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0042] In the description of the embodiments of the present invention, it should be noted that if the terms "upper," "lower," "horizontal," "inner," etc. appear, the orientation or positional relationship indicated is based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the inventive product is typically placed when in use. These terms are merely for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. In addition, the terms "first," "second," etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0043] In addition, when the term "horizontal" appears, it does not mean that the component is required to be absolutely horizontal, but it can be slightly inclined. For example, "horizontal" only means that its direction is more horizontal relative to "vertical", and it does not mean that the structure must be completely horizontal, but it can be slightly inclined.

[0044] In the description of the embodiments of the present invention, it should also be noted that unless otherwise clearly specified and limited, when the terms "set", "install", "connected", "connected" appear, they should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0045] The present invention will be further described in detail below with reference to the drawings:

[0046] See Figure 1 , the present invention discloses a method for identifying low-contrast reservoir fluids, which is characterized by including:

[0047] S101: Based on the resistivity curve in the array induction, obtain the true formation resistivity RT1D.

[0048] Input the array induction curve, deep lateral curve (RT), acoustic time difference curve (AC), neutron curve (CN), density curve (DEN) and natural gamma (GR), perform one-dimensional inversion on the input resistivity curve, and obtain the porosity and the true formation resistivity RT1D curve.

[0049] S102: Based on the true formation resistivity RT1D and the deep lateral resistivity RT, obtain the ratio coefficient Br between the two.

[0050]

[0051] Among them, Br is the ratio coefficient, and the ratio is a decimal. The deep lateral resistivity RT is obtained from conventional logging data.

[0052] S103: Intersect the acoustic time difference curve, porosity curve and ratio coefficient of the well logging to judge the oil and gas layer and the water layer.

[0053] Use the acoustic time difference curve and porosity curve of the well logging as the abscissa respectively, and the ratio coefficient as the ordinate to judge the oil and gas layer and the water layer; among them, for the oil and gas layer: RT1D>RT, Br>1.4; for the water layer: RT1D>RT, 1<Br<1.4; RT1D is the true formation resistivity inverted by the array induction. <00​S104: Obtaining a T2 geometric mean of the movable fluid based on the long nuclear magnetic resonance echo interval.

[0055]

[0056] Among them, T 2i is the transverse relaxation time of NMR logging, T 2i =2 i ms,i=1,2,3…10;P i is the NMR logging corresponding to T 2i The amplitude.

[0057] S105: Identify the oil, gas and water layers of the fluid based on the ratio coefficient Br and the geometric mean of the movable fluid T2.

[0058] The T2 geometric mean of the oil layer is greater than that of the water and gas layers. The ratio coefficient Br is used as the abscissa and the T2 geometric mean of the movable fluid as the ordinate to produce a cross-plot and identify the oil, gas and water layers of the fluid.

[0059] See also Figure 2 The present invention discloses a low-contrast reservoir fluid identification system, comprising:

[0060] a first acquisition module, wherein the first acquisition module obtains a true resistivity RT1D of the formation based on a resistivity curve in array sensing;

[0061] A second acquisition module, wherein the second acquisition module obtains a ratio coefficient Br of the true resistivity RT1D and the deep lateral resistivity RT of the formation;

[0062] A judgment module, which judges the oil and gas layer and the water layer by intersecting the logging acoustic wave time difference curve, the porosity curve and the ratio coefficient;

[0063] a calculation module, wherein the calculation module obtains a T2 geometric mean of the movable fluid based on a long nuclear magnetic resonance echo interval;

[0064] The identification module identifies the oil, gas and water layers of the fluid based on the ratio coefficient Br and the geometric mean of the movable fluid T2.

[0065] Example: This method fully relies on the fact that the depth of array induction detection is much greater than that of deep lateral. It uses the ratio coefficient method of array induction inversion true resistivity and deep lateral resistivity, the cross-plot technology of the movable fluid T2 geometric mean of long echo interval of nuclear magnetic resonance and array induction inversion resistivity to comprehensively identify fluid properties, effectively solving the problem of fluid identification in this area. Figure 3 , the specific steps are as follows:

[0066] (1) Obtain relevant parameters using logging data

[0067] The true resistivity RT1D of the formation is obtained by one-dimensional inversion calculation of six resistivity curves at 2 feet using array sensing;

[0068] The T2 geometric mean (T2LM) of movable fluid was calculated using the long echo interval of nuclear magnetic resonance.

[0069]

[0070] Among them, T 2i is the transverse relaxation time of NMR logging, T 2i =2 i ms,i=1,2,3…10;P i is the NMR logging corresponding to T 2i The amplitude.

[0071] (2) Array induction inversion method for formation resistivity and deep lateral ratio coefficient

[0072] The ratio coefficient of the formation resistivity RT1D obtained by array induction inversion to the deep lateral resistivity RT is defined as the ratio of the formation resistivity RT1D obtained by array induction inversion to the deep lateral resistivity RT:

[0073]

[0074] Where Br is the ratio coefficient, which is a decimal; RT1D is the true resistivity of the formation obtained by array induction inversion, in Ω·m; and RT is the deep lateral resistivity, in Ω·m.

[0075] Use the logging acoustic time difference curve and porosity curve as the horizontal axis and the ratio coefficient as the vertical axis to make a cross plot, see Figure 4 (a) and Figure 4 (b); The oil and gas and water layers can be clearly identified, and the ranges are as follows: Oil and gas layer: RT1D>RT, Br>1.4; Water layer: RT1D>RT, 1 <Br<1.4。

[0076] (3) Identification of fluid properties using the T2 geometric mean method of NMR moving fluids

[0077] NMR dual-TE logging mainly uses different echo intervals to perform a measurement to obtain different T2 distribution spectra. Usually, when the reservoir contains natural gas, the gas signal peak of the T2 spectrum with a long echo interval moves toward the direction of smaller T2, causing the echo signal with a long echo interval to attenuate faster. Due to the difference in diffusion coefficients between water and medium-viscosity oil, the distribution position changes on the two T2 distribution spectra. The diffusion coefficient of water is larger than that of medium-viscosity oil. When long echo interval logging is used, the T2 distribution peak of oil shifts forward very little, while the T2 distribution peak of water shifts forward greatly. An oil-water peak will appear on the T2 distribution. Therefore, the T2 distribution spectrum of the water layer shifts forward significantly on the T2 distribution spectrum with a long echo interval, while the oil layer exhibits a dragging phenomenon. Therefore, the use of the long echo interval movable fluid T2 geometric mean, that is, the logarithmic mean of the long echo interval movable fluid T2 spectrum can well describe the center position of the movable fluid T2 spectrum and reflect different fluid properties. The T2 geometric mean of the oil layer is greater than the T2 geometric mean of the water and gas layers. The T2 geometric mean of the movable fluid in the oil layer with a long echo interval is above 50ms, and the T2 geometric mean of the movable fluid in the gas layer with a long echo interval is between 40-60ms. When using array induction inversion to use the formation resistivity and deep lateral ratio coefficient Br as the abscissa and the movable fluid T2 geometric mean as the ordinate to make a cross plot, see Figure 5 , which can clearly and effectively identify the oil, gas and water layers.

[0078] In practice, the above formulas are compiled into code in a language such as FORTRAN or C within logging interpretation software. This code is then compiled into a logging interpretation module and integrated into the software. This module can then be used to process individual wells. Input curves include: deep lateral (RT), time difference (AC), neutron (CN), density (DEN), and natural gamma (GR). Output curves include: total porosity (UPOR), effective porosity (EPOR), permeability (PERM), water saturation (SW), shale content (SH), and ratio coefficient (Br).

[0079] The comprehensive identification of fluid properties using array induction inversion formation resistivity and deep lateral ratio coefficients, along with the long-echo interval NMR T2 geometric mean and array induction inversion formation resistivity crossplot technology, achieved excellent results and played a key role in improving the interpretation accuracy of new wells.

[0080] See also Figure 6 Well X1 oil test section: 2623.6-2694.6m; Interpretation conclusion: Gas zone; Oil test method: Self-flowing production; Oil test result: 8mm nozzle, equivalent daily gas production 166551m 3 , daily oil production 23.42m 3 .

[0081] Analysis of the induction inversion formation resistivity and deep lateral resistivity curves and ratio coefficients shows that the two basically coincide in the impermeable layer and water layer, with a ratio of approximately 1. However, the deep resistivity of the gas layer is significantly greater than the deep lateral resistivity, with a ratio coefficient greater than 1.4. Combined with the physical and electrical properties of conventional logging, the formation resistivity is relatively high, the reservoir physical properties are good, and there is a certain excavation effect, which is interpreted as a gas layer.

[0082] See also Figure 7 Well Y1 oil test section: 2726.1 ~ 2766.0m; oil test method: self-flowing production; oil test results: initial daily oil production 0, daily water production 12.6, water cut 100%, cumulative oil production 0, cumulative water production 306.5, comprehensive water production rate 100%

[0083] The geometric mean T2 of movable fluid in gas layer nuclear magnetic resonance with long echo interval is 40-60ms; the ratio coefficient of true resistivity of formation and deep lateral resistivity curve obtained by array induction inversion is greater than 1.4; the distribution of T2 spectrum of oil layer nuclear magnetic resonance is wide and the tail is far behind. The T2 spectrum with long echo interval reaches 200ms, with obvious dragging phenomenon. The geometric mean T2 of movable fluid in long echo interval is above 50ms, and the ratio coefficient of true resistivity of formation and deep lateral resistivity curve obtained by array induction inversion is greater than 1.4.

[0084] An embodiment of the present invention provides a terminal device. The terminal device of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of each of the aforementioned method embodiments are implemented. Alternatively, when the processor executes the computer program, the functions of each module / unit in each of the aforementioned device embodiments are implemented.

[0085] The computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to accomplish the present invention.

[0086] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0087] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0088] The memory may be used to store the computer programs and / or modules, and the processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory.

[0089] If the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0090] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A low-contrast reservoir fluid identification method, characterized in that: Including: Step 1: Based on the resistivity curve in array induction, obtain the true formation resistivity RT1D. Step 2: Based on the true formation resistivity RT1D and the deep lateral resistivity RT, obtain the ratio coefficient Br between the two. Step 3: Respectively cross the acoustic travel time curve, porosity curve with the ratio coefficient to judge oil and gas layers and water layers. Step 4: Based on the long echo spacing of nuclear magnetic resonance, obtain the geometric mean of the movable fluid T2. Step 5: Based on the ratio coefficient and the geometric mean of T2 of the movable fluid to identify the oil, gas and water layers of the fluid; The ratio coefficient The geometric mean of T2 of movable fluid is used to identify the oil, gas and water layers of the fluid. Specifically, the geometric mean of T2 of the oil layer is greater than the geometric mean of T2 of the water and gas layers. The ratio coefficient is used The cross-plot is made with the T2 geometric mean of the movable fluid as the abscissa and the ordinate to identify the oil, gas and water layers of the fluid.

2. The low-contrast reservoir fluid identification method according to claim 1, characterized in that: The obtaining of the ratio coefficient Br between the true formation resistivity RT1D and the deep lateral resistivity RT specifically is: in, is the ratio coefficient, and the ratio is a decimal.

3. The low-contrast reservoir fluid identification method according to claim 2, characterized in that: The judging of oil and gas layers and water layers by respectively crossing the acoustic travel time curve, porosity curve with the ratio coefficient specifically is: Take the acoustic travel time curve and porosity curve as the abscissa respectively, and the ratio coefficient as the ordinate to judge oil and gas layers and water layers; among them, for oil and gas layers: RT1D > RT, Br > 1.4; for water layers: RT1D > RT, 1 < Br < 1.4; RT1D is the true formation resistivity inverted by array induction.

4. The low-contrast reservoir fluid identification method according to claim 3, characterized in that: The obtaining of the geometric mean of the movable fluid T2 based on the long echo spacing of nuclear magnetic resonance specifically is: in, is the transverse relaxation time of NMR logging, ; NMR logging corresponds to The amplitude.

5. A low-contrast reservoir fluid identification system, characterized in that: Including: The first obtaining module, which obtains the true formation resistivity RT1D based on the resistivity curve in array induction. The second obtaining module, which obtains the ratio coefficient Br between the true formation resistivity RT1D and the deep lateral resistivity RT. The judging module, which respectively crosses the acoustic travel time curve, porosity curve with the ratio coefficient to judge oil and gas layers and water layers. The calculating module, which obtains the geometric mean of the movable fluid T2 based on the long echo spacing of nuclear magnetic resonance. Identification module, the identification module is based on the ratio coefficient and the geometric mean of T2 of the movable fluid to identify the oil, gas and water layers of the fluid; The ratio coefficient The geometric mean of T2 of movable fluid is used to identify the oil, gas and water layers of the fluid. Specifically, the geometric mean of T2 of the oil layer is greater than the geometric mean of T2 of the water and gas layers. The ratio coefficient is used The cross-plot is made with the T2 geometric mean of the movable fluid as the abscissa and the ordinate to identify the oil, gas and water layers of the fluid.

6. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 - 4.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 - 4.

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