CN113031064B - Method, device and equipment for identifying oil layer with low oil saturation - Google Patents
Method, device and equipment for identifying oil layer with low oil saturation Download PDFInfo
- Publication number
- CN113031064B CN113031064B CN201911356892.8A CN201911356892A CN113031064B CN 113031064 B CN113031064 B CN 113031064B CN 201911356892 A CN201911356892 A CN 201911356892A CN 113031064 B CN113031064 B CN 113031064B
- Authority
- CN
- China
- Prior art keywords
- reservoir
- quality index
- irreducible water
- data
- water saturation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 35
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 99
- 238000004364 calculation method Methods 0.000 claims abstract description 50
- 238000004590 computer program Methods 0.000 claims description 4
- 239000011148 porous material Substances 0.000 description 14
- 238000010586 diagram Methods 0.000 description 12
- 230000006872 improvement Effects 0.000 description 8
- 230000000704 physical effect Effects 0.000 description 6
- 238000012360 testing method Methods 0.000 description 5
- 238000011161 development Methods 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000011156 evaluation Methods 0.000 description 3
- QSHDDOUJBYECFT-UHFFFAOYSA-N mercury Chemical compound [Hg] QSHDDOUJBYECFT-UHFFFAOYSA-N 0.000 description 3
- 229910052753 mercury Inorganic materials 0.000 description 3
- 230000005311 nuclear magnetism Effects 0.000 description 3
- 239000011435 rock Substances 0.000 description 3
- 230000015572 biosynthetic process Effects 0.000 description 2
- 230000000994 depressogenic effect Effects 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000005755 formation reaction Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 239000002245 particle Substances 0.000 description 2
- 230000035699 permeability Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000003556 assay Methods 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000004626 scanning electron microscopy Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/30—Analysis
- G01V1/307—Analysis for determining seismic attributes, e.g. amplitude, instantaneous phase or frequency, reflection strength or polarity
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Acoustics & Sound (AREA)
- Environmental & Geological Engineering (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The embodiment of the specification provides a method, a device and equipment for identifying an oil layer with low oil saturation. The method comprises the following steps: obtaining reservoir exploration data corresponding to a reservoir to be identified; calculating a reservoir quality index by using the reservoir exploration data according to a reservoir quality index calculation model; calculating an irreducible water saturation parameter by utilizing the reservoir quality index according to an irreducible water saturation parameter calculation model; and identifying the oil layer with low oil saturation in the reservoir to be identified by using the reservoir quality index and the irreducible water saturation parameter. By the method, the low oil saturation oil layer in the reservoir is identified by using the quality index of the reservoir and the irreducible water saturation parameter under the condition of combining the relation between the irreducible water saturation and the low oil saturation oil layer, so that the low oil saturation oil layer is accurately identified.
Description
Technical Field
The embodiment of the specification relates to the technical field of geological exploration and development, in particular to a method, a device and equipment for identifying an oil layer with low oil saturation.
Background
In the field of geological exploration, after a reservoir possibly containing oil and gas resources is determined, evaluation is carried out on various attribute characteristics of the reservoir before development and exploration are carried out on the reservoir, and an actually developed geological model is determined according to an evaluation result, so that a development scheme can be optimized, and the development success rate and the economic benefit are improved.
In the area of exploration, a variety of formations may be included, including oil, water, dry, and non-reservoir. Among these oil layers, there are oil layers with low oil saturation, but at present, there is no clear definition of oil layers with low oil saturation. And the low oil saturation oil layer has low contrast on logging information such as electricity, sound, nuclear and the like, and the traditional reservoir classification and evaluation method is difficult to identify and evaluate the oil layers and further cannot identify the low oil saturation oil layer from the aspect of the cause of the low oil saturation oil layer. Therefore, there is a need for a method that can identify oil layers with low oil saturation based on the cause of the oil layers.
Disclosure of Invention
The embodiment of the specification aims to provide a method, a device and equipment for identifying a low oil saturation oil layer, so as to solve the problem that the low oil saturation oil layer cannot be accurately identified at present.
In order to solve the technical problem, a method, a device and equipment for identifying an oil layer with low oil saturation provided by the embodiment of the specification are realized as follows:
a method of identifying a low oil saturation reservoir, the method comprising:
obtaining reservoir exploration data corresponding to a reservoir to be identified;
calculating a reservoir quality index by using the reservoir exploration data according to a reservoir quality index calculation model;
calculating an irreducible water saturation parameter by utilizing the reservoir quality index according to an irreducible water saturation parameter calculation model;
and identifying a low oil saturation oil layer in the reservoir to be identified by using the reservoir quality index and the irreducible water saturation parameter.
A low oil saturation reservoir identification apparatus, the apparatus comprising:
the data acquisition module is used for acquiring reservoir exploration data corresponding to a reservoir to be identified;
the reservoir quality index calculation module is used for calculating a reservoir quality index by utilizing the reservoir exploration data according to the reservoir quality index calculation model;
the irreducible water saturation parameter calculation module is used for calculating an irreducible water saturation parameter by utilizing the reservoir quality index according to an irreducible water saturation parameter calculation model;
and the oil layer identification module is used for identifying the oil layer with low oil saturation in the reservoir to be identified by utilizing the reservoir quality index and the irreducible water saturation parameter.
A low oil saturation oil layer identification device comprises a memory and a processor;
the memory to store computer program instructions;
the processor to execute the computer program instructions to implement the steps of: obtaining reservoir exploration data corresponding to a reservoir to be identified; calculating a reservoir quality index by using the reservoir exploration data according to a reservoir quality index calculation model; calculating an irreducible water saturation parameter by utilizing the reservoir quality index according to an irreducible water saturation parameter calculation model; and identifying the oil layer with low oil saturation in the reservoir to be identified by using the reservoir quality index and the irreducible water saturation parameter.
According to the technical scheme provided by the embodiment of the specification, the embodiment of the specification firstly utilizes the acquired reservoir exploration data to calculate and obtain the reservoir quality parameter, then combines the reservoir quality parameter to calculate and obtain the irreducible water saturation parameter, and utilizes the reservoir quality index and the irreducible water saturation parameter to complete the identification of the oil layer with low oil saturation. According to the method, the oil layer with low oil saturation in the reservoir is identified under the condition that the cause of the oil layer with low oil saturation, namely the irreducible water saturation is considered, so that the accuracy of identifying the oil layer with low oil saturation is ensured, and errors in oil layer identification are avoided.
Drawings
In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the specification, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a method for identifying a low oil saturation oil layer according to an embodiment of the present disclosure;
fig. 2A is a schematic diagram of a pore structure in a first type of reservoir in accordance with an embodiment of the present disclosure;
fig. 2B is a schematic diagram of a pore structure in a second type of reservoir according to an embodiment of the present disclosure;
fig. 2C is a schematic diagram of a pore structure in a third type of reservoir according to an embodiment of the present disclosure;
fig. 2D is a schematic diagram of a pore structure in a fourth type of reservoir according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a reservoir classification with a pore structure according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of a reservoir quality index calculation model according to an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of a model for computation of an irreducible water saturation parameter in accordance with an embodiment of the present disclosure;
FIG. 6 is a schematic diagram illustrating identification of a low oil saturation reservoir in a well log according to an embodiment of the present disclosure;
fig. 7 is a block diagram of an identification apparatus for a low oil saturation oil layer according to an embodiment of the present disclosure;
fig. 8 is a block diagram of an oil layer identification apparatus with low oil saturation according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present specification without any creative effort shall fall within the protection scope of the present specification.
The method for identifying the oil layer with low oil saturation according to the embodiment of the present disclosure is described below with reference to fig. 1, where an execution subject of the method is a computer device, and the computer device includes, but is not limited to, a server, an industrial personal computer, an all-in-one machine, and a PC. The method for identifying the oil layer with low oil saturation comprises the following specific steps:
s110: reservoir exploration data corresponding to a reservoir to be identified is obtained.
The reservoir to be identified is the stratum to be identified. In the reservoir to be identified, a conventional oil-water layer, a low oil saturation oil layer and a dry layer may be contained. Since the low oil saturation oil layer cannot be identified based on the cause of the low oil saturation oil layer in the prior art when there is a clear definition for the low oil saturation oil layer, in the embodiment of the present specification, the low oil saturation oil layer in the reservoir to be identified needs to be identified based on the above requirement.
In practical application, a plurality of different types of well logging and exploratory wells are preset for a reservoir, and are used for acquiring data such as acoustic waves, electromagnetic waves and geological structures of the reservoir. And taking data obtained by exploring the reservoir to be identified through well logging and exploratory well as reservoir exploration data. The reservoir exploration data comprises at least one of the following: sound wave time difference data, density data and mud content data. In practical applications, the reservoir exploration data may not be limited to the above examples, and will not be described herein.
S120: and calculating the reservoir quality index by using the reservoir exploration data according to the reservoir quality index calculation model.
The reservoir quality index is an optimal macroscopic physical property parameter for quantitatively representing a reservoir microscopic pore structure, and is suitable for identifying a low-oil-saturation oil layer in a reservoir. Therefore, the low oil saturation reservoir in the reservoir to be identified can be identified by calculating the reservoir quality index corresponding to the reservoir to be identified.
The reservoir quality index calculation model is a model for calculating a reservoir quality index. In one embodiment, the reservoir quality index model may be derived by fitting reservoir survey data. According to reservoir exploration sample data corresponding to a reservoir, which is obtained in previous exploration research, the reservoir quality index calculation model is obtained through fitting by combining with the label corresponding to the reservoir exploration sample data, namely the corresponding relation between the reservoir exploration sample data and the reservoir quality index.
And inputting the reservoir exploration data into the reservoir quality index calculation model to obtain the reservoir quality index. Specifically, the formula RQI = Φ (AC) × Φ (DEN)/V may be used sh Calculating a reservoir quality index, wherein RQI is the reservoir quality index, phi (AC) = a + b multiplied by AC, a and b are coefficients, AC is sound wave time difference data, phi (DEN) = c + d multiplied by DEN, c and d are coefficients, DEN is density data, V is the density data, and sh the mud content data is shown.
A specific scenario example is used for explanation, and as shown in fig. 4, a schematic diagram of a reservoir quality index calculation model is shown. In order to make the relation between the reservoir quality index and the stratum exploration data be linear correlation, the acoustic time difference data and the density are processedThe data were adjusted to obtain φ (AC) =32.7158+0.18454 × AC/0.3048, φ (DEN) =168.52-63.44 × DEN, such that the reservoir quality index RQI is equal to φ (AC) × (DEN)/V sh The relation has linear correlation, and the relation is used as a calculation model of the saturation parameter of the irreducible water, so that the calculation in the subsequent process is convenient.
S130: and calculating the irreducible water saturation parameter by utilizing the reservoir quality index according to the irreducible water saturation parameter calculation model.
When oil and gas are transported to a sandstone reservoir from an oil production layer, the transported oil and gas cannot completely displace water in the reservoir, and a certain amount of water still remains in rock pores. Most of the water is distributed and remained in corners and fine pores where the rock particles contact or adsorbed on the surfaces of the rock skeleton particles. This portion of water is almost immobile due to the particular distribution and presence conditions, and its presence and distribution is significantly influenced by the nature of the solids, which portion is called irreducible water, and the saturation corresponding to said irreducible water is called irreducible water saturation. The high irreducible water saturation easily influences the formation of the oil layer with low oil saturation, so the irreducible water saturation is an important factor for identifying the oil layer with low oil saturation. The identification of low oil saturation reservoirs in the subsequent step may be performed by calculating the irreducible water saturation parameter.
The irreducible water saturation parameter calculation model is a model for calculating an irreducible water saturation parameter. In one embodiment, the irreducible water saturation parameter calculation model may be derived by fitting a reservoir quality index. And fitting to obtain the computation model of the irreducible water saturation parameter based on the reservoir quality sample parameters obtained or calculated in the previous exploration research by combining the labels corresponding to the reservoir quality sample parameters and the corresponding relation between the reservoir quality sample parameters and the irreducible water saturation parameters.
And inputting the reservoir quality index into the computation model of the irreducible water saturation parameter to obtain a corresponding irreducible water saturation parameter through computation. Specifically, the formula S can be used wi ＝e×ln (RQI) + f calculating the irreducible water saturation parameter, wherein S wi For irreducible water saturation parameters, e and f are coefficients, and RQI is a reservoir quality index.
A specific scenario example is described below, as shown in fig. 5, which is a schematic diagram of a model for irreducible water saturation parameter calculation. Fitting discrete data samples in the graph based on the relation between the irreducible water saturation parameter and the reservoir quality index to obtain S wi And = 10.4 xln (RQI) +38.055, so that a specific corresponding relation between the irreducible water saturation parameter and the reservoir quality index is determined, and the irreducible water saturation parameter is used as a calculation model of the irreducible water saturation parameter, and the low oil saturation oil layer in the reservoir can be conveniently identified directly according to the calculated parameter.
S140: and identifying a low oil saturation oil layer in the reservoir to be identified by using the reservoir quality index and the irreducible water saturation parameter.
The oil layer with low oil saturation is an oil layer with low oil saturation. To facilitate identification of the low oil saturation reservoir, the low oil saturation reservoir may first be characterized as a reservoir having an oil saturation of less than 50% and an irreducible water saturation of between 40% and 80%. The oil layer with low oil saturation shows low reservoir resistivity and lower resistance increasing rate of the oil-gas layer on logging. The oil layer with low oil saturation can be better distinguished by the definition.
In an embodiment, the method for identifying the oil layer with low oil saturation may be that a reservoir category corresponding to the reservoir to be identified is determined by using the reservoir quality index and the irreducible water saturation parameter, and then the oil layer with low oil saturation in the reservoir to be identified is identified according to the reservoir category based on a reservoir category partition strategy.
The reservoir classification strategy is based on the porosity, permeability and T of the reservoir 2 The reservoir is classified by parameters such as geometric mean value, displacement pressure, mercury withdrawal efficiency, sorting coefficient and the like, and the parameters can be obtained by analysis and assay experiments such as nuclear magnetism, mercury intrusion and the like. In one embodiment, the above parameters may be in accordance withThe reservoirs are divided into four categories, namely a first category reservoir, a second category reservoir, a third category reservoir and a fourth category reservoir. The first type of reservoir has the best physical property, and the pore throat type is a large-pore coarse throat type; the second type of reservoir has better physical property, and the pore throat type is a mesopore-medium throat type; the third type of reservoir has poor physical properties, and the pore throat type is a fine pore throat type; the fourth type of reservoir has the worst physical properties, and the pore throat type is a micropore micro-throat type. As shown in fig. 2A to 2D, the reservoirs of the first type, the second type, the third type and the fourth type are characterized by mercury intrusion, nuclear magnetism, cast body slices and scanning electron microscopy. It can be seen that these four types of reservoirs have some differences in physical properties.
The reservoir classification strategy comprises a corresponding relation between a first type reservoir and a conventional oil-water layer, a corresponding relation between a second type reservoir and a first type oil-containing low-oil-saturation oil layer, a corresponding relation between a third type reservoir and a second type oil-containing low-oil-saturation oil layer and a corresponding relation between a fourth type reservoir and a non-reservoir. Specifically, as shown in fig. 3, the irreducible water saturation in the conventional water-oil reservoir is less than 40%, and medium or high oil-gas flow and/or water production is obtained during oil testing; the saturation of the bound water in the oil layer with low oil saturation is 40-60%, and medium oil-gas flow is obtained during oil testing; the saturation of the irreducible water in the oil layer with low oil saturation is 60-80%, and low or medium oil-gas flow is obtained during oil testing; irreducible water saturation in a non-reservoir is more than 80%, and capacity is generally not generated during oil testing. Specifically, according to the data, the reservoirs with the reservoir quality index in the range of 0.3-1 μm and the irreducible water saturation parameter in the range of 40-60% can be divided into low oil saturation oil layers; reservoirs with reservoir quality index ranging from 0.2 μm to 0.7 μm and irreducible water saturation parameter greater than 60% are classified into two types of oil layers with low oil saturation. The oil layer with low oil saturation comprises the oil layer with low oil saturation of the first kind and the oil layer with low oil saturation of the second kind, namely when the reservoir is identified, the oil layer with low oil saturation of the first kind and the oil layer with low oil saturation of the second kind can be identified as the oil layer with low oil saturation.
According to the reservoir classification strategy determined in the introduction, the low oil saturation oil layer in the reservoir to be identified can be identified by using the reservoir quality index and the irreducible water saturation parameter. Specifically, the reservoir category corresponding to the reservoir to be identified can be determined according to the reservoir quality index and the irreducible water saturation parameter, and the specific category of the oil layer corresponding to the reservoir is determined based on the reservoir category, so that the identification of the oil layer with low oil saturation in the reservoir to be identified is realized.
The method for identifying the oil layer with low oil saturation is applied by using a specific scene example. And identifying the oil layer with low oil saturation aiming at the X well sunken in the Nanbao. As shown in fig. 6, a schematic of the log identification data of the south castle pit X well. According to the logging identification data, calibrating and fitting the reservoir quality index obtained by calculation according to the porosity and permeability obtained by actual measurement and the reservoir quality index obtained by fitting the acoustic time difference data, the density data and the mud content data in the X-well of the Nanburg pit, so as to complete the establishment of a reservoir quality index calculation model; and calibrating and fitting the irreducible water saturation obtained by actual nuclear magnetism measurement and the irreducible water saturation obtained by reservoir quality index calculation, thereby completing the construction of an irreducible water saturation calculation model.
Inputting reservoir exploration data measured in the X well of the recessed Nanburg well, including acoustic time difference data, density data, shale content data and the like, into the reservoir quality index calculation model, and calculating to obtain the reservoir quality index of each stratum; and inputting the reservoir quality index into the irreducible water saturation parameter calculation model, calculating to obtain irreducible water saturation parameters of each stratum, and comparing the irreducible water saturation parameters and the reservoir category division strategy according to the reservoir quality index and the irreducible water saturation parameters obtained through calculation, so as to determine the reservoir categories corresponding to each stratum in the Nanburg depressed X well, as shown in figure 6, and determine the oil layer with low oil saturation therein.
As shown in fig. 6, for the interval No. 1 in the depressed X well of the south castle, in actual production, a test oil conclusion shows that the daily oil yield is 13.01 cubic meters, the daily water yield is 13.1 cubic meters, the water yield reaches 40%, the accumulated oil yield is 18.31 cubic meters, and the accumulated water yield is 15.8 cubic meters, and the oil layer belongs to a typical oil layer with low oil saturation. And according to the determined category corresponding to the interval, the interval is divided into a third type of reservoir, namely a second type of oil layer with low oil saturation.
By combining the embodiment of the method and the introduction of the scene example, it can be seen that when the oil layer is identified, the low oil saturation oil layer identification method utilizes reservoir exploration data to sequentially calculate and obtain a reservoir quality index and an irreducible water saturation parameter based on a pre-constructed reservoir quality index calculation model and an irreducible water saturation parameter calculation model, and then combines a preset reservoir category division strategy to complete identification of the low oil saturation oil layer, so that the accuracy of identification of the low oil saturation oil layer is ensured and unnecessary errors in oil layer identification are avoided under the condition of combining a low oil saturation cause.
An embodiment of a low oil saturation oil layer identification apparatus provided in the computer device is described below with reference to fig. 7, where the apparatus includes:
a data acquisition module 710 for acquiring reservoir exploration data corresponding to the reservoir to be identified;
the reservoir quality index calculation module 720 is used for calculating a reservoir quality index by using the reservoir exploration data according to the reservoir quality index calculation model;
the irreducible water saturation parameter calculating module 730 is used for calculating an irreducible water saturation parameter by using the reservoir quality index according to the irreducible water saturation parameter calculating model;
and the oil layer identification module 740 is configured to identify a low oil saturation oil layer in the reservoir to be identified by using the reservoir quality index and the irreducible water saturation parameter based on a reservoir category classification strategy.
An identification device for oil layer with low oil saturation according to the embodiment of the present specification is described below with reference to fig. 8. The low oil saturation reservoir identification device may include a memory and a processor.
In this embodiment, the memory may be implemented in any suitable manner. For example, the memory may be a read-only memory, a mechanical hard disk, a solid state disk, a U disk, or the like. The memory may be used to store computer instructions.
In this embodiment, the processor may be implemented in any suitable manner. For example, the processor may take the form of, for example, a microprocessor or processor and a computer-readable medium that stores computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, an embedded microcontroller, and so forth. The processor may execute the computer instructions to perform the steps of: obtaining reservoir exploration data corresponding to a reservoir to be identified; calculating a reservoir quality index by using the reservoir exploration data according to a reservoir quality index calculation model; calculating an irreducible water saturation parameter by utilizing the reservoir quality index according to an irreducible water saturation parameter calculation model; and identifying the low oil saturation oil layer in the reservoir to be identified by utilizing the reservoir quality index and the irreducible water saturation parameter based on a reservoir category division strategy.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD) (e.g., a Field Programmable Gate Array (FPGA)) is an integrated circuit whose Logic functions are determined by a user programming the Device. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as ABEL (Advanced Boolean Expression Language), AHDL (alternate Hardware Description Language), traffic, CUPL (core universal Programming Language), HDCal, jhddl (Java Hardware Description Language), lava, lola, HDL, PALASM, rhyd (Hardware Description Language), and vhjh-Language (Hardware Description Language), which is currently used by Hardware compiler-Language-2. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
From the above description of the embodiments, it is clear to those skilled in the art that the present specification can be implemented by software plus a necessary general hardware platform. Based on such understanding, the technical solutions of the present specification may be essentially or partially implemented in the form of software products, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and include instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments of the present specification.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The description is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
While the specification has been described with examples, those skilled in the art will appreciate that there are numerous variations and permutations of the specification without departing from the spirit of the specification, and it is intended that the appended claims encompass such variations and modifications without departing from the spirit of the specification.
Claims (7)
1. A low oil saturation oil layer identification method is characterized by comprising the following steps:
obtaining reservoir exploration data corresponding to a reservoir to be identified; the reservoir exploration data comprising at least one of: sound wave time difference data, density data and mud content data;
calculating a reservoir quality index by using the reservoir exploration data according to a reservoir quality index calculation model; the calculating the reservoir quality index by using the reservoir exploration data according to the reservoir quality index calculation model comprises the following steps: using the formula RQI = φ (AC) x φ (DEN)/V sh Calculating a reservoir quality index, wherein RQI is the reservoir quality index, phi (AC) = a + b multiplied by AC, a and b are coefficients, AC is sound wave time difference data, phi (DEN) = c + d multiplied by DEN, c and d are coefficients, DEN is density data, V is the density data, and sh the mud content data is obtained;
calculating an irreducible water saturation parameter by utilizing the reservoir quality index according to an irreducible water saturation parameter calculation model;
identifying a low oil saturation oil layer in the reservoir to be identified by using the reservoir quality index and the irreducible water saturation parameter, wherein the identification comprises the following steps: determining a reservoir category corresponding to the reservoir to be identified by using the reservoir quality index and the irreducible water saturation parameter; and identifying the low oil saturation oil layer in the reservoir to be identified according to the reservoir category based on a reservoir category division strategy.
2. The method of claim 1, wherein the reservoir quality index calculation model is fit to reservoir survey data.
3. The method of claim 1, wherein the irreducible water saturation parameter calculation model is fit from a reservoir quality index.
4. The method of claim 1, wherein calculating an irreducible water saturation parameter using the reservoir quality index according to an irreducible water saturation parameter calculation model comprises:
using the formula S wi Calculating irreducible water saturation parameter of = e × ln (RQI) + f, wherein S wi For the irreducible water saturation parameter, e and f are coefficients, and RQI is a reservoir quality index.
5. The method of claim 1, wherein the reservoir categories include at least one of: the reservoir type comprises a first reservoir type, a second reservoir type, a third reservoir type and a fourth reservoir type;
the reservoir classification strategy comprises the following steps:
the corresponding relation between the first reservoir and the conventional oil-water layer;
the corresponding relation between the second reservoir and the low oil saturation oil layer;
the corresponding relation between the third type reservoir and the second type oil layer with low oil saturation;
and the fourth type of reservoir corresponds to a non-reservoir.
6. An apparatus for identifying a low oil saturation reservoir, the apparatus comprising:
the data acquisition module is used for acquiring reservoir exploration data corresponding to a reservoir to be identified; the reservoir exploration data comprising at least one of: sound wave time difference data, density data and mud content data;
the reservoir quality index calculation module is used for calculating a reservoir quality index by utilizing the reservoir exploration data according to a reservoir quality index calculation model; the calculating the reservoir quality index by using the reservoir exploration data according to the reservoir quality index calculation model comprises the following steps: using the formula RQI = φ (AC) x φ (DEN)/V sh Calculating the quality index of the reservoir, wherein RQI is the quality index of the reservoir, phi (AC) = a + b multiplied by AC, wherein a and b are coefficients, AC is sound wave time difference data, phi (DEN) = c + d multiplied by DEN, wherein c and d are coefficients, DEN is density data, V sh The mud content data is obtained;
the irreducible water saturation parameter calculation module is used for calculating an irreducible water saturation parameter by utilizing the reservoir quality index according to an irreducible water saturation parameter calculation model;
the oil layer identification module is used for identifying a low oil saturation oil layer in the reservoir to be identified by using the reservoir quality index and the irreducible water saturation parameter based on a reservoir category division strategy, and comprises the following steps: determining a reservoir category corresponding to the reservoir to be identified by using the reservoir quality index and the irreducible water saturation parameter; and identifying the low oil saturation oil layer in the reservoir to be identified according to the reservoir category based on a reservoir category division strategy.
7. A low oil saturation oil layer identification device comprises a memory and a processor;
the memory to store computer program instructions;
the processor to execute the computer program instructions to implement the steps of: obtaining reservoir exploration data corresponding to a reservoir to be identified; the reservoir exploration data comprising at least one of: sound wave time difference data, density data and mud content data; calculating a reservoir quality index by using the reservoir exploration data according to a reservoir quality index calculation model; the calculating the reservoir quality index by using the reservoir exploration data according to the reservoir quality index calculation model comprises the following steps: using the formula RQI = φ (AC) x φ (DEN)/V sh Calculating a reservoir quality index, wherein RQI is the reservoir quality index, phi (AC) = a + b multiplied by AC, a and b are coefficients, AC is sound wave time difference data, phi (DEN) = c + d multiplied by DEN, c and d are coefficients, DEN is density data, V is the density data, and sh the mud content data is obtained; calculating an irreducible water saturation parameter by utilizing the reservoir quality index according to an irreducible water saturation parameter calculation model; identifying a low oil saturation oil layer in the reservoir to be identified by using the reservoir quality index and the irreducible water saturation parameter based on a reservoir category division strategy, wherein the identification comprises the following steps: determining a reservoir category corresponding to the reservoir to be identified by using the reservoir quality index and the irreducible water saturation parameter; and identifying the low oil saturation oil layer in the reservoir to be identified according to the reservoir category based on a reservoir category division strategy.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911356892.8A CN113031064B (en) | 2019-12-25 | 2019-12-25 | Method, device and equipment for identifying oil layer with low oil saturation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911356892.8A CN113031064B (en) | 2019-12-25 | 2019-12-25 | Method, device and equipment for identifying oil layer with low oil saturation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113031064A CN113031064A (en) | 2021-06-25 |
| CN113031064B true CN113031064B (en) | 2022-11-04 |
Family
ID=76458340
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911356892.8A Active CN113031064B (en) | 2019-12-25 | 2019-12-25 | Method, device and equipment for identifying oil layer with low oil saturation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113031064B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101806215A (en) * | 2010-03-05 | 2010-08-18 | 中国石油集团川庆钻探工程有限公司 | Method for discriminating reservoir fluid type by irreducible water saturation data |
| CN109753755A (en) * | 2019-01-25 | 2019-05-14 | 中国石油天然气集团有限公司 | A kind of method of determining reservoir water saturation |
| CN110160927A (en) * | 2019-05-16 | 2019-08-23 | 中海油田服务股份有限公司 | A kind of method and device of determining irreducible water saturation |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106093350B (en) * | 2016-08-10 | 2018-05-04 | 中国石油天然气股份有限公司 | Method for determining heterogeneous carbonate reservoir saturation index |
-
2019
- 2019-12-25 CN CN201911356892.8A patent/CN113031064B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101806215A (en) * | 2010-03-05 | 2010-08-18 | 中国石油集团川庆钻探工程有限公司 | Method for discriminating reservoir fluid type by irreducible water saturation data |
| CN109753755A (en) * | 2019-01-25 | 2019-05-14 | 中国石油天然气集团有限公司 | A kind of method of determining reservoir water saturation |
| CN110160927A (en) * | 2019-05-16 | 2019-08-23 | 中海油田服务股份有限公司 | A kind of method and device of determining irreducible water saturation |
Non-Patent Citations (1)
| Title |
|---|
| 储层品质评价中的核磁共振研究;赵建斌等;《西南石油大学学报（自然科学版）》;20180228;第40卷(第1期);第89-96页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113031064A (en) | 2021-06-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| AU2014306018B2 (en) | Image-based direct numerical simulation of petrophysical properties under simulated stress and strain conditions | |
| Strebelle et al. | Modeling of a deepwater turbidite reservoir conditional to seismic data using principal component analysis and multiple-point geostatistics | |
| Thompson et al. | Application of a new grain-based reconstruction algorithm to microtomography images for quantitative characterization and flow modeling | |
| Chehrazi et al. | Pore-facies as a tool for incorporation of small-scale dynamic information in integrated reservoir studies | |
| CN108252710B (en) | Method and device for determining water saturation of oil reservoir | |
| CN108694264B (en) | Method for determining permeability of shale gas reservoir | |
| CN107367762B (en) | Method and device for determining reservoir parameters | |
| CN106355571B (en) | Method and device for determining quality of dolomite reservoir | |
| CN107329186B (en) | Method and device for determining secondary erosion porosity development degree of igneous rock reservoir | |
| Lu et al. | Assisted history matching for fractured reservoirs by use of hough-transform-based parameterization | |
| Zhang et al. | 3D porosity modeling of a carbonate reservoir using continuous multiple-point statistics simulation | |
| CN111025409B (en) | Flooded layer evaluation method and device and storage medium | |
| CN109298464B (en) | Tight sandstone reservoir diagenetic facies logging identification method and device | |
| US10718188B2 (en) | Method for evaluation of fluid transport properties in heterogenous geological formation | |
| Askari et al. | A fully integrated method for dynamic rock type characterization development in one of Iranian off-shore oil reservoir | |
| CN109870743B (en) | Page-based seam space spread prediction method and device | |
| CN113031064B (en) | Method, device and equipment for identifying oil layer with low oil saturation | |
| Fu et al. | Modeling and simulation of transition zones in tight carbonate reservoirs by incorporation of improved rock typing and hysteresis models | |
| CN111323814B (en) | Method for quantitatively determining water saturation of sandstone reservoir based on rock physical template | |
| CN109358364B (en) | Method, device and system for establishing underground river reservoir body geological model | |
| CN116927771A (en) | Method, device, equipment and medium for predicting total organic carbon data of shale reservoir | |
| Fang et al. | Study on discriminant method of rock type for porous carbonate reservoirs based on Bayesian theory | |
| CN116821786A (en) | Hypotonic reservoir classification method, device and medium | |
| CN115929292A (en) | Logging method, device and equipment based on fusion of imaging logging and conventional logging | |
| CN113818867B (en) | Method, system, medium, equipment and application for constructing pseudo capillary pressure curve |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |