Method for recognizing light oil reservoir and gas condensate reservoir in stratum and application

A light oil layer technology, applied in the distribution characteristics of gas logging hydrocarbon components to identify light oil and condensate gas layers in the formation, and to identify light oil layers and condensate gas layers in the formation, it can solve the problem of reliability and The research or improvement of the effect cannot be said to be sufficient, etc., to achieve the effect of improving the interpretation rate, high reliability, and simple method

Active Publication Date: 2017-12-08
CNOOC TIANJIN BRANCH
2 Cites 6 Cited by

AI-Extracted Technical Summary

Problems solved by technology

[0008] Therefore, as far as the current existing technology is concerned, the research or improvement of the reliability and ef...
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Method used

[0078] For the number of test wells, in the present invention, test wells can be more than 1, preferably more than 5, more preferably more than 7, most preferably...
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Abstract

The invention relates to a method for recognizing a light oil reservoir and a gas condensate reservoir in a stratum and application. The method comprises the steps that firstly, a testing well is obtained, gas compositions of different depth positions in the testing well are measured, and comprise C1, C2, C3, iC4, nC4 and the percentage composition of optional iC5 and nC5 in all positions; secondly, the measuring values of the gas compositions are subject to normalization processing, and the relative contents of the gas compositions are calculated; thirdly, according to the relative content distribution data obtained through the normalization processing in the second step, a curve graph is made; fourthly, in the curve graph in the third step, a gas curve is built; fifthly, according to the contrast relation of the relative content distribution data curve and the gas curve of the compositions of gas logging of each position, the light oil reservoir and the gas condensate reservoir in the stratum are recognized. Through the method, the light oil reservoir and the gas condensate reservoir in the stratum can be effectively recognized, and the interpretation coincidence rate of the hydrocarbon reservoir can be improved.

Application Domain

Prospecting/detection of underground/near-surface gasesBorehole/well accessories

Technology Topic

Gas compositionCoincidence +4

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  • Method for recognizing light oil reservoir and gas condensate reservoir in stratum and application
  • Method for recognizing light oil reservoir and gas condensate reservoir in stratum and application
  • Method for recognizing light oil reservoir and gas condensate reservoir in stratum and application

Examples

  • Experimental program(4)

Example

[0072]
[0073] In the first embodiment of the present invention, a method for identifying light oil layers and condensate gas layers in a formation is provided.
[0074] data collection
[0075] In the first embodiment, the basic data acquisition is achieved through gas logging. This embodiment includes step 1, namely obtaining test wells.
[0076] The “obtained test well” refers to data sampling based on existing test wells. Of course, the “obtained” also includes newly established test wells.
[0077] For the specific method of establishing the test well, the present invention is not particularly limited. The establishment of test wells can be based on existing mature theories. At the same time, with the help of various required instruments and equipment, dynamic testing of downhole oil and gas is used for basic data collection. The basic principles or specific means on which data collection is based are not particularly limited in the present invention, as long as they have a qualified accuracy.
[0078] Regarding the number of test wells, in the present invention, the number of test wells may be one or more, preferably five or more, more preferably seven or more, and most preferably nine or more. For the first embodiment, the establishment of multiple test wells can make the final prediction or interpretation result of this embodiment more accurate.
[0079] For the distribution of test wells, each test well can be distributed in the test area according to actual needs. Preferably, for areas that need to be intensively tested, each test well can be evenly distributed at a certain interval. For each test well, it can be arranged linearly or arranged in an array with a certain shape. There is no special limitation on the interval between each test well in the present invention, as long as it meets the requirements of safe operation. For example, the interval between test wells can be 5000 meters or more, preferably 1000 meters or more.
[0080] In this embodiment, the test well is established in a manner perpendicular to the ground surface. It should be noted that "vertical" here includes the allowable actual error, such as ±5° or less.
[0081] Measure the gas composition of different depth layers in the test well, and the gas composition includes C in each layer 1 , C 2 , C 3 , IC 4 And nC 4 , And optional iC 5 And nC 5 Percentage content, where C 1 Represents a hydrocarbon with carbon atom 1, C 2 Represents a hydrocarbon with 2 carbon atoms, C 3 Represents a hydrocarbon with 3 carbon atoms, iC 4 Represents a hydrocarbon with a heterogeneous structure with 4 carbon atoms, nC 4 Represents a hydrocarbon with a positive structure with 4 carbon atoms. Preferably, the hydrocarbon gas is an alkane gas. It should be noted that for the gas sampling at different depths in the above test well, generally speaking, the gas samples can contain C 1 , C 2 , C 3 , IC 4 And nC 4 Such components, but whether there is iC in actual sampling 5 And nC 5 The composition depends on the different address structure or actual sampling method.
[0082] For the test of gas samples in each formation, a gas chromatograph equipped with flame ionization and thermal conductivity detectors can be used; for most components, the detection limit is 10 -7 ~10 -5; The main component analysis accuracy is within ±5%.
[0083] In step 1, the measurement of the gas composition of the layers at different depths in the test well includes measuring the gas composition of the layers at different depths or the same depth in different test wells. For the depth of the test well, the depth in the different depths is the vertical depth to the ground, and the depth range is 2000m-4000m, preferably 2500m-3500m. As mentioned above, the vertical here is the vertical including the allowable error.
[0084]
[0085] Collect gas logging data based on the above methods, and use the following methods to process the gas composition data of different depth layers in the logging data.
[0086] In step 2, the measured value of the gas composition is normalized, and the relative content of each gas component is calculated. The normalization method includes the following calculation (with no iC 5 And nC 5 Time as an example):
[0087]
[0088]
[0089]
[0090]
[0091]
[0092] The specific function of normalization is to summarize the statistical distribution of a unified sample, which limits the data to be processed (through a certain algorithm) within a certain range. First of all, normalization is for the convenience of subsequent data processing, and the second is to ensure faster convergence when the program is running. In the present invention, in one embodiment, in the normalization method that can be listed, C 1 The content is set to 100% or 1, etc., so as to further calculate the other components relative to C 1 Relative content.
[0093] Then, according to the normalized data obtained in step 2, step 3 is performed, that is, a graph is drawn based on the relative content distribution data of each component of each layer after the normalization processing in step 2, and the graph is based on the relative content It is the ordinate, and different gas components are the abscissa.
[0094] In a preferred embodiment of the present invention, the graph in step 3 is a graph established based on the data after thinning the data.
[0095] Among the various data obtained by normalization processing, there are often many records and there are unavoidable duplication or errors. In order to facilitate the visualization of graphs and reduce the judgment bias caused by noise, certain rules must be adopted to minimize the number of data points while ensuring the shape of the vector curve remains unchanged. This process is called Thin out. After the data is thinned out, the amount is greatly reduced, and it is basically guaranteed to reflect the basic shape characteristics of the original graph or curve, which can save space and time for further processing.
[0096] The data thinning method can be processed according to actual needs. Commonly used data thinning methods can be the step size method, the Douglas-Peuker algorithm, and the offset limit method. These methods can be implemented relatively quickly through computer readable programs.
[0097] In the preferred embodiment of the present invention, the Douglas-Peuker algorithm can be used. Generally, a complete curve or a certain line segment is considered from an overall perspective. The basic idea is:
[0098] 1) Connect a straight line to the first and last points of the curve, find the distance between all points on the curve and the straight line, and find the maximum distance value dmax, compare dmax with the preset threshold D:
[0099] 2) If dmax
[0100] If dmax≥D, keep the coordinate point corresponding to dmax and divide the curve into two parts with this point as the boundary. Repeat this method for these two parts, that is, repeat steps 1) and 2) until all dmax are equal
[0101] Obviously, the thinning precision of this algorithm is related to the threshold. The larger the threshold, the greater the degree of simplification and the more points are reduced. On the contrary, the lower the degree of simplification, the more points are retained, and the more the shape tends to the original curve. The determination of the threshold can be determined according to actual accuracy requirements.
[0102] In addition, the dilution accuracy of the DP algorithm is significantly improved compared to other thinning methods. On the one hand, because the threshold is generally the maximum allowable error of the corresponding feature, on the other hand, because the algorithm can achieve between deletion and retention A better balance, that is, it can fully reduce the number of points, while keeping the feature points as much as possible.
[0103] The graph produced after data dilution can more concisely and more intuitively reflect the change relationship of the gas distribution in each test layer, which is beneficial to the subsequent interpretation.
[0104] In step 3, in a preferred embodiment of the present invention, the ordinate is a logarithmic ordinate, and the gas component in the abscissa includes C 1 , C 2 , C 3 , IC 4 And nC 4 And optional iC 5 And nC 5 Represents the gas composition.
[0105] Specifically, in the process of gas logging and logging, the distribution of the content of different gases in layers of different depths is quite different. At the same time, the percentage content of different gases in the layers at the same depth or the relative content after normalization are also quite different. Therefore, when the ordinate of the general average linear scale is used, during the mapping process, limited by the size of the visible area, there will be too dense data distribution in some areas, and the data in some areas are too distributed and sparse, which is not conducive to observation And subsequent judgments. Therefore, in the present invention, preferably, the ordinate is set to a logarithmic coordinate. As the abscissa, C can be expressed at the same interval 1 , C 2 , C 3 , IC 4 , NC 4 , IC 5 And nC 5 Gas component. That is, in some preferred embodiments of the present invention, the graph according to step 3 is a graph in a semi-logarithmic coordinate system, and the "relative content" represented by the ordinate is a normalized relative number or relative amount, For example, take C 1 The content is set to 100 or 100% or 1, etc., and the calculated relative number of other components relative to C1.
[0106] According to the above set resume curve graph, the gas hydrocarbon component distribution curve in the measured or required different depth layers can be generated in one graph.
[0107]
[0108] In step 4, establish a gas line curve in the graph obtained in step 3, and the gas line curve is the (oil/gas) criticality of the distribution characteristics of the gas and hydrocarbon components of the oil and gas layer in the test well area. Trendline. Specifically, the hydrocarbon component of oil and gas formation gas is mainly composed of C 1 ~C 5 Mainly, namely C 1 , C 2 , C 3 , IC 4 , NC 4 , IC 5 And nC 5 Mainly. Specifically, in a certain layer, C 1 The content of (for example: methane) generally occupies more than 80%, the content of recombination is small, the distribution curve is steep, and the distribution of recombination is gradually reduced. Generally speaking, C 1 ~C 5 The content size distribution is: C 1 C 2 C 3 iC 4 ≥nC 4 iC 5 nC 5. The hydrocarbon in the present invention is preferably an alkane.
[0109] Specifically, in this embodiment, in step 4, the gas line curve may be a gas line curve established based on existing gas survey data in the area. The existing gas measurement data may be, for example, accurate gas measurement data obtained from gas measurement data of proven oil and gas layers in each layer of test wells in test wells in other test wells (other test locations) in the operating area; or Accurate gas measurement data obtained from actual measurement. Based on the existing gas survey data, the critical trend line of the gas hydrocarbon component distribution characteristics of the oil and gas reservoir, namely the gas line curve, is further studied.
[0110]
[0111] The method for identifying light oil layers and condensate gas layers in a formation provided by the present invention is based on the comparison between the relative content distribution data curve and gas line curve of the gas components of each layer, and the light oil layer or condensate gas layer in the formation Identify the gas evolution zone.
[0112] In this field, the humidity ratio (Wh), balance ratio (Bh) and characteristic ratio (Ch) are calculated through a large number of statistics of gas components of condensate gas layers and light oil layers, and light oil layers with different gas-oil ratios in test wells, There are differences in the well flow composition of condensate gas layers, but for example, humidity ratio (Wh) and equilibrium ratio (Bh) may sometimes be difficult to identify oil and gas layers, while characteristic ratio (Ch) can sometimes well identify oil and gas layers Wait. The method of the present invention can effectively identify light oil layers and condensate gas layers in the formation.

Example

[0113]
[0114] In the second embodiment of the present invention, a basis is provided The application of the method in the interpretation and identification of oil and gas distribution of oil and gas reservoirs in the Xihu Sag. Compared with the traditional method, the coincidence rate of the gas logging interpretation oil and gas layer in the geological structure of the Xihu Sag using the method of the present invention is 96.8%, which is about 10% higher than the traditional gas logging method for oil and gas layer interpretation.

Example

[0115]
[0116] In the third embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program or instruction is stored, and when the program or instruction is executed by a processor, the following steps are implemented:
[0117] Step 1. Collection of measured values ​​of gas composition, which are obtained based on the following method:
[0118] Obtain the test well, and measure the gas composition of the different depth layers in the test well. The gas composition includes C in each layer. 1 , C 2 , C 3 , IC 4 And nC 4 , And optional iC 5 And nC 5 Percentage content, where C 1 Represents a hydrocarbon with carbon atom 1, C 2 Represents a hydrocarbon with 2 carbon atoms, C 3 Represents a hydrocarbon with 3 carbon atoms, iC 4 Represents a hydrocarbon with a heterogeneous structure with 4 carbon atoms, nC 4 Represents a hydrocarbon with a positive structure with 4 carbon atoms, iC 5 Represents a hydrocarbon with a heterogeneous structure of 5 carbon atoms, nC 5 Represents a hydrocarbon with a positive structure with 5 carbon atoms;
[0119] Step 2: Perform normalization processing on the measured value of the gas composition, and calculate the relative content of each gas component, wherein the normalization processing method is to perform the following calculation:
[0120]
[0121]
[0122] …
[0123]
[0124] The condition is when iC 5 And/or nC 5 When it exists, i=5 in the above normalization processing, and the normalization processing also includes:
[0125]
[0126]
[0127] Step 3: Make a graph based on the relative content distribution data of each component of each layer after the normalization process in Step 2, and the graph uses the relative content as the ordinate and different gas components as the abscissa;
[0128] Step 4. In the graph obtained in step 3, establish a gas line curve, the gas line curve being a critical trend line of the distribution characteristics of the hydrocarbon component of the oil and gas layer in the test well area;
[0129] Step 5: Identify the light oil layer or condensate gas layer in the formation based on the comparison between the relative content distribution data curve of each component of each layer and the gas line curve.
[0130] For machine-readable media, any combination of one or more computer-usable or computer-readable media can be used. The computer-usable or computer-readable medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, device, or propagation medium. More specific examples (non-exhaustive list) of this computer-readable medium include the following:
[0131] Portable computer disk,
[0132] hard disk,
[0133] Random Access Memory (RAM),
[0134] Read only memory (ROM),
[0135] Erasable programmable read-only memory (EPROM or flash memory),
[0136] Portable compact disc read-only memory (CDROM),
[0137] Optical storage devices,
[0138] Such as those that provide Internet or intranet transmission media,
[0139] Magnetic storage devices,
[0140] USB key, and/or
[0141] Certificate etc.
[0142] In this embodiment, the computer-usable or computer-readable medium can be any medium that can contain, store, communicate, propagate, or transmit a program that is used by or connected to the instruction execution system, device, or device . The computer usable medium may include a propagated data signal with computer usable program code subsequently embodied in baseband or as part of a carrier wave. The computer usable program code can be transmitted using any suitable medium, including but not limited to wireless, wired line, fiber optic cable, RF and so on.
[0143] The computer program code used to implement the operation of the present invention can be written in any combination of one or more programming languages, including object-oriented programming languages, such as Java, Smalltalk, C++, etc., as well as traditional programming languages, such as "C" Programming language or similar programming language. The program code can be executed entirely on the user's computer, partly on the user's computer, as an independent software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network. This can include, for example, a local area network (LAN) or a wide area network (WAN), or a connection that can connect to an external computer (e.g., by using the Internet of an Internet service provider). In addition, in some embodiments, the present invention may be embodied in a field programmable gate array (FPGA).
[0144] For the required computing device, it may include any general computing device or unit (e.g., personal computer, server, etc.) capable of executing the computer program code installed thereon. However, it should be understood that computing devices are merely representative of various possible equivalent computing devices that can perform the processes described herein. To this extent, in some embodiments, the functions provided by the computing device can be implemented by computing components that include any combination of general and/or special purpose hardware and/or computer program code. In some embodiments, standard programming and engineering techniques can be used to generate the program code and hardware, respectively.
[0145] More specifically, the interpretation method of the present invention can be expressed in the form of a computer program product, which can be used by a computer or any instruction execution system or connected to a computer or any instruction execution system that provides program code. Available or computer-readable media to access. The software and/or computer program product can be implemented in a suitable environment. For the purpose of this description, the computer-usable or computer-readable medium can be any medium that can contain, store, communicate, propagate, or transmit the program that is used by or connected to the instruction execution system, apparatus, or device . The medium can be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system (or device or device) or propagation medium. Examples of computer-readable storage media include semiconductor or solid-state memory, magnetic tape, removable computer disk, random access memory (RAM), read-only memory (ROM), flash disk, and optical disk. Examples of existing optical disks include compact disk-read only memory (CD-ROM), high-density disk-read/write (CD-R/W) and DVD.
[0146] Performing the execution of the above method of the present invention through the above machine-readable medium, executable program, computing device or computer program product can more intuitively and quickly present the result of interpretation or recognition.
[0147] The method for identifying the light oil layer and the gas condensate layer in the formation of the present invention can effectively identify the light oil layer and the gas condensate layer in the formation, thereby improving the interpretation coincidence rate of the oil and gas layer, and providing a new solution for gas logging and logging Program.

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