CN102953726B

CN102953726B - Method and device for water drive oilfield advantage channel recognition

Info

Publication number: CN102953726B
Application number: CN201110240837.XA
Authority: CN
Inventors: 冯其红; 王森; 张先敏
Original assignee: China University of Petroleum East China
Current assignee: China University of Petroleum East China
Priority date: 2011-08-22
Filing date: 2011-08-22
Publication date: 2014-05-14
Anticipated expiration: 2031-08-22
Also published as: CN102953726A

Abstract

A method and device for identifying a dominant channel in a water drive oilfield, using unstable pressure recovery well test data to identify the dominant channel formed during the development of a water drive oil field, the method includes the step of setting a typical characteristic curve of the well test; The bottom pressure measurement step; the well test bottom hole pressure derivative calculation step; the step of drawing the relationship curve of the actual test well and the step of judging the existence and development level of the dominant channel; the device includes: a typical characteristic curve chart module, a bottom hole pressure measurement module, Bottomhole pressure derivative calculation module, well test relationship curve drawing module and judgment module. Compared with the prior art, the present invention has high accuracy, strong versatility, simple operation and strong operability, and can provide technical support for the implementation of the next step production increase measures in the oil field and the design of the recovery improvement scheme.

Description

A method and device for identifying dominant channels in water flooding oilfields

技术领域 technical field

本发明涉及水驱油田优势通道的识别技术，特别是一种利用不稳定试井方法对水驱油田开发过程中所形成的优势通道进行识别的水驱油田优势通道识别方法及装置。 The invention relates to a technology for identifying dominant channels in water flooding oilfields, in particular to a method and device for identifying dominant channels in water flooding oilfields by using an unstable well test method to identify dominant channels formed in the development process of water flooding oilfields. the

背景技术 Background technique

在油田的长期注水开发过程中，储层孔隙结构会发生很大变化。油层非均质性等地质因素、开采速度过快等开发因素以及油层压力的变化等都会使储层孔喉半径增大，渗透率增大，从而在储层中形成次生高渗透条带，即优势通道。在油田开发过程中，优势通道最敏感的开发参数是压力和产量，而且试井所录取的资料是各种资料中唯一在油气藏流体流动状态下录取的资料，因此分析结果也最能代表油气藏的动态特性。由于优势通道是在油田开发过程中逐渐形成的，因此优势通道的发育级别不是一成不变的，而是一个由弱到强的动态变化过程。优势通道内流体的流动状态也是逐渐变化的，从达西渗流逐渐演化为非达西渗流。优势通道的出现将造成大量注入水的低效、无效循环，它一方面加剧了油层的非均质性，减小了注入水的波及系数，降低了注入水利用率；另一方面加剧了层内、层间矛盾，严重干扰其它油层的吸水出油状况，导致油井含水上升快，水驱动用程度低；同时，它还会造成其它增产措施实施起来比较困难，加大集输管线和联合站的工作量，使油田开发成本增加，降低了油田的经济采收率，影响油田开发效益的提高。 During the long-term water injection development of oilfields, the reservoir pore structure will change greatly. Geological factors such as oil layer heterogeneity, development factors such as excessively fast production speed, and changes in oil layer pressure will increase the pore throat radius and permeability of the reservoir, thus forming secondary high-permeability strips in the reservoir. That is, the dominant channel. In the process of oilfield development, the most sensitive development parameters of the dominant channel are pressure and production, and the data collected from the well test is the only data collected under the fluid flow state of the oil and gas reservoir, so the analysis results are also the most representative of oil and gas. hidden dynamic characteristics. Since the dominant channel is gradually formed in the process of oilfield development, the development level of the dominant channel is not static, but a dynamic change process from weak to strong. The flow state of the fluid in the dominant channel also changes gradually, from Darcy flow to non-Darcy flow. The emergence of dominant channels will cause inefficient and ineffective circulation of a large amount of injected water. On the one hand, it aggravates the heterogeneity of the oil layer, reduces the sweep coefficient of injected water, and reduces the utilization rate of injected water; Internal and interlayer contradictions seriously interfere with the water absorption and oil production of other oil layers, resulting in rapid rise of water cut in oil wells and low degree of water drive; at the same time, it will also make it difficult to implement other production increase measures, increasing the number of gathering pipelines and joint stations. The workload increases the cost of oil field development, reduces the economic recovery rate of the oil field, and affects the improvement of oil field development benefits. the

因此，如何有效识别优势通道并选取合适的工艺措施对其进行治理，以此来增大注入水波及系数，改善油田水驱开发效果，已经成为中高含水期油藏开发中急需解决的重要问题。而解决该问题的关键以及首要工作就是准确有效地对优势通道进行识别。目前常用的优势通道识别方法主要有：井间示踪剂测试方法、测井方法、水力探测方法和油藏工程方法。示踪剂方法主要通过检测注入示踪剂井周围响应井的示踪剂产出浓度随时间的变化，利用解析法或数值模拟方法，拟合出浓度变化曲线，通过调整地层参数，利用参数变化来模拟地下优势通道的特征；测井方法主要根据测井资料的异常响应特征确定各个小层的吸水变化情况，进而大体确定因优势通道存在而吸水异常的层位；水力探测方法主要利用压力波由注水井传到采油井所需的时间以及井间压差的变化解释出油层渗透率的变化，进而定量解释出优势通道的参数；油藏工程方法主要将优势通道中水的流动视为一维管流，建立大孔道形成后的数学模型，进而采用流管法计算优势通道的参数。然而现有的优势通道识别方法理论基础不完善，在建立数学模型时往往只基于达西渗流或管流的假设，没有考虑到不同级别优势通道所对应的不同渗流状态及其对优势通道识别的影响，不能准确反映优势通道的特征；此外，示踪剂测试和水力探测方法费用昂贵，而且参数解释过程的定性成分较多、受人为主观影响较强、可操作性弱、不利于现场实施；测井方法能够定性判别优势通道存在的层位，但无法判断优势通道发育的级别，认识程度较低，而且测试过程中会影响油田的正常生产，成本较高；油藏工程方法以管流为基础模型，计算简单易行，但假设过于理想化，不符合优势通道的实际情况。 Therefore, how to effectively identify the dominant channel and select appropriate technological measures to control it, so as to increase the sweep coefficient of injected water and improve the water flooding development effect of the oilfield, has become an important problem that needs to be solved urgently in the development of medium-high water-cut reservoirs. The key and primary task to solve this problem is to identify the dominant channel accurately and effectively. At present, the commonly used dominant channel identification methods mainly include: cross-well tracer testing method, logging method, hydraulic detection method and reservoir engineering method. The tracer method mainly detects the change of the tracer output concentration over time in the response wells around the injected tracer well, and uses the analytical method or numerical simulation method to fit the concentration change curve. By adjusting the formation parameters, the parameter Changes to simulate the characteristics of underground dominant channels; the logging method mainly determines the water absorption changes of each small layer according to the abnormal response characteristics of the logging data, and then roughly determines the layer where the water absorption is abnormal due to the existence of the dominant channel; the hydraulic detection method mainly uses the pressure The time required for the wave to travel from the water injection well to the oil production well and the change of interwell pressure difference explain the change of reservoir permeability, and then quantitatively explain the parameters of the dominant channel; the reservoir engineering method mainly regards the flow of water in the dominant channel as For one-dimensional pipe flow, establish a mathematical model after the formation of large pores, and then use the flow pipe method to calculate the parameters of the dominant channel. However, the theoretical basis of existing dominant channel identification methods is not perfect. When establishing mathematical models, they are often only based on the assumption of Darcy seepage or pipe flow, and do not take into account the different seepage states corresponding to different levels of dominant channels and their impact on the identification of dominant channels. In addition, tracer testing and hydraulic detection methods are expensive, and the parameter interpretation process has more qualitative components, is strongly influenced by human subjectivity, and has weak operability, which is not conducive to on-site implementation; The well logging method can qualitatively identify the layer where the dominant channel exists, but it cannot judge the development level of the dominant channel. The basic model is simple and easy to calculate, but the assumption is too ideal and does not meet the actual situation of the dominant channel. the

因此，研究不同级别优势通道的识别方法，对于中高含水期油藏的开发具有重要的理论和现实意义。 Therefore, it is of great theoretical and practical significance to study the identification methods of different levels of dominant channels for the development of medium-high water-cut reservoirs. the

发明内容 Contents of the invention

本发明所要解决的技术问题是提供一种准确性高、通用性强且简单易行的对水驱油田开发过程中所形成的优势通道进行识别的方法及装置。 The technical problem to be solved by the present invention is to provide a method and device for identifying the dominant channels formed in the development process of water flooding oil fields, which are highly accurate, highly versatile, and easy to implement. the

为了实现上述目的，本发明提供了一种水驱油田优势通道识别方法，其中，应用不稳定压力恢复试井资料对水驱油田开发过程中所形成的优势通道进行识别，包括如下步骤： In order to achieve the above object, the present invention provides a method for identifying a dominant channel in a water drive oilfield, wherein the identification of the dominant channel formed in the development process of the water drive oil field is carried out using the unstable pressure recovery well test data, including the following steps:

a、设置试井典型特征曲线图版步骤：设置优势通道识别的试井典型特征曲线图版； a. Steps for setting the typical well test characteristic curve chart: set the well test typical characteristic curve chart for dominant channel identification;

b、试井井底压力测量步骤：将压力计下入试井测试目的层中部，地面关井，利用压力计记录试井井底压力随测试时间恢复的资料井底压力； b. The bottom hole pressure measurement step of the well test: run the pressure gauge into the middle of the target layer for the well test test, close the well on the ground, and use the pressure gauge to record the bottom hole pressure of the test well bottom hole pressure recovered with the test time;

c、试井井底压力导数计算步骤：计算所述试井的井底压力对时间自然对数的一阶导数作为井底压力导数； c. Calculation step of well test bottomhole pressure derivative: calculate the first order derivative of the bottomhole pressure of the well test to the natural logarithm of time as the bottomhole pressure derivative;

d、绘制实测试井关系曲线步骤：以测试时间为横坐标，以井底流压和压力导数为纵坐标，在双对数坐标系中绘制所述井底压力或所述井底压力导数随时间变化的实测试井关系曲线； d. Steps of drawing the relationship curve of the actual test well: take the test time as the abscissa, and take the bottomhole flow pressure and the pressure derivative as the ordinate, and draw the bottomhole pressure or the bottomhole pressure derivative over time in a double-logarithmic coordinate system Variation of actual test well relationship curve;

e、判断优势通道的存在及其发育级别步骤：将所述实测试井关系曲线与优势通道识别的所述试井典型特征曲线进行形态比较，判断优势通道是否存在并确定其发育级别。 e. The step of judging the existence and development level of the dominant channel: compare the shape of the actual test well relationship curve with the typical characteristic curve of the well test identified by the dominant channel, determine whether the dominant channel exists and determine its development level. the

上述的水驱油田优势通道识别方法，其中，在所述绘制实测试井关系曲线步骤前，还包括： The above-mentioned water drive oilfield dominant channel identification method, wherein, before the step of drawing the actual test well relationship curve, also includes:

d0、数据平滑处理步骤：将所述井底压力或所述井底压力导数与时间的关系进行数据平滑处理以降低噪声。 d0. Data smoothing processing step: performing data smoothing processing on the bottom hole pressure or the relationship between the bottom hole pressure derivative and time to reduce noise. the

上述的水驱油田优势通道识别方法，其中，所述数据平滑处理步骤采用小波变换法、线性插值平滑法或傅立叶变换法对所述井底压力或所述井底压力导数进行数据平滑处理。 In the method for identifying dominant channels in water flooding oilfields above, the data smoothing step uses wavelet transform, linear interpolation smoothing or Fourier transform to perform data smoothing on the bottom hole pressure or the bottom hole pressure derivative. the

上述的水驱油田优势通道识别方法，其中，所述设置试井典型特征曲线图版步骤包括设置正常储层试井特征曲线图版和设置优势通道试井典型特征曲线图版。 In the above-mentioned method for identifying dominant channels in a water drive oilfield, the step of setting a typical well test characteristic curve chart includes setting a normal reservoir well test characteristic curve chart and setting a dominant channel well test typical characteristic curve chart. the

上述的水驱油田优势通道识别方法，其中，所述正常储层试井特征曲线图版为均质无限大地层中心一口井的不稳定渗流模型曲线图版。 In the above-mentioned method for identifying dominant channels in water flooding oilfields, the chart of the well test characteristic curve of the normal reservoir is the chart of the unstable seepage model curve of a well in the center of a homogeneous infinite formation. the

上述的水驱油田优势通道识别方法，其中，所述设置优势通道试井典型特征曲线图版包括： In the above-mentioned method for identifying dominant channels in water drive oilfields, wherein the typical characteristic curve charts for setting the dominant channels for well testing include:

a1、给定模型假设条件：按照优势通道的成因及发育级别给定模型的假设条件； a1. Given the assumptions of the model: the assumptions of the model are given according to the cause of the dominant channel and the developmental level;

a2、建立数学模型：按照所述优势通道的成因及发育级别的假设条件分别建立相应的数学模型； a2. Establish a mathematical model: establish a corresponding mathematical model according to the assumptions of the cause of the dominant channel and the developmental level;

a3、模型求解及典型特征曲线绘制：分别对所述数学模型求解并根据求解结果绘制相应的优势通道试井典型特征曲线图版。 a3. Model solution and typical characteristic curve drawing: Solve the mathematical models respectively and draw the corresponding typical characteristic curve charts of dominant channel well tests according to the solution results. the

上述的水驱油田优势通道识别方法，其中，所述优势通道试井典型特征曲线图版按照优势通道的成因及发育级别由弱到强，包括普通高渗透层特征曲线图版、强高渗条带特征曲线图版和大孔道特征曲线图版。 The above method for identifying dominant channels in water flooding oilfields, wherein the typical characteristic curve charts of the dominant channel well test are from weak to strong according to the origin and development level of the dominant channels, including the characteristic curve charts of ordinary high-permeability layers and the characteristics of strong and high-permeability bands. Curve chart and large channel characteristic curve chart. the

为了更好地实现上述目的，本发明还提供了一种水驱油田优势通道识别装置，其中，应用不稳定压力恢复试井资料对水驱油田开发过程中所形成的优势通道进行识别，包括： In order to better achieve the above object, the present invention also provides a water drive oil field dominant channel identification device, wherein, the application of unstable pressure recovery well test data identifies the dominant channel formed in the water drive oil field development process, including :

设置典型特征曲线图版模块：用于设置并存储优势通道识别的试井典型特征曲线图版； Set typical characteristic curve chart module: used to set and store the well test typical characteristic curve chart for dominant channel identification;

井底压力测量模块：包括压力计和压力记录单元，所述压力计用于测试试井随测试时间恢复的井底压力，并将测试得到的所述井底压力输送入所述压力记录单元； Bottomhole pressure measurement module: including a pressure gauge and a pressure recording unit, the pressure gauge is used to test the bottomhole pressure of the well test recovery with the test time, and transmit the bottomhole pressure obtained by the test into the pressure recording unit;

井底压力导数计算模块：用于计算所述井底压力对时间自然对数的一阶导数，作为井底压力导数并存储该井底压力导数； Bottomhole pressure derivative calculation module: used to calculate the first-order derivative of the bottomhole pressure versus time natural logarithm, as the bottomhole pressure derivative and store the bottomhole pressure derivative;

绘制试井关系曲线模块：用于在双对数坐标系中绘制所述井底压力或所述井底压力导数随时间变化的实测试井关系曲线； Drawing well test relationship curve module: used to draw the actual test well relationship curve of the bottom hole pressure or the bottom hole pressure derivative changing with time in the double logarithmic coordinate system;

判断模块：用于将所述实测试井关系曲线与优势通道识别的所述试井典型特征曲线进行形态比较，判断优势通道是否存在并确定其发育级别。 Judgment module: used to compare the actual test well relationship curve with the typical characteristic curve of the well test identified by the dominant channel, determine whether the dominant channel exists and determine its development level. the

上述的水驱油田优势通道识别装置，其中，还包括： The above-mentioned water flooding oil field dominant channel identification device also includes:

数据平滑处理模块：用于将所述井底压力或所述井底压力导数与时间的关系进行数据平滑处理后输入所述绘制实测试井关系曲线模块。 Data smoothing processing module: for smoothing the data of the bottom hole pressure or the relationship between the bottom hole pressure derivative and time and inputting it into the module of drawing actual test well relationship curve. the

本发明的技术效果在于：本发明在不稳定试井测试的基础上，通过对不同级别优势通道渗流特点的理论分析，绘制了针对不同级别优势通道的典型特征曲线，建立了一套准确有效地识别水驱油田优势通道的新方法。本发明经现场实施，及以常规技术进行的验证，均取得了较好的效果。该技术与常规技术相比，准确性高、通用性强，简单易行，具有较强的可操作性，可以为油田下一步增产措施的实施和提高采收率方案的设计提供技术支持。 The technical effect of the present invention is that: on the basis of unstable well test, the present invention draws typical characteristic curves for different levels of dominant channels through theoretical analysis of seepage characteristics of different levels of dominant channels, and establishes a set of accurate and effective A new approach to identifying dominant pathways in waterflood fields. The invention has been implemented on the spot and verified by conventional techniques, and has achieved good results. Compared with conventional technologies, this technology has high accuracy, strong versatility, simplicity, and strong operability. It can provide technical support for the implementation of next-stage production stimulation measures and the design of enhanced oil recovery schemes in oil fields. the

以下结合附图和具体实施例对本发明进行详细描述，但不作为对本发明的限定。 The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments, but not as a limitation of the present invention. the

附图说明 Description of drawings

图1为本发明的水驱油田优势通道识别方法流程图； Fig. 1 is a flow chart of the water flooding oil field dominant channel identification method of the present invention;

图2为储层为正常储层(储层中不存在优势通道)时的试井典型特征曲线； Fig. 2 is a typical well test characteristic curve when the reservoir is a normal reservoir (there is no dominant channel in the reservoir);

图3为储层中存在普通高渗透层时的试井典型特征曲线； Fig. 3 is a typical well test characteristic curve when there is an ordinary high-permeability layer in the reservoir;

图4为储层中存在强高渗条带时的试井典型特征曲线； Fig. 4 is a typical well test characteristic curve when there are strong and high permeability bands in the reservoir;

图5A为大孔道的试井解释模型示意图； Figure 5A is a schematic diagram of a well test interpretation model for large channels;

图5B为储层中存在大孔道时的试井典型特征曲线； Fig. 5B is a typical well test characteristic curve when there are large pores in the reservoir;

图6为本发明的水驱油田优势通道识别装置框图； Fig. 6 is a block diagram of the water flooding oil field dominant channel identification device of the present invention;

图7为本发明一实施例的不稳定试井测试结果； Fig. 7 is the unstable well test test result of an embodiment of the present invention;

图8为本发明一实施例的第二次不稳定试井测试结果； Fig. 8 is the second unstable well test test result of an embodiment of the present invention;

图9为本发明一实施例的不稳定试井测试结果。 Fig. 9 is an unstable well test test result of an embodiment of the present invention. the

其中，附图标记 Among them, reference signs

1 设置典型特征曲线图版模块 1 Set the typical characteristic curve chart module

2 井底压力测量模块 2 Bottomhole pressure measurement module

3 井底压力导数计算模块 3 Bottomhole pressure derivative calculation module

4 数据平滑处理模块 4 Data smoothing processing module

5 绘制试井关系曲线模块 5 Draw well test relationship curve module

6 判断模块 6 judgment module

M 压力导数随时间的变化曲线 M Variation curve of pressure derivative with time

N 压力随时间的变化曲线 N Variation curve of pressure with time

a～e、b0、a1～a3 步骤 a~e, b0, a1~a3 steps

具体实施方式 Detailed ways

下面结合附图对本发明的结构原理和工作原理作具体的描述： Below in conjunction with accompanying drawing, structural principle of the present invention and principle of work are specifically described:

本发明公开了一种基于不稳定试井的水驱油田优势通道识别方法及装置。主要通过对油井进行压力恢复测试，利用实测的井底压力及其导数随时间变化的曲线，对水驱油田开发过程中所形成的优势通道进行识别。对优势通道进行识别主要涉及到两大方面的问题：(1)确定储层中是否存在优势通道；(2)诊断优势通道发育的程度。 The invention discloses a method and a device for identifying a dominant channel in a water drive oilfield based on an unstable well test. Mainly through the pressure recovery test of the oil well, using the measured bottom hole pressure and its derivative curve with time, the dominant channel formed during the development of the water flooding oil field is identified. The identification of dominant channels mainly involves two issues: (1) determining whether there are dominant channels in the reservoir; (2) diagnosing the development degree of dominant channels. the

本发明为了解决优势通道识别过程中的上述两大问题，克服常规优势通道识别方法不准确、不完善、受主观因素影响大的缺点，以不稳定试井测试为基础，建立了一种针对不同级别优势通道的识别技术，以此为油田下一步增产措施的实施和提高采收率方案的设计提供技术支持。 In order to solve the above-mentioned two major problems in the dominant channel identification process, the present invention overcomes the shortcomings of conventional dominant channel identification methods that are inaccurate, imperfect, and greatly influenced by subjective factors. The identification technology of grade superior channels provides technical support for the implementation of the next step of oil field stimulation measures and the design of enhanced oil recovery scheme. the

参见图1，图1为本发明的水驱油田优势通道识别方法流程图。本发明提供了一种基于不稳定试井的水驱优势通道识别方法。其主要是应用不稳定压力恢复试井资料对水驱油田开发过程中所形成的优势通道进行识别，通过对油井进行压力恢复测试，利用所得到的压力和压力导数曲线对水驱油田开发过程中所形成的优势通道进行识别。包括如下步骤： Referring to FIG. 1 , FIG. 1 is a flow chart of the method for identifying dominant channels in water flooding oilfields according to the present invention. The invention provides a water drive dominant channel identification method based on unstable well test. It is mainly to use the unstable pressure recovery well test data to identify the dominant channel formed in the process of water drive oilfield development, through the pressure recovery test of the oil well, and use the obtained pressure and pressure derivative curve to analyze the water drive oilfield development process. The resulting dominant channel is identified. Including the following steps:

设置试井典型特征曲线图版步骤a：设置优势通道识别的试井典型特征曲线图版； Set the well test typical characteristic curve chart step a: set the well test typical characteristic curve chart for dominant channel identification;

试井井底压力测量步骤b：将压力计(本实施例优选为高精度电子压力计)下入试井测试目的层中部，地面关井，利用压力计记录试井随测试时间恢复的井底压力； Well testing bottomhole pressure measurement step b: run a pressure gauge (preferably a high-precision electronic pressure gauge in this embodiment) into the middle of the well testing target layer, shut down the well on the ground, and use the pressure gauge to record the bottomhole of the well testing recovery with the testing time pressure;

试井井底压力导数计算步骤c：计算所述试井的井底压力对时间自然对数的一阶导数作为井底压力导数； Calculation step c of the bottomhole pressure derivative of the well test: calculating the first order derivative of the bottomhole pressure of the well test to the natural logarithm of time as the bottomhole pressure derivative;

绘制实测试井关系曲线步骤d：以测试时间为横坐标，以井底流压和压力导数为纵坐标，在双对数坐标系中绘制所述井底压力或所述井底压力导数随时间变化的实测试井关系曲线；所述实测试井关系曲线为无因次井底压力与无因次时间的双对数关系曲线或无因次井底压力导数与无因次时间的双对数关系曲线。 Step d of drawing the relationship curve of the actual test well: take the test time as the abscissa, and take the bottomhole flow pressure and the pressure derivative as the ordinate, and plot the bottomhole pressure or the bottomhole pressure derivative as a function of time in the log-logarithmic coordinate system The actual test well relationship curve; the actual test well relationship curve is a double logarithmic relationship curve between dimensionless bottomhole pressure and dimensionless time or a double logarithmic relationship between dimensionless bottomhole pressure derivative and dimensionless time curve. the

判断优势通道的存在及其发育级别步骤e：将所述实测试井关系曲线与优势通道识别的所述试井典型特征曲线进行形态比较，判断优势通道是否存在并确定其发育级别。 Judging the existence of the dominant channel and its developmental level step e: comparing the actual test well relationship curve with the typical characteristic curve of the well test identified by the dominant channel to determine whether the dominant channel exists and determine its development level. the

在所述绘制实测试井关系曲线步骤d前，还包括： Before the step d of drawing the actual test well relationship curve, it also includes:

数据平滑处理步骤d0：将所述井底压力或所述井底压力导数与时间的关系进行数据平滑处理以降低噪声。其中，所述数据平滑处理步骤可采用小波变换法、线性插值平滑法或傅立叶变换法对所述井底压力或所述井底压力导数进行数据平滑处理。由于不稳定试井过程中存在着许多不确定因素，这些不确定因素会使高精度压力计记录的井底压力信号中混入干扰信号(噪声)。如果不采用合适的算法进行降噪，则会造成井底压力和压力导数曲线出现较大的波动，造成曲线特征不明显，可能会影响该发明的实际应用效果。因此本实施例优选采用数学中的小波变换方法对实测的井底压力数据进行光滑处理，以达到降噪的目的。 Data smoothing processing step d0: performing data smoothing processing on the relationship between the bottom hole pressure or the bottom hole pressure derivative and time to reduce noise. Wherein, the data smoothing processing step may use wavelet transform method, linear interpolation smoothing method or Fourier transform method to perform data smoothing processing on the bottom hole pressure or the bottom hole pressure derivative. Due to the existence of many uncertain factors in the unstable well testing process, these uncertain factors will cause interference signals (noise) to be mixed into the bottom hole pressure signal recorded by the high precision pressure gauge. If a suitable algorithm is not used for noise reduction, the bottom hole pressure and pressure derivative curves will fluctuate greatly, resulting in inconspicuous curve features, which may affect the actual application effect of the invention. Therefore, in this embodiment, the wavelet transform method in mathematics is preferably used to smooth the measured bottomhole pressure data, so as to achieve the purpose of noise reduction. the

所述设置试井典型特征曲线图版步骤包括设置正常储层试井特征曲线图版和设置优势通道试井典型特征曲线图版。其中，储层为正常储层(储层中不存在优势通道)时，将其视为均质油藏。该类储层的试井解释模型即为传统的均质无限大地层中心一口井的不稳定渗流模型，可采用laplace变换进行解析求解或者有限差分法进行数值求解。该类储层的典型试井曲线为现有技术中的常用曲线，模型的具体求解过程和典型曲线均为较成熟的现有技术，在此不作赘述。本实施例中，所述正常储层试井特征曲线图版为均质无限大地层中心一口井的不稳定渗流模型曲线图版。参见图2，图2为储层为正常储层(储层中不存在优势通道)时的试井典型特征曲线。其中，附图中M为压力导数随时间的变化曲线，N为压力随时间的变化曲线，以下各图中M、N含义相同。压力和压力导数在试井学科中具有固定的含义。 The step of setting a typical well test characteristic curve chart includes setting a normal reservoir well test characteristic curve chart and setting a dominant channel well test typical characteristic curve chart. Among them, when the reservoir is a normal reservoir (there is no dominant channel in the reservoir), it is regarded as a homogeneous reservoir. The well test interpretation model of this type of reservoir is the traditional unstable seepage model of a well in the center of a homogeneous infinite formation, which can be solved analytically by laplace transform or numerically by finite difference method. The typical well test curves of this type of reservoirs are commonly used curves in the prior art, and the specific solution process and typical curves of the model are relatively mature prior art, and will not be repeated here. In this embodiment, the graph plate of the well test characteristic curve of the normal reservoir is the graph plate of the unstable seepage model curve of a well in the center of the homogeneous infinite formation. Referring to Fig. 2, Fig. 2 is a typical well test characteristic curve when the reservoir is a normal reservoir (there is no dominant channel in the reservoir). Among them, M in the accompanying drawings is the change curve of pressure derivative with time, and N is the change curve of pressure with time. The meanings of M and N in the following figures are the same. Pressure and pressure derivatives have fixed meanings in the discipline of well testing. the

本实施例中，根据优势通道的成因及发育级别，将优势通道由弱到强划分为三类：普通高渗透层，强高渗条带和大孔道，分别根据其渗流特点抽象出典型的物理模型，以此来建立相应的试井解释数学模型，并对其进行求解，绘制不同级别优势通道识别的典型特征曲线。 In this example, according to the cause of formation and development level of the dominant channels, the dominant channels are divided into three categories from weak to strong: ordinary high-permeability layers, strong and high-permeability strips, and large channels. Typical physical channels are abstracted according to their seepage characteristics. Model, in order to establish the corresponding well test interpretation mathematical model, and solve it, draw the typical characteristic curves of different levels of dominant channel identification. the

其中，所述设置优势通道试井典型特征曲线图版具体包括： Among them, the typical characteristic curve charts of the well test of the advantage channel set specifically include:

建立模型设置条件步骤a1：按照优势通道的成因及发育级别建立模型设置的假设条件； Step a1 of establishing model setting conditions: establishing assumptions for model setting according to the cause of formation and developmental level of the dominant channel;

建立数学模型步骤a2：按照所述优势通道的成因及发育级别的假设条件分别建立对应的数学模型； Step a2 of establishing a mathematical model: establishing corresponding mathematical models according to the assumptions of the cause of the dominant channel and the developmental level;

模型求解及典型特征曲线绘制步骤a3：分别对所述数学模型求解并根据求解结果绘制相应的优势通道试井典型特征曲线图版。 Model solution and typical characteristic curve drawing step a3: Solve the mathematical model respectively and draw the corresponding typical characteristic curve chart of dominant channel well test according to the solution results. the

其中，所述优势通道试井典型特征曲线图版按照优势通道的成因及发育级别由弱到强包括普通高渗透层特征曲线图版、强高渗条带特征曲线图版和大孔道特征曲线图版。 Wherein, the typical characteristic curve chart of the dominant channel well test includes the characteristic curve chart of ordinary high-permeability layer, the chart of characteristic curve of strong and high-permeability strip and the chart of characteristic curve of large pore channel from weak to strong according to the cause of formation and development level of the dominant channel. the

下面具体说明普通高渗透层特征曲线图版、强高渗条带特征曲线图版和大孔道特征曲线图版的建立过程。 The establishment process of the characteristic curve charts of ordinary high-permeability layer, characteristic curve charts of strong high-permeability strips and large-pore channel characteristic curve charts will be described in detail below. the

参见图3，图3为储层中存在普通高渗透层时的试井典型特征曲线。储层中存在普通高渗透层时，将其视为多层油藏。 Referring to Fig. 3, Fig. 3 is a typical well test characteristic curve when there is an ordinary high-permeability layer in the reservoir. When ordinary high-permeability layers exist in the reservoir, it is regarded as a multi-layer reservoir. the

a1、模型假设条件如下： a1. Model assumptions are as follows:

①油井以定产量生产； ①Oil wells are produced at a fixed rate;

②地层流体和岩石均微可压缩，且压缩系数为常数； ② Formation fluid and rock are both slightly compressible, and the compressibility coefficient is constant;

③地层流体为单相，且在两个渗流场内的流动均符合达西定律； ③The formation fluid is single-phase, and the flow in the two seepage fields conforms to Darcy's law;

④考虑井筒存储与表皮效应的影响； ④Consider the influence of wellbore storage and skin effect;

⑤油井测试前地层中各点压力相同，均为p_i； ⑤The pressure of each point in the formation before the oil well test is the same, all are p _i ;

⑥忽略重力和毛管力的影响，且地层中压力梯度较小； ⑥ Neglect the influence of gravity and capillary force, and the pressure gradient in the formation is small;

⑦每种介质的孔隙度与另一种介质的压力变化相互独立； ⑦ The porosity of each medium is independent of the pressure change of the other medium;

⑧两层之间相连通，且两者之间发生拟稳态窜流； ⑧ The two layers are connected, and quasi-steady-state channeling occurs between the two layers;

a2、建立数学模型 a2. Establish a mathematical model

无因次量定义 dimensionless quantity definition

模型中下标1代表正常储层，下标2代表普通高渗透层。 In the model, subscript 1 represents a normal reservoir, and subscript 2 represents an ordinary high-permeability layer. the

①无因次压力： ① Dimensionless pressure:

${P P}_{Dj Dj} = = \frac{{k k}_{11} {h h}_{11} + + {k k}_{22} {h h}_{22}}{1.842 1.842 \times \times 1010^{- - 33} qμB qμB} Δ Δ {p p}_{j j}$

式中：Δp_j＝p_i-p_j，j＝1，2 In the formula: Δp _j = p _i -p _j , j = 1, 2

②无因次时间： ② Dimensionless time:

${t t}_{D D.} = = \frac{3.6 3.6 (({k k}_{11} {h h}_{11} + + {k k}_{22} {h h}_{22}))}{[[{((φ φ {C C}_{t t} h h))}_{11} + + {((φ φ {C C}_{t t} h h))}_{22}]] μ μ {r r}_{w w}^{22}} t t$

③无因次井筒存储系数 ③ Dimensionless wellbore storage coefficient

${C C}_{D D. 11} = = \frac{C C}{22 π π {((φ φ {C C}_{t t} h h))}_{11} {r r}_{}^{w w}},,$ ${C C}_{D D. 22} = = \frac{C C}{22 π π {((φ φ {C C}_{t t} h h))}_{22} {r r}_{}^{w w}}$

${C C}_{D D.} = = \frac{C C}{22 π π [[{((φ φ {C C}_{t t} h h))}_{11} + + {((φ φ {C C}_{t t} h h))}_{22}]] {r r}_{}^{w w}}$

④储能比 ④ energy storage ratio

$ω ω = = \frac{{((φ φ {C C}_{t t} h h))}_{11}}{{((φ φ {C C}_{t t} h h))}_{11} + + {((φ φ {C C}_{t t} h h))}_{22}}$

⑤窜流系数 ⑤Channel flow coefficient

$λ λ = = {αr αr}_{w w}^{22} \frac{{k k}_{11} {h h}_{11}}{{k k}_{11} {h h}_{11} + + {k k}_{22} {h h}_{22}}$

⑥地层系数比 ⑥ Formation coefficient ratio

$κ κ = = \frac{{k k}_{11} {h h}_{11}}{{k k}_{11} {h h}_{11} + + {k k}_{22} {h h}_{22}}$

⑦无因次半径 ⑦ dimensionless radius

${r r}_{D D.} = = \frac{r r}{{r r}_{w w}}$

数学模型 mathematical model

$\{\begin{matrix} κ κ \frac{11}{{r r}_{D D.}} \frac{&PartialD; &PartialD;}{&PartialD; &PartialD; {r r}_{D D.}} (({r r}_{D D.} \frac{&PartialD; &PartialD; {P P}_{D D. 11}}{&PartialD; &PartialD; {r r}_{D D.}})) - - λ λ (({P P}_{D D. 11} - - {P P}_{D D. 22})) = = ω ω \frac{&PartialD; &PartialD; {P P}_{D D. 11}}{&PartialD; &PartialD; {t t}_{D D.}} \\ ((11 - - κ κ)) \frac{11}{{r r}_{D D.}} \frac{&PartialD; &PartialD;}{&PartialD; &PartialD; {r r}_{D D.}} (({r r}_{D D.} \frac{&PartialD; &PartialD; {P P}_{D D. 22}}{&PartialD; &PartialD; {r r}_{D D.}})) + + λ λ (({P P}_{D D. 11} - - {P P}_{D D. 22})) = = ((11 - - ω ω)) \frac{&PartialD; &PartialD; {P P}_{D D. 22}}{&PartialD; &PartialD; {t t}_{D D.}} \\ {P P}_{D D. 11} (({r r}_{D D.},, 00)) = = {P P}_{D D. 22} (({r r}_{D D.},, 00)) = = 00 \\ {C C}_{D D.} \frac{{dP dP}_{wD W}}{dt dt} - - κ κ \frac{&PartialD; &PartialD; {P P}_{D D. 11}}{&PartialD; &PartialD; {r r}_{D D.}} {| |}_{{r r}_{D D.} = = 11} - - ((11 - - κ κ)) \frac{&PartialD; &PartialD; {P P}_{D D. 22}}{&PartialD; &PartialD; {r r}_{D D.}} {| |}_{{r r}_{D D.} = = 11} = = 11 \\ {P P}_{wD W} = = {[[{P P}_{D D. 11} - - {S S}_{11} (({r r}_{D D.} \frac{{&PartialD; &PartialD; P P}_{D D. 11}}{&PartialD; &PartialD; {r r}_{D D.}}))]]}_{{r r}_{D D.} = = 11} {[[{P P}_{D D. 22} - - {S S}_{22} (({r r}_{D D.} \frac{&PartialD; &PartialD; {P P}_{D D. 22}}{&PartialD; &PartialD; {r r}_{D D.}}))]]}_{{r r}_{D D.} = = 11} \\ {P P}_{D D. 11} (({r r}_{eD E},, {t t}_{D D.})) = = {P P}_{D D. 22} (({r r}_{eD E},, {t t}_{D D.})) = = 00 \end{matrix}$

a3、模型求解 a3. Model solution

此处采用Douglas-Jones预估校正法可以实现对该模型的差分求解。利用求解的结果即可绘制普通高渗透层的试井典型曲线(参见图3)。 Here, the Douglas-Jones predictive correction method can be used to realize the differential solution of the model. The typical well test curves of ordinary high-permeability layers can be drawn by using the solution results (see Fig. 3). the

参见图4，图4为储层中存在强高渗条带时的试井典型特征曲线。储层中存在强高渗条带时，将其视为水平裂缝。 Referring to Fig. 4, Fig. 4 is a typical well test characteristic curve when there are strong and high permeability bands in the reservoir. When there are strong hyperpermeable bands in the reservoir, they are regarded as horizontal fractures. the

在流体微可压缩、上下边界封闭的无限大油藏条件下，一连续点源位于(x_w，y_w，z_w)处，观测点位于(x，y，z)处，点源产生的压力分布的拉普拉斯空间解为： Under the condition of infinite reservoir with slightly compressible fluid and closed upper and lower boundaries, a continuous point source is located at (x _w , y _w , z _w ), the observation point is located at (x, y, z), and the The Laplace space solution of the pressure distribution is:

$\overset{&OverBar; &OverBar;}{Δp Δp} = = \frac{\overset{~ ~}{q q} u u}{22 πkL πkL {h h}_{D D.} s the s} [[{K K}_{00} (({r r}_{D D.} \sqrt{u u})) + + 22 {Σ Σ}_{n no = = 11}^{\infty \infty} {K K}_{00} (({r r}_{D D.} {ϵ ϵ}_{n no})) cos cos nπ nπ \frac{z z}{h h} cos cos nπ nπ \frac{{z z}_{w w}}{h h}]]$

式中 ——压差分布的拉普拉斯空间解； In the formula — Laplace space solution of differential pressure distribution;

——点源的产量，cm³/s；

——the output of point source, cm ³ /s;

μ——液体粘度，mPa·s； μ——liquid viscosity, mPa s;

k——地层渗透率，μm²； k——formation permeability, μm ² ;

L——参考长度，cm； L——reference length, cm;

s——拉普拉斯空间变量； s——Laplace space variable;

K₀——第二类修正的贝塞尔函数； K ₀ ——the modified Bessel function of the second kind;

h——油藏厚度，cm； h—reservoir thickness, cm;

u——u＝sf(s)，其中f(s)为与油藏性质有关的量。当油藏为均质油藏时，f(s)＝1；当油藏为双重介质油藏时，f(s)为窜流系数、弹性储能比和拉普拉斯空间变量的函数。 u—u=sf(s), where f(s) is a quantity related to reservoir properties. When the reservoir is a homogeneous reservoir, f(s)=1; when the reservoir is a dual-media reservoir, f(s) is a function of channeling coefficient, elastic energy storage ratio and Laplace space variables. the

定义无因次变量如下： Define dimensionless variables as follows:

${x x}_{D D.} = = \frac{x x}{L L};;$ ${y the y}_{D D.} = = \frac{y the y}{L L};;$ ${h h}_{D D.} = = \frac{h h}{L L} \sqrt{\frac{k k}{{k k}_{z z}}};;$

${ϵ ϵ}_{n no} = = \sqrt{u u + + {n no}^{22} {π π}^{22} / / {h h}_{D D.}^{22}};;$

${r r}_{D D.}^{22} = = {(({x x}_{D D.} - - {x x}_{wD W}))}^{22} + + {(({y the y}_{D D.} - - {y the y}_{wD W}))}^{22} . .$

根据叠加原理，将连续点源解在矩形的强高渗条带平面上进行积分，可得均匀流量的强高渗条带的压力响应公式为 According to the principle of superposition, the continuous point source solution is integrated on the plane of the rectangular strong hyperpermeable strip, and the pressure response formula of the uniform flow strong hyperpermeable strip can be obtained as

$\overset{&OverBar; &OverBar;}{Δp Δp} = = {&Integral; &Integral;}_{X x - - {L L}_{f f}}^{X x + + {L L}_{f f}} {&Integral; &Integral;}_{Y Y - - \frac{b b}{22}}^{Y Y + + \frac{b b}{22}} \frac{\overset{~ ~}{q q} μ μ}{22 πkL πkL {h h}_{D D.} s the s} [[{K K}_{00} (({r r}_{D D.} \sqrt{u u})) + + 22 {Σ Σ}_{n no = = 11}^{\infty \infty} {K K}_{00} (({r r}_{D D.} {ϵ ϵ}_{n no})) cos cos nπ nπ \frac{z z}{h h} cos cos nπ nπ \frac{{z z}_{w w}}{h h}]] d d {y the y}_{w w} {dx dx}_{w w}$

式中(X，Y)——优势通道井的井点在平面上的位置； In the formula (X, Y)——the position of the well point of the dominant channel well on the plane;

L_f——优势通道的半长，cm； L _f — half length of dominant channel, cm;

b——优势通道的宽度，cm。 b - the width of the dominant channel, cm. the

定义 $\tilde{L_{f}} = \frac{L_{f}}{L},$ $\tilde{b} = \frac{b}{L},$ 则 definition $\tilde{L_{f}} = \frac{L_{f}}{L},$ $\tilde{b} = \frac{b}{L},$ but

$\overset{&OverBar; &OverBar;}{Δp Δp} = = \frac{\overset{~ ~}{q q} μ μ}{22 πkL πkL {h h}_{D D.} s the s} [[{L L}^{22} {&Integral; &Integral;}_{X x - - \overset{~ ~}{{L L}_{f f}}}^{X x + + \overset{~ ~}{{L L}_{f f}}} {&Integral; &Integral;}_{Y Y - - 0.5 0.5 \overset{~ ~}{b b}}^{Y Y + + 0.5 0.5 \overset{~ ~}{b b}} {K K}_{00} ((\sqrt{{(({x x}_{D D.} - - {x x}_{wD W}))}^{22} + + {(({y the y}_{D D.} - - {y the y}_{wD W}))}^{22}} \cdot \cdot \sqrt{u u})) {dy dy}_{wD W} {dx dx}_{wD W}]]$

$+ + \frac{\overset{~ ~}{q q} μ μ}{22 πkL πkL {h h}_{D D.} s the s} [[22 {L L}^{22} {Σ Σ}_{n no = = 11}^{\infty \infty} cos cos nπ nπ \frac{z z}{h h} cos cos nπ nπ \frac{{z z}_{w w}}{h h} {&Integral; &Integral;}_{X x - - \overset{~ ~}{{L L}_{f f}}}^{X x + + \overset{~ ~}{{L L}_{f f}}} {&Integral; &Integral;}_{Y Y - - 0.5 0.5 \overset{~ ~}{b b}}^{Y Y + + 0.5 0.5 \overset{~ ~}{b b}} {K K}_{00} ((\sqrt{{(({x x}_{D D.} - - {x x}_{wD W}))}^{22} + + {(({y the y}_{D D.} - - {y the y}_{wD W}))}^{22}} \cdot \cdot {ϵ ϵ}_{n no}))]] {dy dy}_{wD W} {dx dx}_{wD W}$

定义α，β为积分变量，分别代表某点源与井点无因次的横纵坐标之差，可得到： Define α and β as integral variables, which respectively represent the difference between a point source and the dimensionless horizontal and vertical coordinates of a well point, and we can get:

x方向上：x_wD-X_D＝α In the x direction: x _wD -X _D = α

y方向上：y_wD-Y_D＝β In the y direction: y _wD -Y _D ＝β

则： but:

x_D-x_wD＝x_D-(X_D+α)＝x_D-X_D-α x _D -x _wD ＝x _D -(X _D +α)＝x _D -X _D -α

y_D-y_wD＝y_D-(Y_D+β)＝y_D-Y_D-β y _D -y _wD =y _D -(Y _D +β)=y _D -Y _D -β

定义 $\tilde{x_{D}} = x_{D} - X_{D} - α,$ $\tilde{y_{D}} = y_{D} - Y_{D} - β,$ 则可以得到 definition $\tilde{x_{D.}} = x_{D.} - x_{D.} - α,$ $\tilde{{the y}_{D.}} = {the y}_{D.} - Y_{D.} - β,$ then you can get

$\overset{&OverBar; &OverBar;}{Δp Δp} = = \frac{\overset{~ ~}{q q} μL μ L}{22 πk πk {h h}_{D D.} s the s} [[{&Integral; &Integral;}_{- - Lf Lf}^{Lf Lf} {&Integral; &Integral;}_{- - 0.5 0.5 b b}^{0.5 0.5 b b} {K K}_{00} ((\sqrt{{\overset{~ ~}{{x x}_{D D.}}}^{22} + + {\overset{~ ~}{{y the y}_{D D.}}}^{22}} \cdot &Center Dot; \sqrt{u u})) dαdβ dαdβ + + 22 {Σ Σ}_{n no = = 11}^{\infty \infty} cos cos nπ nπ \frac{z z}{h h} cos cos nπ nπ \frac{{z z}_{w w}}{h h} \times \times$

${&Integral; &Integral;}_{- - Lf Lf}^{Lf Lf} {&Integral; &Integral;}_{- - 0.5 0.5 b b}^{0.5 0.5 b b} {K K}_{00} ((\sqrt{{\overset{~ ~}{{x x}_{D D.}}}^{22} + + {\overset{~ ~}{{y the y}_{D D.}}}^{22}} \cdot &Center Dot; {ϵ ϵ}_{n no})) dαdβ dαdβ$

取井点的坐标为(0，0，z_w)，参考长度为强高渗条带的半长，利用以下关系式对其进行无因次化： The coordinates of the well point are taken as (0, 0, z _w ), the reference length is the half length of the strong hypertonic band, and the following relationship is used to make it dimensionless:

$q q = = \overset{~ ~}{q q} \cdot &Center Dot; 22 Lfb Lfb$

$\overset{&OverBar; &OverBar;}{{p p}_{D D.}} = = \frac{22 πkh πkh \overset{&OverBar; &OverBar;}{Δp Δp}}{qμ qμ}$

$\overset{&OverBar; &OverBar;}{{p p}_{D D.}} = = \frac{h h}{22 bs bs {h h}_{S S}} [[{&Integral; &Integral;}_{- - \overset{~ ~}{{L L}_{f f}}}^{\overset{~ ~}{{L L}_{f f}}} {&Integral; &Integral;}_{- - 0.5 0.5 \overset{~ ~}{b b}}^{0.5 0.5 \overset{~ ~}{b b}} {K K}_{00} ((\sqrt{{(({x x}_{D D.} - - α α))}^{22} + + {(({y the y}_{D D.} - - β β))}^{22}} \cdot &Center Dot; \sqrt{u u})) dαdβ dαdβ + +$

$22 {Σ Σ}_{n no = = 11}^{\infty \infty} {cos cos}^{22} nπ nπ \frac{{z z}_{w w}}{h h} {&Integral; &Integral;}_{- - {L L}_{f f}}^{{L L}_{f f}} {&Integral; &Integral;}_{- - 0.5 0.5 b b}^{0.5 0.5 b b} {K K}_{00} ((\sqrt{{(({x x}_{D D.} - - α α))}^{22} + + {(({y the y}_{D D.} - - β β))}^{22}} \cdot \cdot {ϵ ϵ}_{n no})) dαdβ dαdβ]]$

定义 $L_{D} = \frac{1}{h_{D}} = \frac{L_{f}}{h},$ $e = \frac{b}{L_{f}},$ 可得 definition $L_{D.} = \frac{1}{h_{D.}} = \frac{L_{f}}{h},$ $e = \frac{b}{L_{f}},$ Available

$\overset{&OverBar; &OverBar;}{{p p}_{D D.}} = = \frac{11}{22 se the se} [[{&Integral; &Integral;}_{- - 11}^{11} {&Integral; &Integral;}_{- - 0.5 0.5 e e}^{0.5 0.5 e e} {K K}_{00} ((\sqrt{{(({x x}_{D D.} - - α α))}^{22} + + {(({y the y}_{D D.} - - β β))}^{22}} \cdot &Center Dot; \sqrt{u u})) dαdβ dαdβ + +$

$22 {Σ Σ}_{n no = = 11}^{\infty \infty} {cos cos}^{22} nπ nπ \frac{{z z}_{w w}}{h h} {&Integral; &Integral;}_{- - 11}^{11} {&Integral; &Integral;}_{- - 0.5 0.5 e e}^{0.5 0.5 e e} {K K}_{00} ((\sqrt{{(({x x}_{D D.} - - α α))}^{22} + + {(({y the y}_{D D.} - - β β))}^{22}} \cdot &Center Dot; {ϵ ϵ}_{n no})) dαdβ dαdβ]]$

则井底压差的拉普拉斯空间解为： Then the Laplace space solution of bottom hole pressure difference is:

$\overset{&OverBar; &OverBar;}{{p p}_{D D.}} = = \frac{11}{22 se the se} [[{&Integral; &Integral;}_{- - 11}^{11} {&Integral; &Integral;}_{- - 0.5 0.5 e e}^{0.5 0.5 e e} {K K}_{00} ((\sqrt{{α α}^{22} + + {β β}^{22}} \cdot &Center Dot; \sqrt{u u})) dαdβ dαdβ + +$

$22 {Σ Σ}_{n no = = 11}^{\infty \infty} {cos cos}^{22} nπ nπ \frac{{z z}_{w w}}{h h} {&Integral; &Integral;}_{- - 11}^{11} {&Integral; &Integral;}_{- - 0.5 0.5 e e}^{0.5 0.5 e e} {K K}_{00} ((\sqrt{{α α}^{22} + + {β β}^{22}} \cdot &Center Dot; {ϵ ϵ}_{n no})) dαdβ dαdβ]]$

式中 $ϵ_{n} -$ $ϵ_{n} = \sqrt{u + n^{2} π^{2} L_{D}^{2}};$ In the formula $ϵ_{no} -$ $ϵ_{no} = \sqrt{u + {no}^{2} π^{2} L_{D.}^{2}};$

u——u＝sf(s)，均质油藏中f(s)＝1，双重介质油藏中f(s)为弹性储容比、窜流系数的函数。 u—u=sf(s), f(s)=1 in homogeneous reservoirs, and f(s) in dual-media reservoirs is a function of elastic storage capacity ratio and channeling coefficient. the

进一步利用拉普拉斯流量褶积关系，考虑井筒存储系数C_D和表皮系数S的影响时，强高渗条带模型的拉普拉斯空间解为： Further using the Laplace flow convolution relationship and considering the influence of the wellbore storage coefficient _CD and skin coefficient S, the Laplace space solution of the strong hyperpermeable strip model is:

$\overset{&OverBar; &OverBar;}{{p p}_{wD W}} = = \frac{s the s \overset{&OverBar; &OverBar;}{{p p}_{D D.}} + + S S}{s the s + + {C C}_{D D.} {s the s}^{22} ((s the s \overset{&OverBar; &OverBar;}{{p p}_{D D.}} + + S S))}$

采用Stehfest数值反演方法可将拉普拉斯空间解反演到真实空间中。然后利用求解结果即可绘制强高渗条带的试井典型曲线(参见图4)。 The Laplacian space solution can be inverted to the real space by using the Stehfest numerical inversion method. Then, the typical well test curve of the strong and hyperpermeable zone can be drawn by using the solution results (see Fig. 4). the

参见图5A及图5B，图5A为大孔道的试井解释模型示意图，图5B为储层中存在大孔道时的试井典型特征曲线。储层中存在大孔道时，其流动为一维非达西渗流。 Referring to Fig. 5A and Fig. 5B, Fig. 5A is a schematic diagram of a well test interpretation model for large pores, and Fig. 5B is a typical well test characteristic curve when there are large pores in the reservoir. When there are large pores in the reservoir, the flow is one-dimensional non-Darcy flow. the

该部分将大孔道中流体的流动视为一维非达西渗流，建立了与油藏渗流的耦合流动模型，并采用解析数值混合方法对该模型进行求解。模型示意图如图5A所示。 In this part, the fluid flow in large pores is regarded as one-dimensional non-Darcy seepage flow, and a coupled flow model with reservoir seepage is established, and the model is solved by analytical numerical hybrid method. A schematic diagram of the model is shown in Figure 5A. the

a1、假设条件 a1. Assumption conditions

①单相、等温、微可压缩流体，综合压缩系数为C，流体粘度为μ； ①Single-phase, isothermal, slightly compressible fluid, the comprehensive compressibility coefficient is C, and the fluid viscosity is μ;

②储层各向异性，水平方向渗透率为k，垂直方向渗透率为k_z； ②The reservoir is anisotropic, the permeability in the horizontal direction is k, and the permeability in the vertical direction is _kz ;

③顶底界面封闭，即z＝0，z＝h处不渗透； ③The top-bottom interface is closed, that is, z=0, z=h is impenetrable;

④外边界为无限大； ④The outer boundary is infinite;

⑤由于大孔道的体积很小，假设大孔道内为一维的非达西渗流； ⑤ Due to the small volume of the large pores, it is assumed that there is one-dimensional non-Darcy flow in the large pores;

⑥x＝0处产量q为定值，x＝L处流量为0，流体只通过大孔道的壁面流入井中； ⑥ The output q at x=0 is a constant value, the flow rate at x=L is 0, and the fluid flows into the well only through the wall of the large pore;

⑦不同时间不同位置处由油藏流入井中的流量不同，单位时间单位长度内由油藏流入大孔道中流体的量为q_h(x，t)，则位置x处大孔道内的流量为： ⑦ The flow rate from the oil reservoir into the well at different positions at different times is different, and the amount of fluid flowing from the oil reservoir into the large pore per unit time and unit length is q _h (x, t), then the flow rate in the large pore at position x is:

${q q}_{d d} ((x x,, t t)) = = {&Integral; &Integral;}_{x x}^{L L} {q q}_{h h} (({x x}^{' '},, t t)) d d {x x}^{' '} . .$

a2、建立数学模型 a2. Establish a mathematical model

无因次化 dimensionless

①无因次压力： ① Dimensionless pressure:

${p p}_{D D.} = = \frac{kh kh (({p p}_{i i} - - p p))}{1.842 1.842 \times \times 1010^{- - 33} qμ qμ}$

②无因次时间： ② Dimensionless time:

${t t}_{D D.} = = \frac{3.6 3.6 kt kt}{φμ φμ {C C}_{t t} \cdot &Center Dot; {((L L / / 22))}^{22}}$

③无因次坐标： ③Dimensionless coordinates:

${x x}_{D D.} = = \frac{x x}{L L / / 22},,$ ${y the y}_{D D.} = = \frac{y the y}{L L / / 22},,$ ${z z}_{wD W} = = \frac{{z z}_{w w}}{h h},,$ ${L L}_{D D.} = = \frac{L L}{22 h h} \sqrt{\frac{{k k}_{v v}}{k k}}$

④大孔道的无因次半径： ④ Dimensionless radius of large pores:

${r r}_{wD W} = = \frac{{r r}_{we we}}{h h} = = \frac{{r r}_{w w}}{22 h h} [[{((\frac{k k}{{k k}_{v v}}))}^{\frac{11}{44}} + + {((\frac{{k k}_{v v}}{k k}))}^{\frac{11}{44}}]]$

式中：r_we为大孔道在各向异性油藏中的等效半径； In the formula: r _we is the equivalent radius of large pores in anisotropic reservoirs;

⑤无因次流量为： ⑤ Dimensionless flow is:

${q q}_{dD D} = = \frac{{q q}_{d d}}{q q};;$ ${q q}_{hD hD} = = \frac{{q q}_{h h} L L}{q q}$

⑥大孔道的无因次导流能力为： ⑥The dimensionless conduction capacity of large pores is:

${C C}_{dD D} = = \frac{{k k}_{f f} {πr π r}_{}^{w w}}{kh kh ((L L / / 22))}$

⑦无因次流量常数为： ⑦The dimensionless flow constant is:

${(({q q}_{DND DND}))}_{d d} = = \frac{1010^{- - 33}}{8640086400} \cdot &Center Dot; \frac{{k k}_{f f} ρβq ρβq}{π π {r r}_{}^{w w} μ μ}$

数学模型 mathematical model

①大孔道内的非达西流动模型 ① Non-Darcy flow model in large channels

${p p}_{wD W} - - {p p}_{dDj DJ} = = \frac{22 π π}{{C C}_{dD D}} {&Integral; &Integral;}_{00}^{{x x}_{Dj Dj}} {q q}_{dD D} {dx dx}_{D D.}^{' '} + + \frac{22 π π}{{C C}_{dD D}} {(({q q}_{DND DND}))}_{d d} {&Integral; &Integral;}_{00}^{{x x}_{Dj Dj}} {q q}_{} {dD D}_{22} {dx dx}_{D D.}^{' '}$

对上式进行差分离散： Differentially discretize the above formula:

${&Integral; &Integral;}_{00}^{{x x}_{Dj Dj}} {q q}_{dD D} {dx dx}_{D D.}^{' '} = = {Σ Σ}_{i i = = 11}^{j j - - 11} ((\frac{Δx Δx}{22} {q q}_{dDi D} + + \frac{Δx Δx}{22} {q q}_{dDi D + + 11})) + + \frac{33}{88} Δx Δx \cdot &Center Dot; {q q}_{dDj DJ} + + \frac{11}{88} Δx Δx \cdot \cdot {q q}_{dDj DJ + + 11}$

${&Integral; &Integral;}_{00}^{{x x}_{Dj Dj}} {q q}_{} {dD D}_{22} {dx dx}_{D D.}^{' '} = = {Σ Σ}_{i i = = 11}^{j j - - 11} ((\frac{Δx Δx}{33} {q q}_{}^{dDi D} + + \frac{Δx Δx}{33} {q q}_{dDi D} {q q}_{dDi D + + 11} + + \frac{Δx Δx}{33} {q q}_{dDi D + + 11}^{22})) + + \frac{77}{24 twenty four} Δx Δ x {q q}_{} {dDj DJ}_{22} + + \frac{11}{66} Δx Δx {q q}_{dDj DJ} {\cdot &Center Dot; q q}_{dDj DJ + + 11} + + \frac{11}{24 twenty four} {Δxq Δxq}_{dDj DJ + + 11}^{22}$

②油藏渗流模型 ②Reservoir seepage model

${p p}_{dD D} (({x x}_{Dj Dj},, {r r}_{wD W},, {t t}_{D D.})) = = \overset{^^}{{p p}_{dD D}} (({x x}_{Dj Dj},, {r r}_{wD W},, {t t}_{DN DN})) + + {Σ Σ}_{i i = = 11}^{M m} \frac{22 (({q q}_{dDi D} - - {q q}_{dDi D + + 11}))}{Δx Δx} {&Integral; &Integral;}_{00}^{{t t}_{DN DN} - - {t t}_{DN DN - - 11}} {S S}_{i i} (({x x}_{Dj Dj},, {t t}_{D D.}^{' '})) d d {t t}_{D D.}^{' '}$

式中： In the formula:

$\overset{^^}{{p p}_{dD D}} (({x x}_{Dj Dj},, {r r}_{wD W},, {t t}_{DN DN})) = = {Σ Σ}_{k k = = 11}^{N N - - 11} {Σ Σ}_{i i = = 11}^{M m} {q q}_{hDi h} (({t t}_{Dk Dk})) [[{&Integral; &Integral;}_{00}^{{t t}_{DN DN} - - {t t}_{Dn Dn - - 11}} {S S}_{i i} (({x x}_{Dj Dj},, {t t}_{D D.}^{' '})) {dt dt}_{D D.}^{' '} - - {&Integral; &Integral;}_{00}^{{t t}_{DN DN} - - {t t}_{Dn Dn}} {S S}_{i i} (({x x}_{Dj Dj},, {t t}_{D D.}^{' '})) d d {t t}_{D D.}^{' '}]]$

${S S}_{i i} (({x x}_{D D.},, τ τ)) = = \frac{\sqrt{π π}}{44} [[erf erf ((\frac{{x x}_{D D.} - - \frac{22 i i - - 22}{M m}}{22 \sqrt{τ τ}})) - - erf erf ((\frac{{x x}_{D D.} - - \frac{22 i i}{M m}}{22 \sqrt{τ τ}}))]]$

${{11 + + 22 {Σ Σ}_{n no = = 11}^{\infty \infty} exp exp [[- - {n no}^{22} {π π}^{22} {L L}_{D D.}^{22} τ τ]] cos cos [[nπ nπ (({z z}_{wD W} + + {r r}_{wD W}))]] cos cos (({nπz nπz}_{wD W}))}}$

a3、模型求解 a3. Model solution

将大孔道内的非达西渗流模型与油藏的达西渗流模型进行耦合，可得： Coupling the non-Darcy flow model in the large pores with the Darcy flow model in the reservoir can be obtained:

${p p}_{wD W} - - \overset{^^}{{p p}_{dD D}} (({x x}_{Dj Dj},, {r r}_{wD W},, {t t}_{DN DN})) - - {Σ Σ}_{i i = = 11}^{M m} \frac{22 (({q q}_{dDi D} - - {q q}_{dDi D + + 11}))}{Δx Δx} {&Integral; &Integral;}_{00}^{{t t}_{DN DN} - - {t t}_{DN DN - - 11}} {S S}_{i i} (({x x}_{Dj Dj},, {t t}_{D D.}^{' '})) {dt dt}_{D D.}^{' '}$

$= = \frac{22 π π}{{C C}_{dD D}} [[{Σ Σ}_{i i = = 11}^{j j - - 11} ((\frac{Δx Δx}{22} {q q}_{dDi D} + + \frac{Δx Δx}{22} {q q}_{dDi D + + 11})) + + \frac{33}{88} Δx Δx \cdot &Center Dot; {q q}_{dDj DJ} + + \frac{11}{88} Δx Δx \cdot \cdot {q q}_{dDj DJ + + 11}]] + +$

$\frac{22 π π}{{C C}_{dD D}} {(({q q}_{DND DND}))}_{d d} [\begin{matrix} {Σ Σ}_{i i = = 11}^{j j - - 11} ((\frac{Δx Δx}{33} {q q}_{}^{dDi D} + + \frac{Δx Δx}{33} {q q}_{dDi D} {q q}_{dDi D + + 11} + + \frac{Δx Δx}{33} {q q}_{dDi D + + 11}^{22})) \\ + + \frac{77}{24 twenty four} Δx Δ x {q q}_{} {dDj DJ}_{22} + + \frac{11}{66} Δx Δx {q q}_{dDj DJ} \cdot \cdot {q q}_{dDj DJ + + 11} + + \frac{11}{24 twenty four} Δx Δx {q q}_{dDj DJ + + 11}^{22} \end{matrix}]$

将大孔道分为M段，则有q_dDi(i＝1，2，…，M+1)。因此上式中一共M+2个未知数：p_wD，q_dDi(i＝1，2，…，M+1)。 Divide the large pores into M segments, then there are q _dDi (i=1, 2,..., M+1). Therefore, there are totally M+2 unknowns in the above formula: p _wD , q _dDi (i=1, 2, . . . , M+1).

利用式上式可列M个方程，再加上两个边界条件： Using the above formula, M equations can be listed, plus two boundary conditions:

q_dD(1)＝q，q_dD(M)＝0 q _dD (1) = q, q _dD (M) = 0

因此上式可进行求解。但是其为非线性方程，因此采用Newton-Raphson迭代方法求解。利用求解结果即可绘制大孔道的试井典型曲线(参见图5B)。 Therefore, the above formula can be solved. But it is a nonlinear equation, so the Newton-Raphson iterative method is used to solve it. The typical well test curve of large channels can be drawn by using the solution results (see Fig. 5B). the

参见图6，图6为本发明的水驱油田优势通道识别装置框图。本发明的水驱油田优势通道识别装置，应用不稳定压力恢复试井资料对水驱油田开发过程中所形成的优势通道进行识别，包括： Referring to Fig. 6, Fig. 6 is a block diagram of a device for identifying dominant channels in a water flooding oilfield according to the present invention. The water flooding oil field dominant channel identification device of the present invention uses the unstable pressure recovery well test data to identify the dominant channel formed in the water flooding oil field development process, including:

设置典型特征曲线图版模块1：用于设置并存储优势通道识别的试井典型特征曲线图版； Set typical characteristic curve plate module 1: used to set and store the well test typical characteristic curve plate for dominant channel identification;

井底压力测量模块2：包括压力计和压力记录单元，所述压力计用于测试试井随测试时间恢复的井底压力并将测试得到的所述井底压力输送入所述压力记录单元； Bottomhole pressure measurement module 2: including a pressure gauge and a pressure recording unit, the pressure gauge is used to test the bottomhole pressure recovered with the test time of the well test and send the bottomhole pressure obtained by the test into the pressure recording unit;

井底压力导数计算模块3：用于计算所述井底压力对时间自然对数的一阶导数作为井底压力导数并存储该井底压力导数； Bottomhole pressure derivative calculation module 3: used to calculate the first-order derivative of the bottomhole pressure versus time natural logarithm as the bottomhole pressure derivative and store the bottomhole pressure derivative;

绘制试井关系曲线模块5：用于在双对数坐标系中绘制所述井底压力或所述井底压力导数随时间变化的实测试井关系曲线； Drawing well test relationship curve module 5: used to draw the actual test well relationship curve of the bottom hole pressure or the bottom hole pressure derivative over time in the log-logarithmic coordinate system;

判断模块6：用于将所述实测试井关系曲线与优势通道识别的所述试井典型特征曲线进行形态比较，判断优势通道是否存在并确定其发育级别。 Judgment module 6: for comparing the shape of the actual test well relationship curve with the typical well test characteristic curve identified by the dominant channel, judging whether the dominant channel exists and determining its development level. the

还可包括： May also include:

数据平滑处理模块4：用于将所述井底压力或所述井底压力导数与时间的关系进行数据平滑处理后输入所述绘制实测试井关系曲线模块。 Data smoothing processing module 4: for smoothing the data of the bottom hole pressure or the relationship between the bottom hole pressure derivative and time and then inputting it into the module for drawing actual test well relationship curves. the

上述各个模块可设置在计算机中，通过设定计算机对各模块的控制，可以实现自动检测和判断。同时可以利用计算机的显示输出模块及其显示输出设备(例如显示屏、打印机等)，将检测和判断结果显示或输出。也可将绘制好的典型特征曲线图版提前存储在计算机的存储记忆模块中，直接执行步骤b～步骤e。该步骤在计算机中的循环执行及判断优势通道是否存在并确定其发育级别的具体流程均可采用较成熟的现有技术，在此不作赘述。 Each of the above-mentioned modules can be set in a computer, and automatic detection and judgment can be realized by setting the computer to control each module. At the same time, the display and output module of the computer and its display and output devices (such as display screen, printer, etc.) can be used to display or output the detection and judgment results. It is also possible to store the drawn typical characteristic curves in advance in the storage memory module of the computer, and directly execute steps b to e. The cyclic execution of this step in the computer and the specific process of judging whether the dominant channel exists and determining its developmental level can all adopt relatively mature existing technologies, which will not be repeated here. the

下面以具体三次测试结果为例来说明基于不稳定试井的优势通道识别方法的实际应用情况。 In the following, the actual application of the dominant channel identification method based on unstable well testing is illustrated by taking the results of the three tests as examples. the

实施例一 Embodiment one

所选试井油田储层物性好，为高孔中高渗储层，岩石胶结疏松，填隙物含量较少。经过多年的开采，目前已进入高含水期，区块内优势通道发育严重，造成油井排剩余油饱和度高，水井排水淹严重，纵向吸水剖面差异很大，水线突破速度很快。优势通道的存在已经对该油田采收率的进一步提高造成了严重的影响。 The reservoirs of the selected well test oilfields have good physical properties, are high porosity, medium and high permeability reservoirs, the rocks are loosely cemented, and the content of interstitial substances is small. After years of exploitation, it has now entered a period of high water cut, and the dominant channels in the block are seriously developed, resulting in high residual oil saturation in oil well drainage, serious drainage and flooding of water wells, great differences in vertical water absorption profiles, and rapid breakthrough of water lines. The existence of dominant channels has seriously affected the further improvement of oil recovery. the

下面以该油田A井为例说明基于不稳定试井的优势通道识别方法的实际应用情况。事先对该油田A井分别进行了两次不稳定试井测试，这两次测试时间相隔了1年多。两次测试过程均依照《SY/T6172-2006中华人民共和国石油天然气行业标准——油井试井技术规范》进行，并记录测试过程中的井底流压，计算压力导数，在双对数坐标系下绘制实测的井底流压及其压力导数随时间变化的测试曲线。前后两次测试结果所绘制的测试曲线分别如附图7、图8所示。 Taking Well A of this oilfield as an example to illustrate the practical application of the dominant channel identification method based on unstable well testing. In advance, two unstable well test tests were carried out in Well A of the oilfield, and the time interval between the two tests was more than one year. The two tests were carried out in accordance with the "SY/T6172-2006 Petroleum and Natural Gas Industry Standard of the People's Republic of China-Technical Specifications for Oil Well Testing", and the bottom hole flow pressure during the test was recorded, and the pressure derivative was calculated. In the double logarithmic coordinate system Draw the test curve of the measured bottomhole flowing pressure and its pressure derivative as a function of time. The test curves drawn by the two test results before and after are shown in Figure 7 and Figure 8 respectively. the

将该油田A井第一次测试所得到的井底流压和压力导数随时间变化的曲线(见附图7)与本发明提供的不同级别优势通道的试井典型特征曲线(见附图2、附图3、附图4和附图5A)做比较，可以发现附图7中测试曲线与图3中典型特征曲线的趋势完全一致，而与其它的典型特征曲线相差很大，因此可判断出A井在第一次测试时周围存在优势通道，但优势通道的发育级别较低，可归为普通高渗透层。 The curve (see accompanying drawing 7) and the well test typical characteristic curve (see accompanying drawing 2, 2, Accompanying drawing 3, accompanying drawing 4 and accompanying drawing 5A) compare, can find that the trend of test curve among the accompanying drawing 7 and typical characteristic curve in Fig. 3 is completely consistent, and differs greatly with other typical characteristic curves, therefore can judge There are dominant channels around Well A in the first test, but the development level of the dominant channels is low, which can be classified as ordinary high-permeability layers. the

按照同样的步骤，对A井第二次测得的井底流压及其压力导数随时间变化的曲线(见附图8)进行分析。发现附图8中的测试曲线与图4中典型特征曲线的趋势完全一致，而与其它的典型特征曲线相差很大，因此可判断出A井在第二次测试时周围仍存在优势通道，且优势通道的发育级别提高，可归为强高渗条带。 According to the same procedure, analyze the curve of bottom hole flowing pressure and its pressure derivative with time (see Figure 8) measured for the second time in well A. It is found that the test curve in the accompanying drawing 8 is completely consistent with the trend of the typical characteristic curve in Fig. 4, but is very different from other typical characteristic curves, so it can be judged that there is still a dominant channel around Well A during the second test, and The development level of the dominant channel is increased, which can be classified as a strong hypertonic band. the

该井在两次不稳定试井测试后均进行了井间示踪剂监测。示踪剂监测解释结果也与不稳定试井方法的解释结果完全一致。 The well underwent interwell tracer monitoring after two unstable well test tests. The interpretation results of tracer monitoring are also completely consistent with those of the unstable well testing method. the

实施例二 Example two

以测试油田B井为例说明基于不稳定试井的优势通道识别方法的实际应用情况。将B井测试所得到的井底流压及其压力导数随时间变化的曲线(见附图9)与本发明提供的不同级别优势通道的试井典型特征曲线(见附图2、附图3、附图4和附图5A)做比较，可以发现附图9中的测试曲线与图5中典型特征曲线的趋势完全一致，而与其它的典型特征曲线相差很大，因此可判断出B井在测试时周围存在发育级别很高的优势通道，可归为大孔道。 Taking Well B in the test oilfield as an example to illustrate the practical application of the dominant channel identification method based on unstable well testing. The curve (see accompanying drawing 9) and the well testing typical characteristic curve (see accompanying drawing 2, accompanying drawing 3, accompanying drawing 2, accompanying drawing 3, Accompanying drawing 4 and accompanying drawing 5A) compare, can find that the test curve among the accompanying drawing 9 is completely consistent with the trend of the typical characteristic curve in Fig. 5, and differs greatly with other typical characteristic curves, therefore can judge that B well is At the time of testing, there were dominant channels with a high developmental level around them, which could be classified as macropores. the

该井的解释结果与油田现场的认识完全一致，且在对该井进行不稳定试井以后，对该井对应的水井注入凝胶颗粒进行调剖。堵剂注入时的水井动态表明B井周围存在大孔道，与不稳定试井方法的识别结果相符。 The interpretation result of this well is completely consistent with the understanding of the oil field, and after the unstable well test of this well, the corresponding water well of this well is injected with gel particles for profile control. The water well performance during plugging agent injection shows that there are large pores around Well B, which is consistent with the identification results of the unstable well test method. the

本发明通过对油井进行压力恢复测试，记录测试过程中井底压力随时间恢复的资料，计算井底压力导数；在双对数坐标系中绘制实测的无因次井底压力及其导数随无因次时间变化的关系曲线；将实测曲线与本发明中提供的不同级别优势通道的试井典型曲线进行比较，即可检测和判断该井周围是否存在优势通道以及其发育级别，该方法具有准确性高、可操作性强等特点，可为油田增产措施的实施提供指导。 The present invention carries out the pressure restoration test on the oil well, records the data of the recovery of the bottom hole pressure with time during the test process, and calculates the derivative of the bottom hole pressure; draws the measured dimensionless bottom hole pressure and its derivative with the The relationship curve of sub-time changes; the measured curve is compared with the typical well test curves of different grades of dominant channels provided in the present invention, so as to detect and judge whether there are dominant channels around the well and its development level, the method has accuracy It has the characteristics of high performance and strong operability, which can provide guidance for the implementation of oilfield production increase measures. the

当然，本发明还可有其它多种实施例，在不背离本发明精神及其实质的情况下，熟悉本领域的技术人员当可根据本发明作出各种相应的改变和变形，但这些相应的改变和变形都应属于本发明所附的权利要求的保护范围。 Certainly, the present invention also can have other multiple embodiments, without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and deformations according to the present invention, but these corresponding Changes and deformations should belong to the scope of protection of the appended claims of the present invention. the

Claims

1. a water controlled field advantage channel recognition method, is characterized in that, application transient pressure recovers well test data to be identified the advantage passage forming in water controlled field development process, comprises the steps:

A, well testing characteristic feature curve plate step is set: the well testing characteristic feature curve plate that advantage channel recognition is set;

B, well testing bottom hole pressure measurement step: pressure gauge is lowered to well testing test purpose layer middle part, and surface shut-in, utilizes pressure gauge to record the data that bottom pressure recovered with the testing time;

C, well testing bottom pressure derivative calculations step: the bottom pressure that calculates described well testing to the first derivative of time natural logrithm as bottom pressure derivative;

D, actual measurement well testing relation curve plot step: take the testing time as abscissa, take flowing bottomhole pressure (FBHP) and pressure derivative as ordinate, in log-log coordinate system, draw described bottom pressure or the time dependent actual measurement well testing of described bottom pressure derivative relation curve;

E, judge the existence of advantage passage and grow rank step: the described well testing characteristic feature curve of described actual measurement well testing relation curve and advantage channel recognition is carried out to form comparison, judge whether advantage passage exists and determine its growth rank.

2. water controlled field advantage channel recognition method as claimed in claim 1, is characterized in that, before described actual measurement well testing relation curve plot step, also comprises:

D0, data smoothing treatment step: described bottom pressure or described bottom pressure derivative and the relation of time are carried out to data smoothing processing to reduce noise.

3. water controlled field advantage channel recognition method as claimed in claim 2, it is characterized in that, described data smoothing treatment step adopts Wavelet Transform, linear interpolation exponential smoothing or Fourier transform to carry out data smoothing processing to described bottom pressure or described bottom pressure derivative.

4. the water controlled field advantage channel recognition method as described in claim 1,2 or 3, it is characterized in that, described actual measurement well testing relation curve is the double-log relation curve of zero dimension bottom pressure and non dimensional time or the double-log relation curve of zero dimension bottom pressure derivative and non dimensional time.

5. the water controlled field advantage channel recognition method as described in claim 1,2 or 3, it is characterized in that, the described well testing characteristic feature curve plate step that arranges comprises and normal reservoir well test curve plate is set and advantage passage well testing characteristic feature curve plate is set.

6. water controlled field advantage channel recognition method as claimed in claim 5, is characterized in that, described normal reservoir well test curve plate is the transient seepage flow model curve plate of center, the infinitely great stratum of homogeneous a bite well.

7. water controlled field advantage channel recognition method as claimed in claim 5, is characterized in that, the described advantage passage well testing characteristic feature curve plate that arranges comprises:

A1, set up model condition is set: according to the origin cause of formation of advantage passage and grow rank and set up the assumed condition that model arranges;

A2, set up Mathematical Modeling: set up respectively corresponding Mathematical Modeling according to the origin cause of formation of described advantage passage and the assumed condition of growing rank;

A3, model solution and characteristic feature Drawing of Curve: respectively described Mathematical Modeling solved and draw corresponding advantage passage well testing characteristic feature curve plate according to solving result.

8. water controlled field advantage channel recognition method as claimed in claim 7, it is characterized in that, described advantage passage well testing characteristic feature curve plate grows from weak to strong and comprises common high permeability zone indicatrix plate, strong high infiltration strip indicatrix plate and macropore indicatrix plate according to the origin cause of formation of advantage passage and growth rank.

9. a water controlled field advantage passage identification device, is characterized in that, application transient pressure recovers well test data to be identified the advantage passage forming in water controlled field development process, comprising:

Characteristic feature curve plate module is set: for arranging and store the well testing characteristic feature curve plate of advantage channel recognition;

Bottom hole pressure measurement module: comprise pressure gauge and pressure record unit, described pressure gauge is conveyed into described pressure record unit for testing well testing with the bottom pressure of testing time recovery the described bottom pressure that test is obtained;

Bottom pressure derivative calculations module: for calculate described bottom pressure to the first derivative of time natural logrithm as bottom pressure derivative and store this bottom pressure derivative;

Draw well testing relation curve module: for drawing described bottom pressure or the time dependent actual measurement well testing of described bottom pressure derivative relation curve in log-log coordinate system;

Judge module: for the described well testing characteristic feature curve of described actual measurement well testing relation curve and advantage channel recognition is carried out to form comparison, judge advantage passage whether exist and determine its grow rank.

10. water controlled field advantage passage identification device as claimed in claim 9, is characterized in that, also comprises:

Data smoothing processing module: for described bottom pressure or described bottom pressure derivative and the relation of time are carried out data smoothing process after the described drafting actual measurement of input well testing relation curve module.