WO2019127879A1 - 一种定量表征不同河型河道砂体的几何参数关系的方法 - Google Patents
一种定量表征不同河型河道砂体的几何参数关系的方法 Download PDFInfo
- Publication number
- WO2019127879A1 WO2019127879A1 PCT/CN2018/076934 CN2018076934W WO2019127879A1 WO 2019127879 A1 WO2019127879 A1 WO 2019127879A1 CN 2018076934 W CN2018076934 W CN 2018076934W WO 2019127879 A1 WO2019127879 A1 WO 2019127879A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- river
- channel
- width
- length
- sand
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/17—Function evaluation by approximation methods, e.g. inter- or extrapolation, smoothing, least mean square method
Definitions
- the invention relates to the technical field of channel sand body space prediction, and particularly relates to a method for quantitatively characterizing the geometric parameter relationship of different river channel sand bodies.
- the oil and gas reservoir sand bodies are buried deep underground. In the middle and later stages of oilfield development, it is important to establish accurate geological models to grasp the distribution rules of remaining oil and improve oil recovery. The accuracy of the reservoir sandstone geological knowledge base is affected. The key factor in its success or failure. The geometric parameters of reservoir sand bodies and their relationships are difficult to fully and accurately characterize only by drilling, logging and seismic data. Therefore, the quantitative knowledge base is constructed by using modern river sediments, and then applied to the quantitative prediction of the size and geometric characteristics of underground sand bodies. Is an effective way to solve this problem.
- the object of the present invention is to solve the above-mentioned deficiencies, and propose a method for meticulously characterizing the quantitative relationship between the sand body geometric parameters for different types of river sedimentary features.
- a method for quantitatively characterizing geometric parameter relationships of different river channel sand bodies, based on Google Earth specifically includes the following steps:
- Step 1 Use Google Earth to find typical rivers of the four types of rivers: braided river, tiller river, meandering river and reticulated river;
- Step 2 Measure the basic data of river channels of typical rivers through Google Earth, and establish a geological database of river sand body characteristic parameters of various types of rivers as the basic source data of the geological knowledge base;
- Step 3 According to the basic data obtained by Google Earth, a quantitative formula is applied to the correlation between geometric parameters of different river channel sand bodies;
- Step 4 Summarize the empirical formulas of the correlations between the 14 types of river channel sandstones with significant correlations.
- the 10 items of the 14 related empirical formulas relate to the length of the river, the width of the river, the length of the channel, and the channel. Quantitative characterization relationship with width is used for prediction and calculation of geometric parameters of each river sand body; 4 items are related to river-shaped beach width and heart-street length, point dam width and point dam length, channel sand dam width and channel sand dam length It is used to predict the geometric parameters of the underground river reservoir sand bodies, and provide the geological model basic parameter data for reservoir modeling and reservoir numerical simulation;
- Step 5 Apply the empirical formula of the correlation in step 4 to the river sand body of the river phase to predict the width of the river channel and the river channel.
- the basic data of the channel measured by Google Earth includes: bifurcation parameters, channel arc length, channel diameter, channel width, channel width, curvature and slope.
- the slope comprises a maximum slope and an average slope.
- the characteristic parameters of the river sand body measured by Google Earth, wherein:
- the characteristic parameters of the channel sand body of the braided river include the number of heart beaches, the maximum heart beach length, the maximum heart beach width, the minimum heart beach length and the minimum heart beach width;
- the characteristic parameters of the river sand body of the Tuanhe River include the number of river sand dams, the length of the river sand dam and the width of the river sand dam;
- the characteristic parameters of the channel sand body of the meandering river include the point dam arc length, the point dam length and the point dam width;
- the characteristic parameters of the channel sand body of the reticulated river include the number of river sand dams, the length of the largest channel sand dam, the width of the largest channel sand dam, the length of the minimum channel sand dam and the width of the minimum channel sand dam.
- the image of each river segment is intercepted by Google Earth, and the basic data is obtained, and the characteristic parameters of the river sand body of each type of river are established. database.
- the channel sand body characteristic parameters of the braided river include 20 groups, and the channel sand body characteristic parameters of the Weihe River include 68 groups, and the meandering river
- the characteristic parameters of the channel sand body include 74 groups.
- the channel sand body characteristic parameters of the reticulated river include 54 groups, and the cumulative data is 2821.
- the correlation between the basic parameters of each river type and its characteristic parameters is fitted.
- 10 of the 14 correlation empirical formulas relate to the quantitative relationship between the width of the river channel and the length of the river channel, the width of the river channel, and the length of the channel arc; and the braided river channel
- the relationship between the width and the length of the river, the width of the river, and the length of the arc of the river are specifically the formulas (1) to (3):
- Wb is the width of the braided river channel, the unit is km;
- Rb is the width of the braided river channel, the unit is km;
- Lb is the length of the braided river channel, the unit is km;
- Ab is the arc length of the braided river channel, the unit is Km;
- Wab is the width of the river channel of the Tenghe River, and the unit is km
- Rab is the width of the river channel of the Tenghe River, and the unit is km
- Lab is the length of the river channel of the Tenghe River, and the unit is km
- the relationship between the width of the meandering river channel and the length of the river channel, the width of the river channel, and the arc length of the river channel is specifically (6) to (8);
- Wm is the width of the meandering river channel, the unit is km;
- Rm is the width of the meandering river channel, the unit is km;
- Lm is the length of the meandering river channel, the unit is km;
- Am is the arc length of the meandering river channel, the unit is Km;
- Ras is the width of the reticulated river channel, unit km; Aas is the arc length of the reticulated river channel, the unit is km; Was is the width of the reticulated river channel, the unit is km.
- four of the 14 correlation empirical formulas are related to the quantification of the river-shaped beach width and the beach length, the point dam width and the point dam length, the channel sand dam width and the length of the river sand dam. Relationships, including “width-length of braided river heart beach”, “width-length of sand dam of Tuanhe River”, “width-length of meandering river dam” and “width-length of reticulated river channel sand dam”, For predicting the geometric parameters of the underground river sand body, specifically for the formula (11) ⁇ (14):
- W 1 is the width of the braided river heart beach, and the unit is km
- L 1 is the length of the braided river heart beach, and the unit is km
- W 2 is the width of the sand dam of the Fenhe River, and the unit is km
- L 2 is the length of the sand dam of the Fenhe River, and the unit is km
- W 3 is the width of the meandering river point dam, the unit is km;
- L 3 is the length of the meandering river point dam, and the unit is km;
- W 4 is the width of the reticulated river channel sand dam, the unit is km;
- L 4 is the length of the reticulated river channel sand dam, the unit is km.
- the invention takes the difference of sedimentary development characteristics of different river channel sand bodies as the premise, and summarizes the corresponding sand body prediction empirical formula for different river types.
- the prediction result is more consistent with the characteristics of river sedimentary characteristics and evolution, and can accurately Characterizing the two-dimensional and three-dimensional geometric parameters of the river sand bodies and their relationships, it provides a more accurate geological geometric model for the fine description and prediction of the underground river facies.
- Figure 1 is a flow chart showing the geometric relationship of the method for quantitatively characterizing the geometric parameters of different river channel sand bodies
- FIG. 2 is a schematic diagram of measurement of characteristic parameters of a braided river
- Figure 3 is a schematic diagram of measurement of characteristic parameters of the Biyu River
- Figure 4 is a schematic diagram of measurement of characteristic parameters of meandering river
- Figure 5 is a schematic diagram of measurement of characteristic parameters of a mesh river
- Figure 6a is a quantitative representation of the correlation between the width of the channel of the braided river and the width of the channel;
- Figure 6b is a schematic diagram showing the quantitative relationship between the length of the channel of the braided river and the width of the channel;
- Figure 6c is a quantitative representation of the correlation between the arc length of the braided river and the width of the channel;
- Figure 7a is a quantitative representation of the correlation between the width of the channel of the Fenhe River and the width of the channel;
- Figure 7b is a schematic diagram showing the quantitative relationship between the length of the river channel and the width of the river channel of the Tiller River;
- Figure 8a is a quantitative representation of the correlation between the width of the channel of the meandering river and the width of the channel;
- Figure 8b is a quantitative representation of the correlation between the length of the channel of the meandering river and the width of the channel;
- Figure 8c is a quantitative representation of the correlation between the arc length and the width of the channel of the meandering river
- Figure 9a is a schematic diagram showing the quantitative relationship between the width of the channel of the reticulated river and the width of the channel;
- Figure 9b is a schematic diagram showing the quantitative relationship between the arc length of the river and the width of the channel;
- Figure 10a is a schematic diagram showing the quantitative characterization of the width-length correlation of the braided river bank
- Figure 10b is a schematic diagram showing the quantitative characterization of the width-length correlation of the sand dam of the Fenhe River;
- Figure 10c is a schematic diagram showing the quantitative characterization of the width-length correlation of the meandering river point dam
- Figure 10d is a quantitative representation of the width-length correlation of the reticulated river channel sand dam.
- a method for quantitatively characterizing the geometrical parameters of different river channel sand bodies is based on Google Earth and includes the following steps:
- Step 1 Use Google Earth to find typical rivers of the four types of rivers: braided river, tiller river, meandering river and reticulated river; the selected river must be affected or less affected by human activities, and finally select the Lena River,
- Step 2 Measure the basic data of river channels of typical rivers through Google Earth, and establish a geological database of river sand body characteristic parameters of various types of rivers as the basic source data of the geological knowledge base;
- Step 3 According to the basic data obtained by Google Earth, a quantitative formula is applied to the correlation between geometric parameters of different river channel sand bodies;
- Step 4 Summarize the empirical formulas of the correlations between the 14 types of river channel sandstones with significant correlations.
- the 10 items of the 14 related empirical formulas relate to the length of the river, the width of the river, the length of the channel, and the channel. Quantitative characterization relationship with width is used for prediction and calculation of geometric parameters of each river sand body; 4 items are related to river-shaped beach width and heart-street length, point dam width and point dam length, channel sand dam width and channel sand dam length It is used to predict the geometric parameters of the underground river reservoir sand bodies, and provide the geological model basic parameter data for reservoir modeling and reservoir numerical simulation;
- Step 5 Apply the empirical formula of the correlation in step 4 to the river sand body of the river phase to predict the width of the river channel and the river channel.
- the results show that the present invention can more accurately express the two-dimensional and three-dimensional geometric relations of different river sand bodies by improving the sedimentary characteristics of each river type, and improve the accuracy of reservoir prediction.
- step two the basic data of the river channel measured by Google Earth include: bifurcation parameters, channel arc length, channel diameter, channel width, channel width, curvature and slope.
- the slope includes the maximum slope and the average slope.
- step two the characteristics of the river sand body measured by Google Earth, where:
- the characteristic parameters of the channel sand body of the braided river include the number of heart beaches, the maximum heart beach length, the maximum heart beach width, the minimum heart beach length and the minimum heart beach width; taking the Amazon River 53 as an example; Nature of the river section: braided river; basic parameters: river arc length ACB, river length ADB, river channel width EF, river channel width GH; characteristic parameters: white dotted section is the length and width of different scales.
- the characteristic parameters of the river sand body of the Fenhe River include the number of river sand dams, the length of the river sand dam and the width of the river sand dam; taking the Heilongjiang 10 measuring river section as an example; the nature of the river section: the branching river; the basic parameters : River arc length ACB, river length ADB, river width EF, river channel width GH; Characteristic parameters: white dotted section is the length and width of river dams of different scales.
- the characteristic parameters of the channel sand body of the meandering river include the point dam arc length, the point dam length and the point dam width; taking the Amazon River 36 section as an example; the section nature: the meandering river; the basic parameters: the river channel Arc length ACB, channel length ADB, channel width EF, river channel width GH; characteristic parameters: white dotted line segment is the length and width of different scale points of different periods.
- the characteristic parameters of the channel sand body of the reticulated river include the number of channel sand dams, the length of the largest channel sand dam, the width of the largest channel sand dam, the length of the minimum channel sand dam and the width of the minimum channel sand dam.
- the nature of the river section reticulated river; basic parameters: river arc length ACB, river length ADB, river channel width EF, river channel width GH; characteristic parameters: white dotted section is different scale river sand Dam length and width
- Google Earth In the second step, through Google Earth to measure the basic data of the rivers of typical rivers, Google Earth intercepts the images of the river sections to measure sequentially, obtains the basic data, and establishes a geological database of river sand body characteristic parameters of various types of rivers.
- the characteristic parameters of the channel sand body of the braided river include 20 groups.
- the characteristic parameters of the channel sand body of the Weihe River include 68 groups, and the channel sand body of the meandering river.
- the characteristic parameters include 74 groups.
- the channel sand body characteristic parameters of the reticulated river include 54 groups, and the cumulative data is 2821.
- step 3 according to the basic data obtained in step two, the correlation between the basic parameters of each river type and its characteristic parameters is fitted.
- step 4 10 of the 14 relevant empirical formulas relate to the quantitative relationship between the width of each river channel and the length of the channel, the width of the channel, and the length of the channel; including the width of the braided river channel and the length of the channel,
- the relationship between the width of the river and the length of the arc of the river is shown in Figure 6, specifically the formulas (1) to (3):
- Wb is the width of the braided river channel, the unit is km;
- Rb is the width of the braided river channel, the unit is km;
- Lb is the length of the braided river channel, the unit is km;
- Ab is the arc length of the braided river channel, the unit is Km;
- Wab is the width of the river channel of the Tenghe River, and the unit is km
- Rab is the width of the river channel of the Tenghe River, and the unit is km
- Lab is the length of the river channel of the Tenghe River, and the unit is km
- Wm is the width of the meandering river channel, the unit is km;
- Rm is the width of the meandering river channel, the unit is km;
- Lm is the length of the meandering river channel, the unit is km;
- Am is the arc length of the meandering river channel, the unit is Km;
- Ras is the width of the reticulated river channel, unit km; Aas is the arc length of the reticulated river channel, the unit is km; Was is the width of the reticulated river channel, the unit is km.
- step 4 of the 14 empirical correlation formulas relate to the quantitative relationship between the river-shaped beach width and the beach length, the point dam width and the point dam length, the channel sand dam width and the length of the channel sand dam, including “Width-length of braided river heart beach”, “width-length of sand dam of Tuanhe River channel”, “width-length of meandering river dam” and “width-length of creek sand dam” for predicting underground
- the geometric parameters of the river sand body are specifically expressed by the formulas (11) to (14):
- W 1 is the width of the braided river heart beach, and the unit is km
- L 1 is the length of the braided river heart beach, and the unit is km
- W 2 is the width of the sand dam of the Fenhe River, and the unit is km
- L 2 is the length of the sand dam of the Fenhe River, and the unit is km
- W 3 is the width of the meandering river point dam, the unit is km;
- L 3 is the length of the meandering river point dam, and the unit is km;
- W 4 is the width of the reticulated river channel sand dam, the unit is km;
- L 4 is the length of the reticulated river channel sand dam, the unit is km.
- step 5 using the above empirical formula to calculate the river channel and channel width of the main phase of the rivers of the main strata Ng6 4 , Ng6 1 (2) , Nm7 3 , Nm7 2 (2), etc., and The data calculated according to the previous experience formula were compared (Table 1). The results show that the invention distinguishes different river types, and it is more suitable for the sedimentary laws of different river types than the previous ones, which can more accurately express the two-dimensional and three-dimensional geometric relations of various river sand bodies.
- Ng6 4 of the Neogene main producing layer in a certain area is a braided river
- Ng6 1 (2) is a branching river
- Nm7 3 and Nm7 2 (2) are meandering rivers.
- the river width is calculated according to the previous experience formula, and then the river sand of the main layer of the area is calculated by using equations (1), (4) and (6).
- the width of the river channel is compared with the results obtained by similar empirical formulas.
- the main process is as follows:
- the Lederer relationship is used to find the width of the Lorenz channel Rl (the braided river channel width Rb, the bifurcation river channel width Rab, the meandering river channel width Rm), and the channel depth and the river width are exponential when the channel curvature is >1.7.
- Rl is the width of the Lorenz channel, m
- H is the thickness of the channel positively swirling back to the sand body, m; using the same method to calculate the width of the braided river channel Rb, m; the width of the river channel of the branching river Rab, m; meandering River channel width Rm, m.
- Wl is the width of the Lorenz channel, m
- Rl is the width of the Lorenz channel, m.
- Ng6 4 is a braided river type, calculated by formula (1)
- Ng6 1 (2) is a branching river type, calculated by formula (4)
- Nm7 3 and Nm7 2 (2) are meandering river type, with Calculated by equation (6), the calculation results are shown in Table 1.
- the “Lorenz channel width” of the main sand bodies in a small area in a certain area is not much different, that is, although the river types of the main layers are different, the width of the river belt is very similar; and the different intervals calculated by the present invention are different.
- the width of the channel belt varies greatly.
- the width of the channel of the Minghuazhen Formation is significantly narrower than the width of the channel belt of the Guantao Formation.
- the width of the middle and upper channel of the upper section of the Guantao Formation is significantly narrower than the bottom.
- the invention takes the difference of sedimentary development characteristics of different river channel sand bodies as the premise of understanding, and summarizes the corresponding sand body prediction empirical formula for different river types, so the prediction result is more consistent with the law of river sedimentary characteristics and evolution, natural energy
- the two-dimensional and three-dimensional geometric parameters and their relationships of sand bodies in each river type are more accurately characterized, thus providing a more accurate geological geometric model for the fine description and prediction of underground river facies.
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Physics (AREA)
- Mathematical Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Computational Mathematics (AREA)
- Algebra (AREA)
- Software Systems (AREA)
- Remote Sensing (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Revetment (AREA)
Abstract
公开了一种定量表征不同河型河道砂体的几何参数关系的方法,具体涉及河道砂体空间预测领域。解决了现已建立的河流砂体经验公式定量化方面存在普遍的缺陷且适应性差的不足。该方法基于谷歌地球进行,具体包括:利用谷歌地球寻找辫状河、分汊河、曲流河和网状河四类河型的典型河流;通过谷歌地球测量典型河流的河道的基础数据,建立各类型河流的河道砂体特征参数地质数据库,作为地质知识库的基础源数据;依据谷歌地球获得的基础源数据,对不同河型河道砂体各几何参数之间的相关关系拟合定量公式;总结出14项相关性显著的各类河型河道砂体几何参数的相关关系经验公式,并将相关关系经验公式应用到河流相的河道砂体中预测河道及河道带宽度。
Description
本发明涉及河道砂体空间预测技术领域,具体涉及一种定量表征不同河型河道砂体的几何参数关系的方法。
河型划分有诸多分类方案。在前人的研究基础上,根据河道形态及沉积物特征将河流划分为辫状河、曲流河、分汊河、网状河及顺直河五种河型(王随继等,1999)的河流分类方案既满足了以油气生产为目的的河流储层沉积学家的需要,也满足了以防护水患、治理河流为目的的水利学家和地貌学家的需要,是使沉积学界、地貌学界和水利学界在一个统一的河型分类的格架中相互借鉴各自的研究成果,从而促进河流沉积学不断发展的有益尝试,因而日渐被学者们接受和认可。其中,顺直河是特殊环境下发育的产物,在自然界中并不常见。本发明就前四类河型开展研究进行几何关系定量表征。
油气储集砂体深埋于地下,在油田开发的中后期,建立精确的地质模型对掌握剩余油分布规律,提高石油采收率至关重要,储集砂体地质知识库的精度则是影响其成败的关键因素。储集砂体几何参数及其关系仅依靠钻井、测井和地震资料难以进行全面准确的表征,因此利用现代河流沉积构建定量知识库,然后将其应用于地下砂体规模与几何特征的定量预测,是解决该问题的有效方法。
前人在建立河流砂体经验公式的过程中做了诸多尝试,如Schumm公式,Leeder关系式,Leopold关系式等。但已有的经验公式一方面在定量化方面存在普遍的缺陷,即未能针对不同类型河流沉积特征细致刻画其砂体几何参数之间的定量关系;另一方面,已有的公式多源于现代河流沉积和野外露头的实地考察,因样本有限,局限性较大。
发明内容
本发明的目的是针对上述不足,提出了一种针对不同类型河流沉积特征细致刻画其砂体几何参数之间的定量关系的方法。
本发明具体采用如下技术方案:
一种定量表征不同河型河道砂体的几何参数关系的方法,基于谷歌地球进行,具体包括以下步骤:
步骤一:利用谷歌地球寻找辫状河、分汊河、曲流河和网状河四类河型的典型河流;
步骤二:通过谷歌地球测量典型河流的河道的基础数据,建立各类型河流的河道砂体特征参数地质数据库,作为地质知识库的基础源数据;
步骤三:依据谷歌地球获得的基础数据,对不同河型河道砂体各几何参数之间的相关关系拟合定量公式;
步骤四:总结出14项相关性显著的各类河型河道砂体几何参数的相关关系经验公式,所述14项相关关系经验公式中的10项涉及河道长度、河道宽度、河道弧长和河道带宽度定量表征关系,用于各河型砂体几何参数的预测和计算;4项涉及对应河型心滩宽度与心滩长度、点坝宽度与点坝长度、河道砂坝宽度与河道砂坝长度,用于预测地下河流储集砂体的几何参数,为储层建模和油藏数值模拟提供地质模型基础参数数据;
步骤五:将步骤四中的相关关系经验公式应用到河流相的河道砂体中,预测河道及河道带宽度。
优选地,所述步骤二中,通过谷歌地球测量的河道的基础数据包括:分汊参数、河道弧长、河道直径、河道宽带、河道带宽度、曲率和坡降。
优选地,所述坡降包括最大坡降以及平均坡降。
优选地,所述步骤二中,通过谷歌地球测量的河道砂体特征参数,其中:
辫状河的河道砂体特征参数包括心滩数量、最大心滩长度、最大心滩宽度、最小心滩长度和最小心滩宽度;
分汊河的河道砂体特征参数包括河道砂坝数量、河道砂坝长度和河道砂坝宽度;
曲流河的河道砂体特征参数包括点坝弧长、点坝长度和点坝宽度;
网状河的河道砂体特征参数包括河道砂坝数量、最大河道砂坝长度、最大河道砂坝宽度、最小河道砂坝长度和最小河道砂坝宽度。
优选地,所述步骤二中,通过谷歌地球测量典型河流的河道的基础数据过程中,利用谷歌地球截取各河段图像依次进行测量,获得基础数据,建立各类型河流的河道砂体特征参数地质数据库。
优选地,截取22个河段,测得220组河道砂体特征参数,其中辫状河的河道砂体特征参数包括20组,分汊河的河道砂体特征参数包括68组,曲流河的河道砂体特征参数包括74组,网状河的河道砂体特征参数包括54组,累计数据2821个。
优选地,所述步骤三中,依据步骤二所得的基础数据,对各河型基础参数及其特征参数之间相关关系进行两两拟合。
优选地,所述步骤四中,14项相关关系经验公式中有10项涉及各河型河道带宽度与河道长度、河道宽度、河道弧长和之间的定量表征关系;包括辫状河河道带宽度与河道长度、河道宽度、河道弧长的相关关系,具体为式(1)~(3):
Wb=5.4374Rb
0.7103 (1)
Lb=0.2453Wb
2+0.2794Wb+3.4049 (2)
Ab=2.309Wb+1.8218 (3)
其中,Wb为辫状河河道带宽度,单位为km;Rb为辫状河河道宽度,单位为km;Lb为辫状河河道长度,单位为km;Ab为辫状河河道弧长,单位为km;
分汊河河道带宽度与河道长度、河道宽度的相关关系,具体为式(4)和(5);
Wab=2.9442Rab
0.8861 (4)
Lab=11.175Wab
0.9221 (5)
其中,Wab为分汊河河道带宽度,单位为km;Rab为分汊河河道宽度,单位为km;Lab为分汊河河道长度,单位为km;
曲流河河道带宽度与河道长度、河道宽度、河道弧长的相关关系,具体为式(6)~(8);
Wm=10.632Rm
1.4309 (6)
Lm=0.8095Wm
2-2.8952Wm+4.0103 (7)
Am=1.039Wm
2-3.113Wm+5.5318 (8)
其中,Wm为曲流河河道带宽度,单位为km;Rm为曲流河河道宽度,单位为km;Lm为曲流河河道长度,单位为km;Am为曲流河河道弧长,单位为km;
网状河河道带宽度与河道宽度、河道弧长的相关关系.具体为式(9)和(10):
Ras=0.1497Was
1.0458 (9)
Aas=4.6415Was
0.8617 (10)
其中,Ras为网状河河道宽度,单位km;Aas为网状河河道弧长,单位为km;Was为网状河河道带宽度,单位为km。
优选地,所述步骤四中,14项相关关系经验公式中有4项涉及对应河型心滩宽度与心滩长度、点坝宽度与点坝长度、河道砂坝宽度与河道砂坝长度的定量关系,包括“辫状河心滩宽度-长度”,“分汊河河道砂坝宽度-长度”,“曲流河点坝宽度-长度”和“网状河河道砂坝宽度-长度”,用于预测地下河流砂体的几何参数,具体为式(11)~(14):
W
1=0.3095L
1
0.7521 (11)
其中,W
1为辫状河心滩宽度,单位为km;L
1为辫状河心滩长度,单位为km;
W
2=0.3413L
2
0.9868 (12)
其中,W
2为分汊河河道砂坝宽度,单位为km;L
2为分汊河河道砂坝长度,单位为km;
W
3=0.3751L
3
1.1354 (13)
其中,W
3为曲流河点坝宽度,单位为km;L
3为曲流河点坝长度,单位为km;
W
4=0.3277L
4
0.8433 (14)
其中,W
4为网状河河道砂坝宽度,单位为km;L
4为网状河河道砂坝长度,单位为km。
本发明具有如下有益效果:
本发明以不同河型河道砂体的沉积发育特征的差异性为认识前提,针对不同河流类型总结出相应的砂体预测经验公式,预测结果更加符合河型沉积特征和演化的规律,能够准确地表征各河型河流砂体的二维及三维几何参数及其关系,为精细地描述和预测地下河流相储集砂体提供了更精准的地质几何模型。
图1为定量表征不同河型河道砂体的几何参数关系的方法的几何关系流程图;
图2为辫状河特征参数测量示意图;
图3为分汊河特征参数测量示意图;
图4为曲流河特征参数测量示意图;
图5为网状河特征参数测量示意图;
图6a为辫状河的河道带宽度-河道宽度的相关关系定量表征示意图;
图6b为辫状河的河道长度-河道带宽度的相关关系定量表征示意图;
图6c为辫状河的河道弧长-河道带宽度的相关关系定量表征示意图;
图7a为分汊河的河道带宽度-河道宽度的相关关系定量表征示意图;
图7b为分汊河的河道长度-河道带宽度的相关关系定量表征示意图;
图8a为曲流河的河道带宽度-河道宽度的相关关系定量表征示意图;
图8b为曲流河的河道长度-河道带宽度的相关关系定量表征示意图;
图8c为曲流河的河道弧长-河道带宽度的相关关系定量表征示意图;
图9a为网状河的河道宽度-河道带宽度的相关关系定量表征示意图;
图9b为网状河的河道弧长-河道带宽度的相关关系定量表征示意图;
图10a为辫状河心滩宽度-长度相关关系定量表征示意图;
图10b为分汊河河道砂坝宽度-长度相关关系定量表征示意图;
图10c为曲流河点坝宽度-长度相关关系定量表征示意图;
图10d为网状河河道砂坝宽度-长度相关关系定量表征示意图。
下面结合附图和具体实施例对本发明的具体实施方式做进一步说明:
如图1所示,一种定量表征不同河型河道砂体的几何参数关系的方法,基于谷歌地球(Google Earth)进行,具体包括以下步骤:
步骤一:利用谷歌地球寻找辫状河、分汊河、曲流河和网状河四类河型的典型河流;所 选河流须不受人类活动影响或影响较小,最终选定勒拿河、黑龙江、湄公河、拉凯阿河、巴拉圭河、亚马逊河、尼罗河、刚果河、密西西比河全球九条著名大河的典型河段,涵盖了不同河型。
步骤二:通过谷歌地球测量典型河流的河道的基础数据,建立各类型河流的河道砂体特征参数地质数据库,作为地质知识库的基础源数据;
步骤三:依据谷歌地球获得的基础数据,对不同河型河道砂体各几何参数之间的相关关系拟合定量公式;
步骤四:总结出14项相关性显著的各类河型河道砂体几何参数的相关关系经验公式,所述14项相关关系经验公式中的10项涉及河道长度、河道宽度、河道弧长和河道带宽度定量表征关系,用于各河型砂体几何参数的预测和计算;4项涉及对应河型心滩宽度与心滩长度、点坝宽度与点坝长度、河道砂坝宽度与河道砂坝长度,用于预测地下河流储集砂体的几何参数,为储层建模和油藏数值模拟提供地质模型基础参数数据;
步骤五:将步骤四中的相关关系经验公式应用到河流相的河道砂体中,预测河道及河道带宽度。结果表明,本发明由于切合各河型沉积特征,可更准确地表达不同河型砂体的二维及三维几何关系,提高储层预测的准确性。
步骤二中,通过谷歌地球测量的河道的基础数据包括:分汊参数、河道弧长、河道直径、河道宽带、河道带宽度、曲率和坡降,坡降包括最大坡降以及平均坡降。
步骤二中,通过谷歌地球测量的河道砂体特征参数,其中:
如图2所示,辫状河的河道砂体特征参数包括心滩数量、最大心滩长度、最大心滩宽度、最小心滩长度和最小心滩宽度;以亚马逊河53测量河段为例;河段性质:辫状河;基础参数:河道弧长ACB,河道长度ADB,河道宽度EF,河道带宽度GH;特征参数:白色虚线段为不同规模心滩长度和宽度。
如图3所示,分汊河的河道砂体特征参数包括河道砂坝数量、河道砂坝长度和河道砂坝宽度;以黑龙江10测量河段为例;河段性质:分汊河;基础参数:河道弧长ACB,河道长度ADB,河道宽度EF,河道带宽度GH;特征参数:白色虚线段为不同规模河道砂坝长度和宽度。
如图4所示,曲流河的河道砂体特征参数包括点坝弧长、点坝长度和点坝宽度;以亚马逊河36河段为例;河段性质:曲流河;基础参数:河道弧长ACB,河道长度ADB,河道宽度EF,河道带宽度GH;特征参数:白色虚线段为不同时期不同规模点坝长度和宽度。
如图5所示,网状河的河道砂体特征参数包括河道砂坝数量、最大河道砂坝长度、最大河道砂坝宽度、最小河道砂坝长度和最小河道砂坝宽度。以勒拿河4河段为例;河段性质:网状河;基础参数:河道弧长ACB,河道长度ADB,河道宽度EF,河道带宽度GH;特征参数: 白色虚线段为不同规模河道砂坝长度和宽度
步骤二中,通过谷歌地球测量典型河流的河道的基础数据过程中,利用谷歌地球截取各河段图像依次进行测量,获得基础数据,建立各类型河流的河道砂体特征参数地质数据库。
截取22个河段,测得220组河道砂体特征参数,其中辫状河的河道砂体特征参数包括20组,分汊河的河道砂体特征参数包括68组,曲流河的河道砂体特征参数包括74组,网状河的河道砂体特征参数包括54组,累计数据2821个。
步骤三中,依据步骤二所得的基础数据,对各河型基础参数及其特征参数之间相关关系进行两两拟合。
步骤四中,14项相关关系经验公式中有10项涉及各河型河道带宽度与河道长度、河道宽度、河道弧长和之间的定量表征关系;包括辫状河河道带宽度与河道长度、河道宽度、河道弧长的相关关系,如图6所示,具体为式(1)~(3):
Wb=5.4374Rb
0.7103 (1)
Lb=0.2453Wb
2+0.2794Wb+3.4049 (2)
Ab=2.309Wb+1.8218 (3)
其中,Wb为辫状河河道带宽度,单位为km;Rb为辫状河河道宽度,单位为km;Lb为辫状河河道长度,单位为km;Ab为辫状河河道弧长,单位为km;
分汊河河道带宽度与河道长度、河道宽度的相关关系,如图7所示,具体为式(4)和(5);
Wab=2.9442Rab
0.8861 (4)
Lab=11.175Wab
0.9221 (5)
其中,Wab为分汊河河道带宽度,单位为km;Rab为分汊河河道宽度,单位为km;Lab为分汊河河道长度,单位为km;
曲流河河道带宽度与河道长度、河道宽度、河道弧长的相关关系,如图8所示,具体为式(6)~(8);
Wm=10.632Rm
1.4309 (6)
Lm=0.8095Wm
2-2.8952Wm+4.0103 (7)
Am=1.039Wm
2-3.113Wm+5.5318 (8)
其中,Wm为曲流河河道带宽度,单位为km;Rm为曲流河河道宽度,单位为km;Lm为曲流河河道长度,单位为km;Am为曲流河河道弧长,单位为km;
网状河河道带宽度与河道宽度、河道弧长的相关关系,如图9所示,具体为式(9)和(10):
Ras=0.1497Was
1.0458 (9)
Aas=4.6415Was
0.8617 (10)
其中,Ras为网状河河道宽度,单位km;Aas为网状河河道弧长,单位为km;Was为网状河河道带宽度,单位为km。
步骤四中,14项相关关系经验公式中有4项涉及对应河型心滩宽度与心滩长度、点坝宽度与点坝长度、河道砂坝宽度与河道砂坝长度之间的定量关系,包括“辫状河心滩宽度-长度”,“分汊河河道砂坝宽度-长度”,“曲流河点坝宽度-长度”和“网状河河道砂坝宽度-长度”,用于预测地下河流砂体的几何参数,具体为式具体为式(11)~(14):
W
1=0.3095L
1
0.7521 (11)
其中,W
1为辫状河心滩宽度,单位为km;L
1为辫状河心滩长度,单位为km;
W
2=0.3413L
2
0.9868 (12)
其中,W
2为分汊河河道砂坝宽度,单位为km;L
2为分汊河河道砂坝长度,单位为km;
W
3=0.3751L
3
1.1354 (13)
其中,W
3为曲流河点坝宽度,单位为km;L
3为曲流河点坝长度,单位为km;
W
4=0.3277L
4
0.8433 (14)
其中,W
4为网状河河道砂坝宽度,单位为km;L
4为网状河河道砂坝长度,单位为km。
其中
式(11)~(14)均为W=AL
B形式,其拟合结果如图10所示,且相关系数较高,可用于预测地下河道砂体的几何参数。
在步骤五中,运用上述经验公式进行计算,得到某地区新近系Ng6
4、Ng6
1(2)、Nm7
3、Nm7
2(2)等主力层河流相砂体的河道及河道带宽度,并与根据前人经验公式计算所得的数据进行对比(表1)。结果表明,本发明由于区分了不同河型,与前人经验公式相比更加切合不同河型的沉积规律,可更准确地表达各类河流砂体的二维及三维几何关系。
表1
本发明人相关研究业已明确某地区新近系主力产层Ng6
4为辫状河、Ng6
1(2)为分汊河、Nm7
3和Nm7
2(2)为曲流河。在统计该地区所有钻井主力层河道砂体单层厚度基础上,结合前人经验公式计算得到河道宽度,然后运用式(1)、(4)以及(6)计算得到该地区主力层河流相砂体的河道带宽度,并与前人类似经验公式所得结果进行了对比。主要过程如下:
利用Leeder关系式求出Lorenz河道宽度Rl(辫状河河道宽度Rb,分汊河河道宽度Rab,曲流河河道宽度Rm),河道曲率>1.7时河道深度和河道宽度呈指数关系:
logRl=1.54logH+0.83
式中,Rl为Lorenz河道宽度,m;H为河道深度正旋回砂体厚度,m;用同样的方法计算得出辫状河河道宽度Rb,m;分汊河河道宽度Rab,m;曲流河河道宽度Rm,m。
运用Lorenz关系式计算得出“Lorenz河道带宽度”:
Wl=7.44Rl
1.01
式中,Wl为Lorenz河道带宽度,m;Rl为Lorenz河道宽度,m。计算结果见表1。
利用本发明所得的各河型河道砂体定量表征式分别计算,得出各主力层的河道带宽度。其中,Ng6
4为辫状河型,用式(1)计算;Ng6
1(2)为分汊河型,用式(4)计算;Nm7
3和Nm7
2(2)为曲流河型,用式(6)计算,计算结果见表1。
对比分析表1数据可知,某地区各小层主力砂体“Lorenz河道带宽度”相差不大,即尽管各主力层河型不同,但河道带宽度极为相近;而本发明计算所得的不同层段河道带宽度数值差别较大,其中明化镇组河道带宽度明显窄于馆陶组河道带宽度,馆陶组上段中上部河道带宽度明显窄于底部。
原因在于,Lorenz经验公式对河道带宽度的预测没有区分河型,对不同河型均使用了统一的计算公式,因而无法准确表征不同河型河道砂体几何参数的特异性,以此为地质模型自然无法精准预测地下储集砂体。本发明以不同河型河道砂体的沉积发育特征的差异性为认识前提,针对不同河流类型总结出相应的砂体预测经验公式,因而预测结果更加符合河型沉积特征和演化的规律,自然能更准确地表征各河型河流砂体的二维及三维几何参数及其关系,从而为精细地描述和预测地下河流相储集砂体提供了更精准的地质几何模型。
当然,上述说明并非是对本发明的限制,本发明也并不仅限于上述举例,本技术领域的技术人员在本发明的实质范围内所做出的变化、改型、添加或替换,也应属于本发明的保护范围。
Claims (9)
- 一种定量表征不同河型河道砂体的几何参数关系的方法,其特征在于,基于谷歌地球进行,具体包括以下步骤:步骤一:利用谷歌地球寻找辫状河、分汊河、曲流河和网状河四类河型的典型河流;步骤二:通过谷歌地球测量典型河流的河道的基础数据,建立各类型河流的河道砂体特征参数地质数据库,作为地质知识库的基础源数据;步骤三:依据谷歌地球获得的基础数据,对不同河型河道砂体各几何参数之间的相关关系拟合定量公式;步骤四:总结出14项相关性显著的各类河型河道砂体几何参数的相关关系经验公式,所述14项相关关系经验公式中的10项涉及河道长度、河道宽度、河道弧长和河道带宽度定量表征关系,用于各河型河道砂体几何参数的预测和计算;4项涉及对应河型心滩宽度与心滩长度、点坝宽度与点坝长度、河道砂坝宽度与河道砂坝长度,用于预测地下河流储集砂体的几何参数,为储层建模和油藏数值模拟提供地质模型基础参数数据;步骤五:将步骤四中的相关关系经验公式应用到河流相的河道砂体中,预测河道及河道带宽度。
- 如权利要求1所述的一种定量表征不同河型河道砂体的几何参数关系的方法,其特征在于,所述步骤二中,通过谷歌地球测量的河道的基础数据包括:分汊参数、河道弧长、河道直径、河道宽带、河道带宽度、曲率和坡降。
- 如权利要求2所述的一种定量表征不同河型河道砂体的几何参数关系的方法,其特征在于,所述坡降包括最大坡降以及平均坡降。
- 如权利要求1所述的一种定量表征不同河型河道砂体的几何参数关系的方法,其特征在于,所述步骤二中,通过谷歌地球测量的河道砂体特征参数,其中:辫状河的河道砂体特征参数包括心滩数量、最大心滩长度、最大心滩宽度、最小心滩长度和最小心滩宽度;分汊河的河道砂体特征参数包括河道砂坝数量、河道砂坝长度和河道砂坝宽度;曲流河的河道砂体特征参数包括点坝弧长、点坝长度和点坝宽度;网状河的河道砂体特征参数包括河道砂坝数量、最大河道砂坝长度、最大河道砂坝宽度、最小河道砂坝长度和最小河道砂坝宽度。
- 如权利要求1所述的一种定量表征不同河型河道砂体的几何参数关系的方法,其特征在于,所述步骤二中,通过谷歌地球测量典型河流的河道的基础数据过程中,利用谷歌地球截取各河段图像依次进行测量,获得基础数据,建立各类型河流的河道砂体特征参数地质数据库。
- 如权利要求5所述的一种定量表征不同河型河道砂体的几何参数关系的方法,其特征在于,截取22个河段,测得220组河道砂体特征参数,其中辫状河的河道砂体特征参数包括20组,分汊河的河道砂体特征参数包括68组,曲流河的河道砂体特征参数包括74组,网状河的河道砂体特征参数包括54组,累计数据2821个。
- 如权利要求6所述的一种定量表征不同河型河道砂体的几何参数关系的方法,其特征在于,所述步骤三中,依据步骤二所得的基础数据,对各河型基础参数及其特征参数之间相关关系进行两两拟合。
- 如权利要求1所述的一种定量表征不同河型河道砂体的几何参数关系的方法,其特征在于,所述步骤四中,14项相关关系经验公式中有10项涉及各河型河道带宽度与河道长度、河道宽度、河道弧长和之间的定量表征关系;包括辫状河河道带宽度与河道长度、河道宽度、河道弧长的相关关系,具体为式(1)~(3):Wb=5.4374Rb 0.7103 (1)Lb=0.2453Wb 2+0.2794Wb+3.4049 (2)Ab=2.309Wb+1.8218 (3)其中,Wb为辫状河河道带宽度,单位为km;Rb为辫状河河道宽度,单位为km;Lb为辫状河河道长度,单位为km;Ab为辫状河河道弧长,单位为km;分汊河河道带宽度与河道长度、河道宽度的相关关系,具体为式(4)和(5);Wab=2.9442Rab 0.8861 (4)Lab=11.175Wab 0.9221 (5)其中,Wab为分汊河河道带宽度,单位为km;Rab为分汊河河道宽度,单位为km;Lab为分汊河河道长度,单位为km;曲流河河道带宽度与河道长度、河道宽度、河道弧长的相关关系,具体为式(6)~(8);Wm=10.632Rm 1.4309 (6)Lm=0.8095Wm 2-2.8952Wm+4.0103 (7)Am=1.039Wm 2-3.113Wm+5.5318 (8)其中,Wm为曲流河河道带宽度,单位为km;Rm为曲流河河道宽度,单位为km;Lm为曲流河河道长度,单位为km;Am为曲流河河道弧长,单位为km;网状河河道带宽度与河道宽度、河道弧长的相关关系,具体为式(9)和(10):Ras=0.1497Was 1.0458 (9)Aas=4.6415Was 0.8617 (10)其中,Ras为网状河河道宽度,单位km;Aas为网状河河道弧长,单位为km;Was为网 状河河道带宽度,单位为km。
- 如权利要求1所述的一种定量表征不同河型河道砂体的几何参数关系的方法,其特征在于,所述步骤四中,14项相关关系经验公式中有4项涉及对应河型心滩宽度与心滩长度、点坝宽度与点坝长度、河道砂坝宽度与河道砂坝长度之间的定量关系,包括“辫状河心滩宽度-长度”,“分汊河河道砂坝宽度-长度”,“曲流河点坝宽度-长度”和“网状河河道砂坝宽度-长度”,用于预测地下河流砂体的几何参数,具体为式(11)~(14):W 1=0.3095L 1 0.7521 (11)其中,W 1为辫状河心滩宽度,单位为km;L 1为辫状河心滩长度,单位为km;W 2=0.3413L 2 0.9868 (12)其中,W 2为分汊河河道砂坝宽度,单位为km;L 2为分汊河河道砂坝长度,单位为km;W 3=0.3751L 3 1.1354 (13)其中,W 3为曲流河点坝宽度,单位为km;L 3为曲流河点坝长度,单位为km;W 4=0.3277L 4 0.8433 (14)其中,W 4为网状河河道砂坝宽度,单位为km;L 4为网状河河道砂坝长度,单位为km。
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201711470353.8 | 2017-12-29 | ||
CN201711470353.8A CN108255990A (zh) | 2017-12-29 | 2017-12-29 | 一种定量表征不同河型河道砂体的几何参数关系的方法 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2019127879A1 true WO2019127879A1 (zh) | 2019-07-04 |
Family
ID=62725087
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2018/076934 WO2019127879A1 (zh) | 2017-12-29 | 2018-02-22 | 一种定量表征不同河型河道砂体的几何参数关系的方法 |
Country Status (2)
Country | Link |
---|---|
CN (1) | CN108255990A (zh) |
WO (1) | WO2019127879A1 (zh) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111597732A (zh) * | 2020-06-02 | 2020-08-28 | 中国水利水电科学研究院 | 一种使用汊点影响区水面梯度的河网水流数值模拟方法 |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110874505B (zh) * | 2018-08-14 | 2022-11-04 | 中国石油天然气股份有限公司 | 一种辫状河储层建模的方法及装置 |
CN113190954A (zh) * | 2021-03-16 | 2021-07-30 | 广东石油化工学院 | 一种基于露头和井资料定量表征河道单砂体的方法 |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
RU2390806C2 (ru) * | 2008-01-09 | 2010-05-27 | Государственное образовательное учреждение высшего профессионального образования Марийский государственный технический университет | Способ гидрографической оценки речной сети по численности водотоков |
CN103942842A (zh) * | 2014-03-19 | 2014-07-23 | 中国石油天然气股份有限公司 | 嵌入式曲流河砂体建模方法 |
CN104978763A (zh) * | 2015-05-13 | 2015-10-14 | 中国矿业大学(北京) | 一种基于三维Douglas-Peucker算法的河网要素与DEM的同步综合地图仿真方法 |
CN105740464A (zh) * | 2016-03-03 | 2016-07-06 | 中国国土资源航空物探遥感中心 | 一种基于dem的河谷形态参数自动提取方法 |
CN107301263A (zh) * | 2017-04-05 | 2017-10-27 | 华东师范大学 | 一种基于单幅图像的河流网络过程式生成方法 |
CN107315813A (zh) * | 2017-06-29 | 2017-11-03 | 中国测绘科学研究院 | 一种stroke特征约束的树状河系层次关系构建及简化方法 |
Family Cites Families (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CA2579138C (en) * | 2004-09-10 | 2013-10-22 | Exxonmobil Upstream Research Company | Geologic models of subsurface sedimentary volumes |
CN104729445A (zh) * | 2015-03-11 | 2015-06-24 | 长江大学 | 河口坝几何形态测量方法 |
CN105607146B (zh) * | 2015-09-10 | 2017-10-03 | 中国海洋石油总公司 | 一种曲流河砂体规模的定量表征方法 |
CN105844709B (zh) * | 2016-03-25 | 2019-05-07 | 中国水利水电科学研究院 | 复杂河道地形流域洪水演进虚拟仿真的淹没线追踪方法 |
-
2017
- 2017-12-29 CN CN201711470353.8A patent/CN108255990A/zh active Pending
-
2018
- 2018-02-22 WO PCT/CN2018/076934 patent/WO2019127879A1/zh active Application Filing
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
RU2390806C2 (ru) * | 2008-01-09 | 2010-05-27 | Государственное образовательное учреждение высшего профессионального образования Марийский государственный технический университет | Способ гидрографической оценки речной сети по численности водотоков |
CN103942842A (zh) * | 2014-03-19 | 2014-07-23 | 中国石油天然气股份有限公司 | 嵌入式曲流河砂体建模方法 |
CN104978763A (zh) * | 2015-05-13 | 2015-10-14 | 中国矿业大学(北京) | 一种基于三维Douglas-Peucker算法的河网要素与DEM的同步综合地图仿真方法 |
CN105740464A (zh) * | 2016-03-03 | 2016-07-06 | 中国国土资源航空物探遥感中心 | 一种基于dem的河谷形态参数自动提取方法 |
CN107301263A (zh) * | 2017-04-05 | 2017-10-27 | 华东师范大学 | 一种基于单幅图像的河流网络过程式生成方法 |
CN107315813A (zh) * | 2017-06-29 | 2017-11-03 | 中国测绘科学研究院 | 一种stroke特征约束的树状河系层次关系构建及简化方法 |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111597732A (zh) * | 2020-06-02 | 2020-08-28 | 中国水利水电科学研究院 | 一种使用汊点影响区水面梯度的河网水流数值模拟方法 |
CN111597732B (zh) * | 2020-06-02 | 2020-12-08 | 中国水利水电科学研究院 | 一种使用汊点影响区水面梯度的河网水流数值模拟方法 |
Also Published As
Publication number | Publication date |
---|---|
CN108255990A (zh) | 2018-07-06 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Wilson et al. | From outcrop to flow simulation: Constructing discrete fracture models from a LIDAR survey | |
CN107917865A (zh) | 一种致密砂岩储层多参数渗透率预测方法 | |
CN107894615B (zh) | 一种定量化评价三维地震属性预测储层参数有效性的方法 | |
CN106842301B (zh) | 一种凝灰质砂岩有利储层的定量识别与预测方法 | |
CN113901681A (zh) | 一种全寿命周期页岩气储层双甜点三维可压性评估方法 | |
WO2019127879A1 (zh) | 一种定量表征不同河型河道砂体的几何参数关系的方法 | |
CN105510993A (zh) | 前陆盆地深埋挤压型复杂膏盐岩层识别和分布预测方法 | |
CN103529474A (zh) | 采用岩性细分实现岩相精细描述的方法 | |
Tan et al. | Quantitative evaluation methods for water-flooded layers of conglomerate reservoir based on well logging data | |
CN111899338B (zh) | 一种覆盖区地层岩性三维建模的方法、装置及系统 | |
CN111239815A (zh) | 基于三维地震属性的砂岩型铀储层成矿沉积要素提取方法 | |
CN109425900A (zh) | 一种地震储层预测方法 | |
Xu et al. | 3D geostatistical modeling of Lascaux hill from ERT data | |
CN106556863A (zh) | 基于深度域叠前角道集的孔隙度预测方法 | |
CN103376468A (zh) | 基于神经网络函数逼近算法的储层参数定量表征方法 | |
Zhang et al. | Multi-parameters logging identifying method for sand body architectures of tight sandstones: A case from the Triassic Chang 9 Member, Longdong area, Ordos Basin, NW China | |
CN103197348B (zh) | 利用各层内部样品进行加权编制测井交会图的方法 | |
CN106842289B (zh) | 一种适用于测井约束反演的波阻抗曲线去压实处理方法 | |
CN115857047B (zh) | 一种地震储层综合预测方法 | |
CN115880455A (zh) | 基于深度学习的三维智能插值方法 | |
CN105888656A (zh) | 一种定量评价天然微裂缝发育致密储层覆压下液测渗透率的方法 | |
Murphy | A geospatial investigation of the potential for inter-aquifer communication in Shelby County, Tennessee: A multi-scale Spatial Dependency Model | |
Li et al. | Three-dimensional reservoir architecture modeling by geostatistical techniques in BD block, Jinhu depression, northern Jiangsu Basin, China | |
Sbiga et al. | Prediction of resistivity index by use of neural networks with different combinations of wireline logs and minimal core data | |
Boateng et al. | Analysis of reservoir heterogeneities and depositional environments: a new method |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 18893795 Country of ref document: EP Kind code of ref document: A1 |