CN104156617B - For the six stage modeling methods that multilayer sandstone reservoirs gas-bearing formation attribute classification is characterized - Google Patents
For the six stage modeling methods that multilayer sandstone reservoirs gas-bearing formation attribute classification is characterized Download PDFInfo
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Abstract
The invention discloses a kind of modeling method characterized for multilayer sandstone reservoirs gas-bearing formation attribute classification, it is related to a kind of six stages modeling method.The sandwich construction that the present invention is formed around multi-layer steamed bread shape multilayer sandstone reservoirs planar depositions stabilization, longitudinal sand and mud interstratification, propose two schichtenaufbaus modeling, two levels mutually model and four types of reservoir model attributes new method, the six stage modeling method systems that mutually modeling reservoir property modeling gas-bearing formation attribute classification modeling is preserved in stratigraphic structure modeling sand body structural modeling sandbody microfacies modeling are established, the accurate quantitative analysis for realizing multi-layer steamed bread shape multilayer sandstone reservoirs gas-bearing formation quality in three dimensions are characterized.The multilayer sandstone reservoirs gas-bearing formation attribute classification model obtained based on the present invention is more accurate compared with the gas reservoir model built by three traditional stage modeling methods, fine, and be widely used in multilayer sandstone reservoirs mid-later development phase to the balanced exploitation of Classification of Gas Pools in the urgent need to.
Description
Technical field
The present invention relates to a kind of six stages modeling method, and in particular to one kind is used for multilayer sandstone reservoirs gas-bearing formation quality
Six stage modeling methods of sign of classifying.
Background technology
At present, the modeling method not characterized particular for multilayer sandstone reservoirs gas-bearing formation attribute classification also both at home and abroad, is building
During vertical multilayer sandstone reservoirs model, mainly traditional construction modeling-facies modelization-reservoir property modeling that people use
Three stage modeling methods.
Traditional three stage of tectonic sedimentary-reservoir attribute modeling method is used for multilayer sandstone reservoirs gas-bearing formation attribute classification table
The shortcoming levied is embodied in following three aspect：(1) multilayer sandstone reservoirs show as the sandwich construction of sand and mud interstratification, and sand body structure is
One of principal element of gas reservoir fluid distrbution is controlled, but conventional method only focuses on the modeling in stratigraphic structure face, does not account for sand body
Structural modeling；(2) multilayer sandstone reservoirs are typically in shore, Vlei (sea) environment, and sand body plane depositional facies are stable, but by diagenesis
Influence, sandbody microfacies are difficult to correspond with Effective Reservoirs, and conventional method only sets up sandbody microfacies model, do not consider to set up storage
Collection phase model；(3) traditional modeling method only considered the control action of construction and sandbody microfacies to reservoir attribute, it is difficult to realize sand
Body structure and the control action for preserving relative reservoir attribute.As can be seen here, traditional modeling method is the modeling method of extensive style, main
It is applied to the overall situation not high of requirement that multilayer sandstone reservoirs initial stage of development describes precision to gas reservoir.This method is obviously difficult
The higher and higher requirement of precision is described to gas reservoir to adapt to multilayer sandstone reservoirs mid-later development phase.
Belong to the multilayer sandstone reservoirs of shore Vlei (sea) parfacies in China's Qinghai Oil Field, Changqing oilfields, Gas field, Xinjiang
The ground such as oil field, Daqing oil field, Shengli Oil Field extensive development, and this kind of gas reservoir at present mostly had been introduced into exploitation in after
Phase, the pressure of gas reservoir continuously steady production is increasing, and urgent need is employed new technology and realizes characterizing the classification of gas reservoir gas-bearing formation quality, and is passed
The stage of tectonic sedimentary-reservoir attribute three of system is modeled no matter in modeling method, or in the fine degree of modeling result all
It is difficult to meet reality need.Therefore, be badly in need of invention it is a kind of take into full account multilayer sandstone reservoirs feature, while again accurate fine build
Mould new method.
The content of the invention
For not enough present on prior art, the present invention seeks to be to provide a kind of for multilayer sandstone reservoirs gas-bearing formation
The six stage modeling methods that attribute classification is characterized, are modeled-are preserved by stratigraphic structure modeling-sand body structural modeling-sandbody microfacies
The six stage modeling methods that mutually modeling-reservoir property modeling-gas-bearing formation attribute classification is modeled, it is therefore an objective to realize to multi-layer steamed bread shape multilayer
Sandstone reservoirs gas-bearing formation quality is characterized in the accurate quantitative analysis of three dimensions, for multilayer sandstone reservoirs fine description provides technical method branch
Support.
To achieve these goals, the present invention is by a kind of six ranks characterized for multilayer sandstone reservoirs gas-bearing formation attribute classification
The technical scheme of section modeling method realizes that its method and step includes：
(A) two schichtenaufbaus modeling：The general principle of two schichtenaufbaus modeling is shown in formula (1) and (2).First level is ground
Layer construction modeling, using stratum top, bottom surface height above sea level data at the m mouthfuls of well point that classification and correlation is obtained to Wi, pass through
Golden Decided modelling algorithm f in gram, foundation forms stratum top, bottom surface tectonic model S；Second level is sand body structural modeling, according to
The constraint on stratum top, bottom surface S by building up, sand body top, the bottom surface height above sea level at the m mouthfuls of well point obtained with contrast are divided using sand body
Elevation data Wij, by gram in golden Decided modelling algorithm f, foundation forms the n top of sand body, bottom surface tectonic model in stratum
Sj, realize the forecast of distribution of stratum and sand body in three dimensions.
First level：Stratigraphic structure is modeled
Second level：Sand body structural modeling
In formula：F --- it is mapping.
(B) two levels are mutually modeled：The general principle that two levels are mutually modeled is shown in formula (3) and (4).The first order is sandbody microfacies
Modeling, directly using the sandbody microfacies flat distribution map drawn by gram in gold Decided modelling algorithm f set up and to be formed.The second level
Mutually modeled to preserve, input data is the individual well reservoir distribution data obtained by individual well RESERVOIR RECOGNITION, using sequential instruction mould
The stochastic simulation algorithm ff such as plan or indicator Kriging sets up reservoir facies model；During foundation, reservoir facies model is placed in all the time
Under the constraint of sandbody microfacies model so that between well point preserve mutually can only random walk in the spatial domain that sandbody microfacies are limited.
The first order：Sandbody microfacies are modeled
The second level：Preserve and mutually model
In formula：F --- it is mapping；GSF --- the sandbody microfacies distribution map drawn based on geology man is quantized the number to be formed
According to collection；SF --- set up the sandbody microfacies model for being formed；WRE --- individual well preserves phase data collection；RE --- set up the storage for being formed
Collection phase model；M --- well number.
(C) four type attributes modeling：Porosity, three attribute models of gas saturation and permeability are used and preserve phase prosecutor
Method is set up, and general principle is shown in formula (5)；Gas-bearing formation attribute classification attribute is then directly generated by above-mentioned attribute model, general principle
See formula (6).
Preserve phased three model attributes
Gas-bearing formation attribute classification model attributes
In formula：F --- it is mapping；PROPij--- individual well attribute data；Fg --- it is sequence Gauss stochastic simulation algorithm；
RE --- reservoir facies model；MPROPj--- attribute model；Fff --- it is gas-bearing formation categorical attribute parameter and standard；GCLASS——
Gas-bearing formation attribute classification attribute model；J=1 is porosity, and 2 is gas saturation, and 3 is permeability；M --- well number.
Beneficial effects of the present invention：Relatively relied on based on the multilayer sandstone reservoirs gas-bearing formation attribute classification model that the present invention is obtained and passed
The gas reservoir model built of three stage modeling methods of system is more accurate, fine, and after being widely used in the exploitation of multilayer sandstone reservoirs
Phase exploitation balanced to Classification of Gas Pools in the urgent need to.
Brief description of the drawings
Describe the present invention in detail with reference to the accompanying drawings and detailed description；
Fig. 1 is technical flow figure of the invention；
Fig. 2 is that the three-dimensional of certain the multilayer sandstone gas field stratum-layer of sand-sandwich and section structure in the present invention characterizes that (upper left is
The hatching location drawing, upper right is the stratal surface structural map of three dimensions；Main body was that well stratum-layer of sand-sandwich and section structure is cutd open
Face figure)；
Fig. 3 is that certain multilayer sandstone gas field sandbody microfacies of the invention are characterized with the three-dimensional of phase is preserved.((1), (2), (3) point
Not Wei 0-2-2 substratums, 0-2-5 substratums and 0-2-4 substratum sandbody microfacies, (4), (5), that (6) are respectively 0-2-2 substratums, 0-2-3 is small
Layer and 0-2-4 substratums preserve phase.)
Fig. 4 is the three-dimensional sign of the type attribute model of certain multilayer sandstone gas field 0-2-2 substratum gas-bearing formations quality four of the invention
Figure；((1) porosity model, (2) penetration rate model, (3) gas saturation model, (4) gas-bearing formation attribute classification model.)
Fig. 5 is the three-dimensional sign of the type attribute model of certain multilayer sandstone gas field 0-2-3 substratum gas-bearing formations quality four of the invention
((1) porosity model, (2) penetration rate model, (3) gas saturation model, (4) gas-bearing formation attribute classification model)；
Fig. 6 is the three-dimensional sign of the type attribute model of certain multilayer sandstone gas field 0-2-4 substratum gas-bearing formations quality four of the invention.
((1) porosity model, (2) penetration rate model, (3) gas saturation model, (4) gas-bearing formation attribute classification model.)
Specific embodiment
For technological means, creation characteristic, reached purpose and effect for making present invention realization are easy to understand, with reference to
Specific embodiment, is expanded on further the present invention.
Reference picture 1, this specific embodiment uses following technical scheme：The present invention is around multi-layer steamed bread shape multilayer sandstone reservoirs
The sandwich construction that planar depositions stabilization, longitudinal sand and mud interstratification are formed, it is proposed that the modeling of two schichtenaufbaus, two levels are mutually modeled and four
The new approaches of types of reservoir model attributes, establish stratigraphic structure modeling-sand body structural modeling-sandbody microfacies model-preserve phase
In six stages modeling method system (Fig. 1) of modeling-reservoir property modeling-gas-bearing formation attribute classification modeling, realize multi-layer steamed bread shape many
Layer sandstone reservoirs gas-bearing formation quality is characterized in the accurate quantitative analysis of three dimensions.
The general principle of described two schichtenaufbaus modeling is shown in formula (1) and (2).First level is modeled for stratigraphic structure,
Using stratum top, bottom surface height above sea level data at the m mouthfuls of well point that classification and correlation is obtained to Wi, by gram in golden certainty
Modeling algorithm f, foundation forms stratum top, bottom surface tectonic model S；Second level is sand body structural modeling, by the stratum built up
Top, the constraint of bottom surface S, sand body top, the bottom surface height above sea level data W at the m mouthfuls of well point obtained with contrast are divided using sand bodyij,
By gram in golden Decided modelling algorithm f, foundation forms in stratum the n top of sand body, bottom surface tectonic model Sj, realize three-dimensional space
Between middle stratum and sand body forecast of distribution.
First level：Stratigraphic structure is modeled
Second level：Sand body structural modeling
In formula：F --- it is mapping.
Fig. 2 is given certain the multilayer sandstone gas field 0-2-2 completed using two schichtenaufbau modeling methods and (is divided into A, B two
Sand body), the stratigraphic structure of three substratums of 0-2-3 (being divided into tri- sand bodies of A, B, C) and 0-2-4 (being divided into tri- sand bodies of A, B, C) and
Sand body structural modeling achievement.
The general principle that two described levels are mutually modeled is shown in formula (3) and (4).The first order is modeled for sandbody microfacies, directly
Using the sandbody microfacies flat distribution map drawn by gram in gold Decided modelling algorithm f set up and to be formed.The second level is to preserve phase
Modeling, input data is the individual well reservoir distribution data obtained by individual well RESERVOIR RECOGNITION, using Sequential Indicator Simulation or instruction
The stochastic simulation algorithm such as Ke Lijin ff sets up reservoir facies model；During foundation, reservoir facies model is placed in sandbody microfacies all the time
Under the constraint of model so that between well point preserve mutually can only random walk in the spatial domain that sandbody microfacies are limited.
The first order：Sandbody microfacies are modeled
The second level：Preserve and mutually model
In formula：F --- it is mapping；GSF --- the sandbody microfacies distribution map drawn based on geology man is quantized the number to be formed
According to integrating (0 is sand dam as mud bank, 1 as sand waste, 2)；SF --- set up the sandbody microfacies model for being formed；WRE --- individual well preserves phase
Data set (0 is non-reservoir, 1 is reservoir)；RE --- set up the reservoir facies model for being formed；M --- well number.
Fig. 3 gives small by certain multilayer sandstone gas field 0-2-2,0-2-3,0-2-4 of the completion of two level phase modeling methods
The sandbody microfacies model and corresponding reservoir facies model of layer.
The four type attributes modeling of this specific embodiment：
Porosity, three attribute models of gas saturation and permeability are set up using phased method is preserved, and general principle is shown in
Formula (5)；Gas-bearing formation attribute classification attribute is then directly generated by above-mentioned attribute model, and general principle is shown in formula (6).
Preserve phased three model attributes
Gas-bearing formation attribute classification model attributes
In formula：F --- it is mapping；PROPij--- individual well attribute data；Fg --- it is sequence Gauss stochastic simulation algorithm；
RE --- reservoir facies model；MPROPj--- attribute model；Fff --- it is gas-bearing formation categorical attribute parameter and standard；GCLASS——
Gas-bearing formation attribute classification attribute model；J=1 is porosity, and 2 is gas saturation, and 3 is permeability；M --- well number.
Fig. 4-Fig. 6 respectively show using certain multilayer sandstone gas field 0-2-2,0-2-3 and the 0- for preserving phased method foundation
The porosity of 2-4 substratums, gas saturation and penetration rate model, and using Petrochina Qi Nghai Oilfield Company based on hole
Gas field gas-bearing formation attribute classification standard (table 1, Shi Qiang, et al, 2000 of porosity and gas saturation parameter；Ma
Jianhai, 2008；Zhao Yan, et al, 2009), by the gas that porosity model and gas saturation model are directly set up
Layer attribute classification threedimensional model.
Table 1 certain multilayer sandstone gas field gas-bearing formation attribute classification parameter and standard
| Fluid type | POR | Sg | Remarks |
| I class gas-bearing formations | ＞=25% | ＞=60% | Aerobic layer |
| II class gas-bearing formations | 25% ＞ POR ＞=18%% | 60% ＞ Sg ＞=50%% | Medium gas-bearing formation |
| Group III gas-bearing formation | 18% ＞ POR ＞=12% | 60% ＞ Sg ＞=50% | Difference gas-bearing formation |
This specific embodiment is at present in the multilayer of the western Sebei Gas Field of China, Zhong Ba gas fields, Soviet Union's Sulige gas field etc.
Sandstone reservoirs gas-bearing formation attribute classification is applied in characterizing, and brings good economic results in society.
General principle of the invention and principal character and advantages of the present invention has been shown and described above.The technology of the industry
Personnel it should be appreciated that the present invention is not limited to the above embodiments, simply explanation described in above-described embodiment and specification this
The principle of invention, without departing from the spirit and scope of the present invention, various changes and modifications of the present invention are possible, these changes
Change and improvement all fall within the protetion scope of the claimed invention.The claimed scope of the invention by appending claims and its
Equivalent thereof.
Claims (1)
1. the six stage modeling methods that multilayer sandstone reservoirs gas-bearing formation attribute classification is characterized are used for, it is characterised in that its method and step
Including：
(A) two schichtenaufbaus modeling：The general principle of two schichtenaufbaus modeling is shown in formula (1) and (2), and the first level is stratum structure
Modeling is made, using stratum top, bottom surface height above sea level data at the m mouthfuls of well point that classification and correlation is obtained to Wi, by gram in
Golden Decided modelling algorithm f, foundation forms stratum top, bottom surface tectonic model S；Second level is sand body structural modeling, by building
Good stratum top, the constraint of bottom surface tectonic model S, sand body top, the bottom surface at the m mouthfuls of well point obtained with contrast are divided using sand body
Height above sea level data Wij, by gram in golden Decided modelling algorithm f, foundation forms n the top of sand body, bottom surface in stratum and constructs mould
Type Sj, realize the forecast of distribution of stratum and sand body in three dimensions；
First level：Stratigraphic structure is modeled
Second level：Sand body structural modeling
In formula：F --- it is mapping.
(B) two levels are mutually modeled：The general principle that two levels are mutually modeled is shown in formula (3) and (4), and the first order is built for sandbody microfacies
Mould, directly using the sandbody microfacies flat distribution map drawn by gram in gold Decided modelling algorithm f set up and to be formed；The second level is
Preserve and mutually model, input data is the individual well reservoir distribution data obtained by individual well RESERVOIR RECOGNITION, using Sequential Indicator Simulation
Or indicator Kriging stochastic simulation algorithm ff sets up reservoir facies model；During foundation, reservoir facies model is placed in sand body all the time
Under the constraint of microfacies model so that between well point preserve mutually can only random walk in the spatial domain that sandbody microfacies are limited；
The first order：Sandbody microfacies are modeled
The second level：Preserve and mutually model
In formula：F --- it is mapping；GSF --- the sandbody microfacies distribution map drawn based on geology man is quantized the data set to be formed；
SF --- set up the sandbody microfacies model for being formed；WRE --- individual well preserves phase data collection；RE --- that sets up formation preserves phase mould
Type；M --- well number；
(C) four type attributes modeling：Porosity, the three attribute models uses of gas saturation and permeability are preserved phased method and are built
Vertical, general principle is shown in formula (5)；Gas-bearing formation attribute classification attribute model is then directly generated by above-mentioned attribute model, general principle
See formula (6),
Preserve phased three model attributes
Gas-bearing formation attribute classification model attributes
In formula：F --- it is mapping；PROPij--- individual well attribute data；Fg --- it is sequence Gauss stochastic simulation algorithm；
RE --- reservoir facies model；MPROPj--- attribute model；Fff --- it is gas-bearing formation categorical attribute parameter and standard；GCLASS——
Gas-bearing formation attribute classification attribute model；J=1 is porosity, and 2 is gas saturation, and 3 is permeability；M --- well number.
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| CN104747144B (en) * | 2015-02-06 | 2017-02-22 | 中国石油天然气股份有限公司 | Geological stratum selection method based on natural gas multi-stratum series partial pressure combined solution |
| CN109598068B (en) * | 2018-12-06 | 2021-06-18 | 中国石油大学(北京) | Ancient structure constraint modeling method, device and equipment |
| CN114165199A (en) * | 2020-08-20 | 2022-03-11 | 中国石油化工股份有限公司 | Method for laying out and depicting internal interlayer of multi-thin-layer reservoir |
| CN112282751B (en) * | 2020-12-01 | 2022-11-25 | 西南石油大学 | Geological engineering three-dimensional coupling compact oil gas horizontal well exploitation detection method |
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