CN109543973A - The method for seeking unit reserve factor based on probabilistic method - Google Patents
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Abstract
The invention discloses the methods for seeking unit reserve factor based on probabilistic method, comprising the following steps: (a) determines the relevant parameter of unit reserve factor, and the probability Distribution Model f (x) of each relevant parameter is determined by sample point；(b) the probability Distribution Model f (x) of each relevant parameter is brought into unit reserve factor calculation formula, obtains unit reserve factor pdf model f (Ko)；(c) by f (Ko) Integral Transformation at accumulated probability distribution function f (x'), determines unit reserve factor parameter probability valuing.The purpose of the present invention is to provide the methods for seeking unit reserve factor based on probabilistic method, to solve the conventional method of unit reserve factor in the prior art as method of arithmetical average, it is constrained by data point number larger, the problem of area or the apparent area of data distribution difference less to material point will cause biggish statistical error, realize the uncertainty for overcoming traditional parameters static state in parameter calculating, the purpose of precision and validity that high reserves calculate.
Description
Technical field
The present invention relates to reservoir geology fields, and in particular to the method for seeking unit reserve factor based on probabilistic method.
Background technique
Unit reserve factor is also known as reserves closeness, refers to 1Km2It is former containing the ground in area, filled in the oil reservoir of 1m thickness
Ten thousand tonnages of oil, its calculation formula is: Ko=100 Φ Soiρoa/Boi, in which: Ko: crude oil unit reserve factor, 104t/km2·m；
Φ: effecive porosity, f；ρoa, crude oil density in stock tank, g/cm3: Soi: oil saturation, f；Boi: oil volume factor.Single storage system
Number is the reserves of unit oil-gas Layer thickness in unit area, is mainly buried with construction location locating for trap, with oil-gas reservoir
Depth (place layer position) and closely related with the property of oil sources.
In the prior art, due to the difference of different trap exploration degree, to make full use of parameter study achievement and trap sheet
Classification estimation generally is carried out according to the following table according to trap actual conditions when TRAP RESERVE calculates in the parameter information of body:
Herein on basis, existing unit reserve factor calculating parameter mainly takes mean value method to be calculated, and calculates public
Formula are as follows:In the more situation of data point, the calculation method result is more accurate, but is exploring
New district, since drilling data is less, mean value method error is larger, and then influences oil and gas reserves computational accuracy, causes oil gas
Exploration decision validity.
Summary of the invention
The purpose of the present invention is to provide the methods for seeking unit reserve factor based on probabilistic method, to solve single storage in the prior art
The conventional method of coefficient is method of arithmetical average, and larger, the area less to material point or data point are constrained by data point number
The problem of apparent area of cloth difference will cause biggish statistical error, realization overcome traditional parameters static state in parameter calculating
Uncertainty, the purpose of precision and validity that high reserves calculate.
The present invention is achieved through the following technical solutions:
The method for seeking unit reserve factor based on probabilistic method, comprising the following steps:
(a) relevant parameter for determining unit reserve factor determines the probability Distribution Model f (x) of each relevant parameter by sample point；
(b) the probability Distribution Model f (x) of each relevant parameter is brought into unit reserve factor calculation formula, obtains unit reserve factor
Pdf model f (Ko)；
(c) by f (Ko) Integral Transformation at accumulated probability distribution function f (x'), determines unit reserve factor parameter probability valuing P (x'),
Wherein: f (x')=P { X <=x'} (- ∝ < x'< ∝).
Conventional method for unit reserve factor in the prior art is method of arithmetical average, larger by the constraint of data point number,
The problem of area or the apparent area of data distribution difference less to material point will cause biggish statistical error, the present invention mentions
The method for seeking unit reserve factor based on probabilistic method out, this method are determined relevant parameter related with unit reserve factor first, are passed through
Known limited sample point, determines the probability Distribution Model f (x) of each relevant parameter.Again by the probability of each relevant parameter point
Cloth model f (x) is brought into unit reserve factor calculation formula, obtains unit reserve factor pdf model f (Ko), later by f (Ko) integral
It is converted into accumulated probability distribution function f (x'), determines unit reserve factor parameter probability valuing P (x'), in which: f (x')=P { X <=x'}
(- ∝ < x'< ∝).Unit reserve factor parameter probability valuing such as P50And Pmean, thus for geologic objective reserves calculating provide accurately according to
According to.The present invention is by establishing the probability Distribution Model of goal in research, mathematical method and estimation ginseng that reasonably selection target calculates
Number overcomes uncertainty of the traditional parameters static state in parameter calculating, improves the precision and validity of reserves calculating.
Further, the relevant parameter of the unit reserve factor includes effecive porosity Φ, crude oil density in stock tank ρoa, oil-containing it is full
With degree Soi.According to unit reserve factor calculation formula, parameter relevant to unit reserve factor includes effecive porosity Φ, crude oil density in stock tank
ρoa, oil saturation Soi, oil volume factor Boi, wherein oil volume factor is constant, can according to exploration well oil test result early period
It directly to measure, therefore is not included in the relevant parameter of unit reserve factor of the present invention, to reduce calculation amount.
Further, the unit reserve factor pdf model are as follows: f (Ko)=100 × f (φ) × f (Soi)×f(ρoa)/
Boi, in which: f (φ) --- effecive porosity probability Distribution Model；f(Soi) --- oil saturation probability Distribution Model；f
(ρoa) --- crude oil density in stock tank probability Distribution Model；Boi--- oil volume factor.
Preferably, the probability Distribution Model includes normal distribution, logarithm normal distribution, Beta distribution, angular distribution.This
Four kinds of distributed models summarise common probability Distribution Model, can satisfy the foundation of most probability Distribution Models.
When probability Distribution Model is normal distribution,Model parameter value includes mean valueStandard deviation sigma；
When probability Distribution Model is logarithm normal distribution,
Model parameter value includes position L, mean valueStandard deviation sigma；
When probability Distribution Model is that Beta is distributed,Wherein
Model parameter value includes maximum value Max, minimum M in, α, β；
When probability Distribution Model is angular distribution,
WhereinModel parameter value includes maximum value Max, minimum M in, most probable value Likeliest.
Compared with prior art, the present invention having the following advantages and benefits:
The present invention is based on the methods that probabilistic method seeks unit reserve factor to be closed by establishing the probability Distribution Model of goal in research
The mathematical method and estimation parameter that reason ground selection target calculates, it is uncertain in parameter calculating to overcome traditional parameters static state
Property, improve the precision and validity of reserves calculating.
Detailed description of the invention
Attached drawing described herein is used to provide to further understand the embodiment of the present invention, constitutes one of the application
Point, do not constitute the restriction to the embodiment of the present invention.In the accompanying drawings:
Fig. 1 is the flow diagram of the specific embodiment of the invention；
Fig. 2 is effecive porosity probability Distribution Model in the specific embodiment of the invention；
Fig. 3 is oil saturation probability Distribution Model in the specific embodiment of the invention；
Fig. 4 is specific embodiment of the invention Crude Oil density probability distributed model；
Fig. 5 is unit reserve factor pdf model in the specific embodiment of the invention；
Fig. 6 is unit reserve factor probability distribution graph in the specific embodiment of the invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below with reference to embodiment and attached drawing, to this
Invention is described in further detail, and exemplary embodiment of the invention and its explanation for explaining only the invention, are not made
For limitation of the invention.
Embodiment 1:
The method that unit reserve factor is sought based on probabilistic method as shown in Figure 1, comprising the following steps: (a) determines unit reserve factor
Relevant parameter, the probability Distribution Model f (x) of each relevant parameter is determined by sample point；(b) by the probability of each relevant parameter point
Cloth model f (x) is brought into unit reserve factor calculation formula, obtains unit reserve factor pdf model f (Ko)；(c) by f (Ko) integral
It is converted into accumulated probability distribution function f (x'), determines unit reserve factor parameter probability valuing P (x'), in which: f (x')=P { X <=x'}
(- ∝ < x'< ∝).Wherein, the relevant parameter of the unit reserve factor includes effecive porosity Φ, crude oil density in stock tank ρoa, oil-containing
Saturation degree Soi。
Further, the unit reserve factor pdf model are as follows: f (Ko)=100 × f (φ) × f (Soi)×f(ρoa)/
Boi, in which: f (φ) --- effecive porosity probability Distribution Model；f(Soi) --- oil saturation probability Distribution Model；f
(ρoa) --- crude oil density in stock tank probability Distribution Model；Boi--- oil volume factor.
The present embodiment is by taking the calculating of Tahe Oilfield of The Tarim Basin block hole type reservoir unit reserve factor parameter as an example, first
To porosity, oil saturation, oil density and the crude oil body of block Ordovician system hawk mountain group hole type 130 sample points of reservoir
Product coefficient is counted, and following parametric statistics table is obtained:
According to upper table statistical parameter, it is as shown in Fig. 2 to obtain effecive porosity probability Distribution Model, meets α=4.762, β
=129.65 Beta distribution, α, β are brought intoIn, obtain f (φ)；
According to upper table statistical parameter, it is as shown in Fig. 3 to obtain oil saturation probability Distribution Model, meet α=
149.862, β=69.686 Beta distribution, α, β are brought intoIn, obtain f (Soi)；
According to upper table statistical parameter, it is as shown in Fig. 4 to obtain oil density probability Distribution Model, carries out data to sample point
Classified statistic discovery, data distribution concentration degree is high, individual discrete, between whole standard deviation distribution 0.003-0.049, uses triangle
It is more objective that distribution characterizes its probability form, therefore Max, Min, Likeliest are brought into following formula:
By f (φ), f (Soi)、f(ρoa) bring f (K intoo)=100 × f (φ) × f (Soi)×f(ρoa)/BoiIn, obtain single storage
Coefficient pdf model f (Ko) as shown in Fig. 5.
Finally utilize f (x')=P { X <=x'} (- ∝ < x'< ∝), by unit reserve factor pdf model Integral Transformation
At accumulated probability distribution function, unit reserve factor probability distribution graph as shown in Fig. 6 is obtained.Determine that unit reserve factor is general from Fig. 6
Rate value, such as P50=1.3811 and Pmean=1.4766, so that the reserves calculating for geologic objective provides accurate foundation.
Above-described specific embodiment has carried out further the purpose of the present invention, technical scheme and beneficial effects
It is described in detail, it should be understood that being not intended to limit the present invention the foregoing is merely a specific embodiment of the invention
Protection scope, all within the spirits and principles of the present invention, any modification, equivalent substitution, improvement and etc. done should all include
Within protection scope of the present invention.
Claims (5)
1. the method for seeking unit reserve factor based on probabilistic method, which comprises the following steps:
(a) relevant parameter for determining unit reserve factor determines the probability Distribution Model f (x) of each relevant parameter by sample point；
(b) the probability Distribution Model f (x) of each relevant parameter is brought into unit reserve factor calculation formula, obtains unit reserve factor probability
Density model f (Ko)；
(c) by f (Ko) Integral Transformation at accumulated probability distribution function f (x'), determines unit reserve factor parameter probability valuing P (x'), in which: f
(x')=P { X <=x'} (- ∝ < x'< ∝).
2. the method according to claim 1 for seeking unit reserve factor based on probabilistic method, which is characterized in that the unit reserve factor
Relevant parameter include effecive porosity Φ, crude oil density in stock tank ρoa, oil saturation Soi。
3. the method according to claim 1 for seeking unit reserve factor based on probabilistic method, which is characterized in that the unit reserve factor
Pdf model are as follows: f (Ko)=100 × f (φ) × f (Soi)×f(ρoa)/Boi, in which: f (φ) --- effecive porosity is general
Rate distributed model；f(Soi) --- oil saturation probability Distribution Model；f(ρoa) --- crude oil density in stock tank probability distribution mould
Type；Boi--- oil volume factor.
4. the method according to claim 1 for seeking unit reserve factor based on probabilistic method, which is characterized in that the probability distribution
Model includes normal distribution, logarithm normal distribution, Beta distribution, angular distribution.
5. the method according to claim 4 for seeking unit reserve factor based on probabilistic method, it is characterised in that:
When probability Distribution Model is normal distribution,Model parameter value includes mean valueMark
Quasi- difference σ；
When probability Distribution Model is logarithm normal distribution,
Model parameter value includes position L, mean valueStandard deviation sigma；
When probability Distribution Model is that Beta is distributed,WhereinModel ginseng
Number value includes maximum value Max, minimum M in, α, β；
When probability Distribution Model is angular distribution,
WhereinModel parameter value includes maximum value Max, minimum M in, most probable value Likeliest.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130262069A1 (en) * | 2012-03-29 | 2013-10-03 | Platte River Associates, Inc. | Targeted site selection within shale gas basins |
| CN105354404A (en) * | 2014-08-19 | 2016-02-24 | 中国石油化工股份有限公司 | Method for constructing resource quantity parameter distribution model |
| CN107015289A (en) * | 2016-01-28 | 2017-08-04 | 中国石油化工股份有限公司 | Trap evaluation stock number determines method and device |
-
2018
- 2018-11-12 CN CN201811340061.7A patent/CN109543973A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130262069A1 (en) * | 2012-03-29 | 2013-10-03 | Platte River Associates, Inc. | Targeted site selection within shale gas basins |
| CN105354404A (en) * | 2014-08-19 | 2016-02-24 | 中国石油化工股份有限公司 | Method for constructing resource quantity parameter distribution model |
| CN107015289A (en) * | 2016-01-28 | 2017-08-04 | 中国石油化工股份有限公司 | Trap evaluation stock number determines method and device |
Non-Patent Citations (2)
| Title |
|---|
| 张达景 等: "碳酸盐岩油气资源量计算方法——藏控单储系数法", 《石油实验地质》 * |
| 李定军: "概率统计法在储量估算中的应用", 《断块油气田》 * |
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