CN109978374A - Oil-gas pipeline system risk appraisal procedure - Google Patents
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Abstract
The invention discloses oil-gas pipeline system risk appraisal procedures, it include: to obtain third history oil-gas pipeline accident training set, determine the level-one factors causing disaster of each accident, second level factors causing disaster, cope with index, assess parameter and corresponding numerical value, level-one factors causing disaster numerical value is inputted into first nerves network model, obtain the first entry evaluation parameter values, the input reply index value into nervus opticus network model, obtain the second entry evaluation parameter values, with second level factors causing disaster numerical value, first initial assessment parameter values and the first initial assessment parameter values are the input layer of neural network, to assess output layer of the parameter values as neural network, training obtains third nerve network model；According to the practical operation situation of pipeline, using third nerve network model forecast assessment parameter values, and calculation risk value.The present invention is using neural network factors causing disaster, reply index and assesses contacting for parameter, and it is more objective to assess, and assessment is time-consuming short.
Description
Technical field
The present invention relates to a kind of appraisal procedures.It is more particularly related to a kind of oil-gas pipeline system risk assessment
Method.
Background technique
The oil gas conveyed in oil-gas pipeline has the characteristic of inflammable, explosive and easy diffusion, once accident occurs, it would be possible to make
At explosion, fire, environmental pollution, casualties, economic loss.In order to improve safety, the risk of oil-gas pipeline system is commented
Estimate it is very necessary, but existing some appraisal procedures compared with depend on technical staff subjective judgement, it is more difficult to quantify, take a long time.
Therefore, it needs to design a kind of oil-gas pipeline system risk appraisal procedure that can overcome drawbacks described above to a certain degree.
Summary of the invention
It is an object of the present invention to provide a kind of oil-gas pipeline system risk appraisal procedures, utilize neural network
Factors causing disaster copes with index and assesses contacting for parameter, and it is more objective to assess, and assessment is time-consuming short.
In order to realize these purposes and other advantages according to the present invention, oil-gas pipeline system risk assessment side is provided
Method, comprising:
Step 1: determining the level-one factors causing disaster of oil-gas pipeline accident, level-one factors causing disaster is classified, and according to grade
Other size carries out assignment to level-one factors causing disasters at different levels；
Step 2: determining the relevant second level factors causing disaster of level-one factors causing disaster, second level factors causing disaster is classified, and root
According to rank size, assignment is carried out to second level factors causing disasters at different levels；
Step 3: determine the reply index of oil-gas pipeline accident, to should be classified to index, and according to rank size,
To at different levels assignment should be carried out to index；
Step 4: determining the assessment parameter of oil-gas pipeline accident, assessment parameter is classified, and according to rank size,
Assignment is carried out to assessment parameters at different levels, then utilizes assessment parameter definition value-at-risk；
Step 5: obtaining the first history oil-gas pipeline accident training set, level-one factors causing disaster, the assessment ginseng of each accident are determined
Several and corresponding numerical value, using level-one factors causing disaster numerical value as the input layer of neural network, to assess parameter values as neural network
Output layer, training obtain first nerves network model；
Step 6: obtain the second history oil-gas pipeline accident training set, determine each accident reply index, assessment parameter and
Corresponding numerical value, to cope with input layer of the index value as neural network, to assess output layer of the parameter values as neural network,
Training obtains nervus opticus network model；
Step 7: obtaining third history oil-gas pipeline accident training set, determine that the level-one factors causing disaster of each accident, second level cause
Calamity factor, reply index, assessment parameter and corresponding numerical value, level-one factors causing disaster number is inputted into first nerves network model
Value obtains the first entry evaluation parameter values, and into nervus opticus network model, input reply index value, it is preliminary to obtain second
Parameter values are assessed, with second level factors causing disaster numerical value, the first initial assessment parameter values and the first initial assessment parameter values
For the input layer of neural network, to assess output layer of the parameter values as neural network, training obtains third nerve network model；
Step 6: according to the practical operation situation of pipeline, using third nerve network model forecast assessment parameter values, and
Calculation risk value.
Preferably, the oil-gas pipeline system risk appraisal procedure, the level-one factors causing disaster is divided into Pyatyi, described
Second level factors causing disaster and the assessment parameter are divided into nine grades, and the reply index is divided into Pyatyi.
Preferably, the oil-gas pipeline system risk appraisal procedure, to the level-one by way of expert estimation
Factors causing disaster, described should carry out assignment to index and the assessment parameter at the second level factors causing disaster.
Preferably, the oil-gas pipeline system risk appraisal procedure, value-at-risk are to assess the weighted average of parameter,
The weight of assessment parameter is determined by analytic hierarchy process (AHP).
Preferably, the oil-gas pipeline system risk appraisal procedure, the level-one factors causing disaster are maloperation, corrosion
And damage from third-party, the second level factors causing disaster be design maloperation, construction maloperation, operation maloperation, maintenance maloperation,
Pipe material, cathodic protection situation, soil property, service life, buried depth, ground situation, squatter building situation, patrols at anti-corrosion layer status
Line frequency, pipeline are along line index.
Preferably, the oil-gas pipeline system risk appraisal procedure, the reply index include emergency preplan, rescue
Strength, feedback mechanism, public's disasters and prevention, administrative management organization.
Preferably, the oil-gas pipeline system risk appraisal procedure, the assessment parameter includes casualties, property
Loss, production suspension induced losses, social influence and environment influence.
The present invention is include at least the following beneficial effects:
The present invention is using neural network factors causing disaster, reply index and assesses directly contacting for parameter, avoids spending
Long period obtains intermediate parameters, and evaluation process time-consuming is short, in evaluation process the subjective judgement of less dependence technical staff and
Experience, assessment result are relatively objective.The invention firstly uses level-one factors causing disasters and reply index to establish first nerves net respectively
Network model and nervus opticus network model obtain more rough first entry evaluation parameter and the second entry evaluation parameter, then will
First entry evaluation parameter, the second entry evaluation parameter establish third nerve network model together with second level factors causing disaster, with
Three neural network models assess risk, more comprehensively consider factors causing disasters at different levels and reply index in this way, improve
The accuracy of assessment.
Further advantage, target and feature of the invention will be partially reflected by the following instructions, and part will also be by this
The research and practice of invention and be understood by the person skilled in the art.
Specific embodiment
The present invention will be further described in detail below with reference to the embodiments, to enable those skilled in the art referring to specification
Text can be implemented accordingly.
It should be appreciated that such as " having ", "comprising" and " comprising " term used herein do not allot one or more
The presence or addition of a other elements or combinations thereof.
In a kind of technical solution, oil-gas pipeline system risk appraisal procedure, comprising:
Step 1: determining the level-one factors causing disaster of oil-gas pipeline accident, level-one factors causing disaster is classified, and according to grade
Other size carries out assignment to level-one factors causing disasters at different levels；
Step 2: determining the relevant second level factors causing disaster of level-one factors causing disaster, second level factors causing disaster is classified, and root
According to rank size, assignment is carried out to second level factors causing disasters at different levels；
Step 3: determine the reply index of oil-gas pipeline accident, to should be classified to index, and according to rank size,
To at different levels assignment should be carried out to index；
Step 4: determining the assessment parameter of oil-gas pipeline accident, assessment parameter is classified, and according to rank size,
Assignment is carried out to assessment parameters at different levels, then utilizes assessment parameter definition value-at-risk；
Step 5: obtaining the first history oil-gas pipeline accident training set, level-one factors causing disaster, the assessment ginseng of each accident are determined
Several and corresponding numerical value, using level-one factors causing disaster numerical value as the input layer of neural network, to assess parameter values as neural network
Output layer, training obtain first nerves network model；
Step 6: obtain the second history oil-gas pipeline accident training set, determine each accident reply index, assessment parameter and
Corresponding numerical value, to cope with input layer of the index value as neural network, to assess output layer of the parameter values as neural network,
Training obtains nervus opticus network model；
Step 7: obtaining third history oil-gas pipeline accident training set, determine that the level-one factors causing disaster of each accident, second level cause
Calamity factor, reply index, assessment parameter and corresponding numerical value, level-one factors causing disaster number is inputted into first nerves network model
Value obtains the first entry evaluation parameter values, and into nervus opticus network model, input reply index value, it is preliminary to obtain second
Parameter values are assessed, with second level factors causing disaster numerical value, the first initial assessment parameter values and the first initial assessment parameter values
For the input layer of neural network, to assess output layer of the parameter values as neural network, training obtains third nerve network model；
Step 6: according to the practical operation situation of pipeline, using third nerve network model forecast assessment parameter values, and
Calculation risk value.
In the above-mentioned technical solutions, level-one factors causing disaster refers to the factors causing disaster of larger concept, such as maloperation, burn into
Tripartite's destruction etc., second level factors causing disaster is specific factors causing disaster, such as designs maloperation, construction maloperation, operation maloperation, ties up
It protects maloperation, pipe material, anti-corrosion layer status, cathodic protection situation, soil property, service life, buried depth, ground situation, disobey
Situation, line walking frequency, pipeline are built along line index etc..Level-one factors causing disaster often reflects the characteristics of accident on the whole, and two
Grade factors causing disaster often reflects the details of accident, both to consider, could comprehensively reflect and cause calamity reason.Coping with index is
Refer to counter-measure after the accident, counter-measure it is suitable whether will affect the consequence of accident, therefore counter-measure is also necessary
It takes in, such as emergency preplan, rescue strength, feedback mechanism, public's disasters and prevention, administrative management organization etc..Assess parameter
Refer to the assessment to damage sequence, for the extent of damage for the accident of reacting, thus judge the operation risk size of oil-gas pipeline, than
Such as casualties, property loss, production suspension induced losses, social influence and environment influence.Value-at-risk uses number by assessment parameter definition
Relationship gets up value-at-risk and assessment parameter association, can use relevant calculation formula in the prior art or empirical equation.
By level-one factors causing disaster, second level factors causing disaster, assignment should be carried out all in accordance with rank degree size to index and assessment parameter, such as
The corrosion of level-one factors causing disaster is divided into three ranks according to extent of corrosion, is assigned a value of 1,2,3 respectively, the bigger assignment of extent of corrosion is more
It is divided into five ranks, is assigned a value of 1,2,3,4,5 respectively, the poorer tax of emergency preplan
It is worth smaller, for example five ranks is divided into according to the depth of social influence, respectively assignment 1,2,3,4,5, the bigger assignment of social influence
It is bigger.Specifically to the first history oil-gas pipeline accident training set, the second history oil-gas pipeline accident training set and third history oil
Factors causing disaster in feed channel accident training set, reply index and the assignment for assessing parameter, chosen in a vote by multidigit expert or according to
It is empirically determined, and corresponding value-at-risk is calculated accordingly.Respectively with the first history oil-gas pipeline accident training set, the second history oil
The training of feed channel accident training set obtains first nerves network model and nervus opticus network model, according to third history Oil/Gas Pipe
Road accident training set, first nerves network model and nervus opticus network model obtain third nerve network model.In pipeline
In operational process, the numerical value of the input layer of third nerve network model is acquired, calculates assessment ginseng using third nerve network model
Number is vertical, and then obtains value-at-risk, completes the assessment to oil-gas pipeline system risk.Following in neural network model training process
The parameters such as ring number, learning rate, error amount can refer to the prior art.As can be seen that the technical program is built using neural network
Vertical factors causing disaster, reply index and the direct of assessment parameter contact, and avoid taking a long time acquisition intermediate parameters, evaluation process
Time-consuming short, the subjective judgement and experience of less dependence technical staff, assessment result are relatively objective in evaluation process.This technology side
Case establishes first nerves network model and nervus opticus network model first with level-one factors causing disaster and reply index respectively, obtains
More rough first entry evaluation parameter and the second entry evaluation parameter are taken, then tentatively comments the first entry evaluation parameter, second
Estimate parameter and establish third nerve network model together with second level factors causing disaster, risk is commented with third nerve network model
Estimate, more comprehensively considers factors causing disasters at different levels and reply index in this way, improve the accuracy of assessment.
In another technical solution, the oil-gas pipeline system risk appraisal procedure, the level-one factors causing disaster point
For Pyatyi, the second level factors causing disaster and the assessment parameter are divided into nine grades, and the reply index is divided into Pyatyi.Here, it mentions
Factors causing disaster, assessment parameter and the classification for coping with index are supplied, to react the practical feelings of each parameter of accident as precisely as possible
Condition.
In another technical solution, the oil-gas pipeline system risk appraisal procedure, by way of expert estimation
To the level-one factors causing disaster, the second level factors causing disaster, described assignment should be carried out to index and the assessment parameter.Here,
A kind of preferred assignment mode is provided, selects multiple experienced experts to determine the rank of each parameter, and then assignment, compared to master
It sees or empirically determined, more accurately.
In another technical solution, the oil-gas pipeline system risk appraisal procedure, value-at-risk is assessment parameter
Weighted average, the weight for assessing parameter are determined by analytic hierarchy process (AHP).Here there is provided a kind of definition method of value-at-risk, letters
Single easily to calculate, the weight that analytic hierarchy process (AHP) determines is more more acurrate than experience.
In another technical solution, the oil-gas pipeline system risk appraisal procedure, the level-one factors causing disaster is
Maloperation, corrosion and damage from third-party, the second level factors causing disaster be design maloperation, construction maloperation, operation maloperation,
Safeguard maloperation, pipe material, anti-corrosion layer status, cathodic protection situation, soil property, service life, buried depth, ground situation,
Squatter building situation, line walking frequency, pipeline are along line index.Here there is provided preferred level-one factors causing disaster and second level factors causing disaster, one
The characteristics of grade factors causing disaster can reflect accident on the whole, and second level factors causing disaster often reflects the details of accident.
In another technical solution, the oil-gas pipeline system risk appraisal procedure, the reply index includes answering
Anxious prediction scheme, rescue strength, feedback mechanism, public's disasters and prevention, administrative management organization.Index is coped with here there is provided preferred,
Reply situation after accident can be reflected in comprehensively.
In another technical solution, the oil-gas pipeline system risk appraisal procedure, the assessment parameter includes people
Member's injures and deaths, property loss, production suspension induced losses, social influence and environment influence.Here there is provided preferred assessment parameters, can be comprehensively
It is reflected in the loss of accident, preferably to define value-at-risk.
Although the embodiments of the present invention have been disclosed as above, but its is not only in the description and the implementation listed
With it can be fully applied to various fields suitable for the present invention, for those skilled in the art, can be easily
Realize other modification, therefore without departing from the general concept defined in the claims and the equivalent scope, the present invention is simultaneously unlimited
In specific details and embodiment shown and described herein.
Claims (7)
1. oil-gas pipeline system risk appraisal procedure characterized by comprising
Step 1: determining the level-one factors causing disaster of oil-gas pipeline accident, level-one factors causing disaster is classified, and big according to rank
It is small, assignment is carried out to level-one factors causing disasters at different levels；
Step 2: determining the relevant second level factors causing disaster of level-one factors causing disaster, second level factors causing disaster is classified, and according to grade
Other size carries out assignment to second level factors causing disasters at different levels；
Step 3: the reply index of oil-gas pipeline accident is determined, to should be classified to index, and according to rank size, to each
The reply index of rank carries out assignment；
Step 4: determining the assessment parameter of oil-gas pipeline accident, assessment parameter is classified, and according to rank size, to each
The assessment parameter of rank carries out assignment, then utilizes assessment parameter definition value-at-risk；
Step 5: obtain the first history oil-gas pipeline accident training set, determine each accident level-one factors causing disaster, assessment parameter and
Corresponding numerical value, using level-one factors causing disaster numerical value as the input layer of neural network, to assess parameter values as the defeated of neural network
Layer out, training obtain first nerves network model；
Step 6: obtain the second history oil-gas pipeline accident training set, the reply index of each accident, assessment parameter and corresponding are determined
Numerical value, to cope with input layer of the index value as neural network, to assess output layer of the parameter values as neural network, training
Obtain nervus opticus network model；
Step 7: obtain third history oil-gas pipeline accident training set, determine the level-one factors causing disaster of each accident, second level cause calamity because
Element, reply index, assessment parameter and corresponding numerical value, level-one factors causing disaster numerical value is inputted into first nerves network model, is obtained
The first entry evaluation parameter values are obtained, input reply index value, obtains the second entry evaluation into nervus opticus network model
Parameter values are mind with second level factors causing disaster numerical value, the first initial assessment parameter values and the first initial assessment parameter values
Input layer through network, to assess output layer of the parameter values as neural network, training obtains third nerve network model；
Step 6: using third nerve network model forecast assessment parameter values, and being calculated according to the practical operation situation of pipeline
Value-at-risk.
2. oil-gas pipeline system risk appraisal procedure as described in claim 1, which is characterized in that the level-one factors causing disaster point
For Pyatyi, the second level factors causing disaster and the assessment parameter are divided into nine grades, and the reply index is divided into Pyatyi.
3. oil-gas pipeline system risk appraisal procedure as described in claim 1, which is characterized in that by way of expert estimation
To the level-one factors causing disaster, the second level factors causing disaster, described assignment should be carried out to index and the assessment parameter.
4. oil-gas pipeline system risk appraisal procedure as described in claim 1, which is characterized in that value-at-risk is assessment parameter
Weighted average, the weight for assessing parameter are determined by analytic hierarchy process (AHP).
5. oil-gas pipeline system risk appraisal procedure as described in claim 1, which is characterized in that the level-one factors causing disaster is
Maloperation, corrosion and damage from third-party, the second level factors causing disaster be design maloperation, construction maloperation, operation maloperation,
Safeguard maloperation, pipe material, anti-corrosion layer status, cathodic protection situation, soil property, service life, buried depth, ground situation,
Squatter building situation, line walking frequency, pipeline are along line index.
6. oil-gas pipeline system risk appraisal procedure as described in claim 1, which is characterized in that the reply index includes answering
Anxious prediction scheme, rescue strength, feedback mechanism, public's disasters and prevention, administrative management organization.
7. oil-gas pipeline system risk appraisal procedure as described in claim 1, which is characterized in that the assessment parameter includes people
Member's injures and deaths, property loss, production suspension induced losses, social influence and environment influence.
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| CN112053029A (en) * | 2020-07-28 | 2020-12-08 | 中国石油天然气股份有限公司 | Classification and classification method for gas production pipeline management of natural gas field |
| CN112053029B (en) * | 2020-07-28 | 2024-03-08 | 中国石油天然气股份有限公司 | Classification and classification method for natural gas field gas production pipeline management |
| CN115481940A (en) * | 2022-10-31 | 2022-12-16 | 中特检管道工程（北京）有限公司 | Oil and gas pipeline area risk monitoring system based on big data |
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