CN102830442A - Evaluation method for potential coefficient used to predict and forecast productivity of coalbed methane - Google Patents
Evaluation method for potential coefficient used to predict and forecast productivity of coalbed methane Download PDFInfo
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Abstract
A kind of potential coefficient evaluation method of prediction Coalbed Methane Productivity, comprising the following steps:
Dominated Factors are determined on coal bed gas well gas production mechanism analysis foundation;
Using GIS powerful data management and spatial analysis functions, the sub- thematic map of each Dominated Factors is established;
Determine each Dominated Factors to the weight contribution of production capacity using ANN;
The Coalbed Methane Productivity potential coefficient evaluation model coupled based on ANN with GIS is established, Coalbed Methane Productivity potential coefficient subregion and evaluation are carried out. Achievement is evaluated according to the Coalbed Methane Productivity Potential Prediction that ANN and GIS are coupled, the Coalbed Methane Productivity Potential Evaluation partition scheme of proposition, it evaluates subregion and actual conditions fitting is preferable, evaluation result and aerogenically matter condition analysis result are almost the same, evaluation effect is ideal, it rationally designs to formulate for block mining scheme and provides important technical basis, compensate for practical be complementary to one another with theory and study inadequate defect.
Description
Technical field
The present invention relates to a kind of Assessment Method on Potential of prediction coal bed gas resource production capacity, especially a kind of potential coefficient evaluation method of prediction coal-seam gas production capacity.
Background technology
The forecast of coal-seam gas production capacity Potential Prediction is the importance that coal bed gas resource is estimated, but because interior zones of different geology of different blocks even same block and hydrogeological condition there are differences, in practice is produced, is difficult on top of; And existing theoretical prediction method distributes to the coal-seam gas production capacity and the nonlinear relationship of various major influence factors is considered not enough.
Summary of the invention
The objective of the invention is to: provide a kind of spatial distribution characteristic that has taken into full account the coal-seam gas production capacity and multiple major influence factors nonlinear relationship, remedied the actual and theoretical potential coefficient evaluation method of the prediction coal-seam gas production capacity of the not enough defective of Supplementary Study each other.
To achieve these goals, the potential coefficient evaluation method of a kind of prediction coal-seam gas of the present invention production capacity is a kind of coal-seam gas production capacity potential coefficient evaluation model based on ANN and GIS coupling, has adopted following technical scheme:
1. on coal bed gas well aerogenesis Analysis on Mechanism basis, confirm Dominated Factors;
2. use powerful data management and the spatial analysis functions of GIS, set up the sub-thematic map of each Dominated Factors;
3. use ANN and confirm the weight contribution of each Dominated Factors production capacity;
4. set up coal-seam gas production capacity potential coefficient evaluation model, carry out coal-seam gas production capacity potential coefficient subregion and evaluation based on ANN and GIS coupling.
Owing to adopted above-mentioned technical scheme, the beneficial effect that the present invention has is:
1. start with from analyzing coal-seam gas enrichment and output mechanism; Quality factor mainly to influencing the coal-seam gas production capacity has carried out analysis-by-synthesis, confirms to influence the principal element of coal-seam gas production capacity potentiality, and the factor of consideration is more comprehensive; These factor interactions influence the size of coal-seam gas production capacity jointly.
2. the coal-seam gas production capacity Potential Prediction evaluation model that is coupled of ANN and GIS; The nonlinear characteristic that can reflect multifactor combined action; Reduced the interference of human factor, used this model coal gas production capacity potentiality are predicted, passed through comparative analysis with actual conditions; Prediction effect is more satisfactory, and row adopts the reference frame that provides certain for actual production.
3. thematic map stack adopts data normalization to handle, and has not only solved the stack difficult problem of different dimension data, and has solved the problem that Dominated Factors and coal-seam gas production capacity are negative correlation, has guaranteed the accuracy that data superpose and the rationality of evaluation model.
4. the coal-seam gas production capacity Potential Prediction that is coupled according to ANN and GIS is estimated achievement; The coal-seam gas production capacity Potential Evaluation partition scheme that proposes; Estimate subregion and actual conditions better fitting, evaluation result and aerogenesis geological condition analysis be basically identical as a result, and evaluation effect is desirable; For block row adopts the formulation of scheme appropriate design the important techniques foundation is provided, has remedied the actual and theoretical not enough defective of Supplementary Study each other.
Description of drawings
Accompanying drawing 1: workflow diagram of the present invention;
Accompanying drawing 2: the sub-thematic map of each Dominated Factors of the present invention;
Accompanying drawing 3: BP network model structural representation of the present invention;
Accompanying drawing 4: production capacity potential coefficient subregion evaluation map of the present invention;
Accompanying drawing 5: coal-seam gas production capacity potential coefficient block plan of the present invention.
Specific embodiment
To combine accompanying drawing below, the present invention described in detail with certain block coal seam.
The potential coefficient evaluation method of a kind of prediction coal-seam gas of the present invention production capacity, the practical implementation technical scheme may further comprise the steps:
1. on coal bed gas well aerogenesis Analysis on Mechanism basis, confirm Dominated Factors;
Described coal bed gas well aerogenesis Analysis on Mechanism comprises: the quality factor mainly of analyzing the coal-seam gas production capacity has reservoir conditions, mode of occurence and output condition;
Described Dominated Factors is meant to comprise the geologic agent of control coal-seam gas production capacity: coal is thick, ash content, permeability, buried depth, top board lithology, tectonic structure, air content, 8 factors of reservoir pressure.
2. use powerful data management and the spatial analysis functions of GIS, set up the sub-thematic map of each Dominated Factors;
The sub-thematic map of described each Dominated Factors comprises:
(1) the thick isogram of coal;
The coal seam reservoirs that thickness is bigger can suppress the diffusion of coal-seam gas on the one hand, so that more coal-seam gas preserves; Coal seam reservoirs thickness also shows on the coal bed gas resource amount the control of coal-seam gas on the other hand, and under the identical condition of other controlling factor, coal bed gas resource amount and coal seam reservoirs thickness are proportional, utilizes the data of collecting to draw the thick isogram of coal, sees accompanying drawing 2a;
(2) ash content isogram;
Coal petrography, ature of coal difference mainly are different through the Different Effects coal-bed gas content of its angry condition and absorption property, are related to the problem such as anger amount and coal seam reservoirs characteristic in coal seam equally; Ash content is significantly as the important parameter of weighing ature of coal for the influence of coal-bed gas content in the coal, utilizes the coal seam ash content data of collecting to draw the ash content isogram, sees accompanying drawing 2b;
(3) permeability isogram;
The permeability in coal seam is the important parameter of the permeance property of gas, water or other fluid in the reflection coal seam; It is one of the most key parameter of coal seam reservoirs evaluation; It directly influences the output speed of coal-seam gas and the aerogenesis course of coal bed gas well; Educate all the more in the crack, and flow-guiding channel is unimpeded more, is beneficial to the output of coal-seam gas more; Therefore, reservoir permeability is significant for coal-seam gas parsing output.The permeability data plotting permeability isogram that well testing obtained that utilization is collected is seen accompanying drawing 2c;
(4) buried depth isogram;
Can a large amount of gases that produce in the incoalation process well be preserved, and depends on the effective depth of burial in coal seam that the structure differentiation causes, and promptly main mining coal seam top board is to the variation of the thickness between Neozoic group's substrate; Effectively depth of burial increases, and the hold capacity of coal-seam gas constantly strengthens, and air content also increases thereupon; Obtain corresponding buried depth data through adding up the composite columnar section of respectively holing, draw the buried depth isogram in view of the above, see accompanying drawing 2d;
(5) top board sandstone thickness isoline figure;
The coal measures that is formed in certain sedimentary system has certain coal seam reservoirs and cap rock syntagmatic, and the lithology difference of country rock is also different for the influence of the capping potentiality of coal seam reservoirs in the various combination.Good capping layer not only can stop the vertical loss of coal-seam gas, keeps the higher reservoir pressure and the adsorbance of coal-seam gas, but also can stop local water vertical alternately, reduce the loss amount of coal gas; Generally speaking, if be mostly fine and close and stable mud stone or the relatively poor tight sand of oozing property of hole, then replacement pressure is high in the top board certain distance, and the capping ability is strong, is good capping layer, and vice versa.Statistics roof sandstone thickness characterizes this layer of roof condition, and the big more expression cap rock condition of sandstone thickness is poor more.Draw isoline figure according to sandstone thickness data in the statistics top board 20m, see accompanying drawing 2e;
(6) structure distribution plan;
Be mainly rift structure and fold for the influential structure of coal-seam gas production capacity.In the folding tectonics, the rock stratum in appressed fold area is barrier layer often, and the gathering and the richness of strong coal-seam gas are deposited; In the mesofold, when sealing condition was better, anticline was high to oblique air content, and when sealing condition was relatively poor, air content was higher to oblique position, and to tiltedly with the alar part of anticline owing to moderate pressure, perviousness is better relatively, is prone to prolific well; For expressing the influence of fold axial region for the coal-seam gas production capacity, it is interior for being unfavorable for the high yield zone to set fold axis 50m scope, and assignment is 0.6; Other zone is 1.0 owing to not receiving fold distribution influence, assignment; According to collecting each fold distribution situation of target block, draw structure distribution plan in the study area, see accompanying drawing 2f;
(7) air content distribution isogram;
As the material base of coal bed gas well high yield, the possibility that the zone that air content is high more obtains high yield is just big more; The principal ingredient of coal-seam gas generally is CH
4, secondly be CO
2, moisture, N
2Deng.For the production capacity potentiality of available gas in the rational and effective prediction coal-seam gas, only add up effective constituent CH in the coal-seam gas
4Content, according to the above-mentioned air content data of collecting, draw air content distribution isogram, see accompanying drawing 2g;
(8) reservoir pressure isogram.
Coal seam reservoirs pressure is meant the hydrodynamic pressure (comprising hydraulic pressure and air pressure) that acts on coal hole-space, crack, so be called pore-fluid pressure again; Coal seam reservoirs pressure and coal seam gas-bearing property are closely related, and the high more coal seam reservoirs that certainly will mean of reservoir pressure has the potentiality of high air content; In addition, the relativeness between it and the adsorbability (particularly critical adsorption pressure) directly influences the complexity of drainage and step-down in the gas production process; The groundwater pressure head height is the immediate data of characterize reservoir pressure, and the general high more reservoir pressure of head is just big more in the simple structure zone; Initial dynamic water level was the direct reflection of reservoir pressure when row adopted, and therefore available row adopts the characterization value of initial dynamic water level as coal seam reservoirs pressure; Collect in the target block scope and arranged on every side and adopted the initial dynamic water level data of well,, draw initial reservoir pressure isogram, see accompanying drawing 2h according to the above-mentioned data of collecting.
3. use ANN and confirm the weight contribution of each Dominated Factors production capacity;
May further comprise the steps:
(1) BP Network Design and training;
According to the relation between coal-seam gas production capacity potential coefficient and the influence factor, to use three layers of BP network and predict that coal-seam gas production capacity potential coefficient is the output of model, this model adopts experience number 2 * (ni+nk)-1, and the hidden layer node is made as 17; The transfer function that to select the tansig function be input layer to hidden layer, hidden layer to output layer; Adopt the trainlm function to train, fast convergence rate, the training error of network is smaller; Maximum training cycle index is 1000, and the objective function error is 0.0001, and step-length is 10; BP network model structure is as shown in Figure 3.
Its training process is: according to the BP network model structure of design, coding; Behind the netinit, call normalized sample data, network is tamed and dociled practice, through after the iteration repeatedly, the network error quadratic sum reaches the requirement of target error.
Training utilizes the test set sample that the ANN network that trains is tested after finishing, if do not reach desired output, then model is unreliable, also need increase typical sample quantity, and training until obtaining desired output, is satisfied examination requirements again.
(2) calculating of each Dominated Factors weight.
1. significant correlation coefficient:
Wherein:
2. the index of correlation:
Wherein:
3. absolute effect coefficient:
In the above-mentioned formula:
is the neural network input block;
=1 ...
;
is the implicit unit of neural network;
=1 ...
;
is the neural network output unit;
=1 ...
;
is the weight coefficient between input neuron
and the hidden layer neuron
,
be the weight coefficient between hidden layer neuron
and the output layer neuron
.
According to three above formula; To the analyzing and processing in addition of the weight between each neuron; Can obtain the decision-making weight coefficient of input factor to the output factor, the absolute effect coefficient S is exactly our desired weight (table 1) that influences each Dominated Factors of coal-seam gas production capacity.
Each Dominated Factors weight coefficient table of table 1
4. coal-seam gas production capacity potential coefficient subregion and evaluation.Comprise:
(1) data normalization;
After each Dominated Factors thematic map is set up, just can set up each factor attribute database and preserve each factor data information; In order to eliminate of the influence of the different dimension data of Dominated Factors, need carry out normalization to data and handle evaluation result:
In formula;
is the data of normalization after handling;
is respectively the lower limit and the upper limit of normalization scope; This paper
gets 0 and 1 respectively;
is the raw data before the normalization, and
and
is respectively the minimum value and the maximal value of each Dominated Factors quantized value;
In the normalization process, must consider the positive negative correlation of each Dominated Factors: in above-mentioned 8 geologic agents that influence coal-seam gas production capacity potentiality to object event; Coal is thick, the size of permeability, buried depth, tectonic structure, air content, reservoir pressure becomes positive relationship with the size of coal-seam gas production capacity potential coefficient, is called the positive correlation factor; And ash content, top board sandstone thickness become reverse relation with the size of coal-seam gas production capacity potential coefficient, be called the negative correlation factor;
For normalized data; Carry out forward to reverse data quantizes; Promptly negative correlation factor positive correlationization; Forward method to the reverse influence factor:
;
is the data after the forwardization, and
is the data after the direct normalization;
Carried out data that above-mentioned normalization handles just with the coal-seam gas production capacity relation of being proportionate;
(2) thematic map complex superposition;
Carry out multifactor fit analysis before, at first must carry out Combined Processing, be combined into an information storage layer to the information storage layer of each related factors, make the information that comprises all correlative factors in the information storage layer that is generated.The essence that complex superposition is handled is exactly to eliminate the synthetic new figure of normalization thematic map registration after dimension to each Dominated Factors, and rebuilds topology and form new topological relation attribute list, and the thematic map after utilizing GIS to each normalization carries out overlap-add procedure.
(3) set up coal-seam gas production capacity potential coefficient method evaluation model;
Setting up coal-seam gas production capacity potential coefficient method evaluation model, in fact is exactly to set up a mathematical model that shows each Dominated Factors effect, and the result of calculation that this model drew can reflect a certain geographic position coal-seam gas production capacity potentiality degree.The foundation of initial physical conceptual model must be with aerogenesis master control geologic agent selected and each factor the contribution mechanism of aerogenesis is the basis.
Production capacity potential coefficient method may be defined as: in a certain grid positions in a certain location in a certain mining area, complex superposition influences each controlling factor of coal-seam gas production capacity, provides its acting in conjunction of each factor and the comprehensive criterion of these grid production capacity potentiality of forming.Available following formula is represented:
Where:
is the capacity of potential coefficient;
as the impact factor weight;
for the first
two main factors that affect the value of the normalized function;
for the geographical coordinates;
is the number of influencing factors.
Can draw this block coal-seam gas production capacity potential coefficient method model thus is:
(4) production capacity potential coefficient subregion is estimated.
According to above-mentioned model; Calculate the coal-seam gas production capacity potential coefficient of each geographical grid; Then it is carried out cumulative frequency histogram (seeing accompanying drawing 4) statistical study, utilization nature stage method is confirmed the subregion threshold value, and this piece coal-seam gas production capacity potential coefficient is divided into 5 sub-areas (seeing accompanying drawing 5):
Relative high-withdrawal area: V >=0.67
Than high-withdrawal area: 0.61≤V＜0.67
Medium producing region: 0.57≤V＜0.61
Low producing region: 0.52≤V＜0.57
Low relatively producing region: 0.42≤V＜0.52.
Claims (8)
1. the potential coefficient evaluation method of a prediction coal-seam gas production capacity, it is characterized in that: the practical implementation technical scheme may further comprise the steps:
2. the potential coefficient evaluation method of a kind of prediction coal-seam gas production capacity according to claim 1; It is characterized in that: described coal bed gas well aerogenesis Analysis on Mechanism comprises: the quality factor mainly of analyzing the coal-seam gas production capacity has reservoir conditions, mode of occurence and output condition;
Described Dominated Factors is meant to comprise the geologic agent of control coal-seam gas production capacity: coal is thick, ash content, permeability, buried depth, top board lithology, tectonic structure, air content, 8 factors of reservoir pressure.
3. the potential coefficient evaluation method of a kind of prediction coal-seam gas production capacity according to claim 1 is characterized in that: the sub-thematic map of described each Dominated Factors comprises:
(1) the thick isogram of coal;
(2) ash content isogram;
(3) permeability isogram;
(4) buried depth isogram;
(5) top board sandstone thickness isoline figure;
(6) structure distribution plan;
(7) air content distribution isogram;
(8) reservoir pressure isogram.
4. the potential coefficient evaluation method of a kind of prediction coal-seam gas production capacity according to claim 1 is characterized in that: described application ANN confirms the weight contribution of each Dominated Factors to production capacity, may further comprise the steps:
(1) BP Network Design and training;
(2) calculating of each Dominated Factors weight.
5. the potential coefficient evaluation method of a kind of prediction coal-seam gas production capacity according to claim 4; It is characterized in that: described BP Network Design is meant according to the relation between coal-seam gas production capacity potential coefficient and the influence factor; Using three layers of BP network predicts; Coal-seam gas production capacity potential coefficient is the output of model, and this model adopts experience number 2 * (ni+nk)-1, and the hidden layer node is made as 17; The transfer function that to select the tansig function be input layer to hidden layer, hidden layer to output layer; Adopt the trainlm function to train; Maximum training cycle index is 1000, and the objective function error is 0.0001, and step-length is 10; The training of described BP network, process is: according to the BP network model structure of design, coding; Behind the netinit, call normalized sample data, network is tamed and dociled practice, through after the iteration repeatedly, the network error quadratic sum reaches the requirement of target error.
6. the potential coefficient evaluation method of a kind of prediction coal-seam gas production capacity according to claim 4 is characterized in that: the calculating of described each Dominated Factors weight comprises:
The calculating of
significant correlation coefficient;
The calculating of
index of correlation;
The calculating of
absolute effect coefficient.
7. the potential coefficient evaluation method of a kind of prediction coal-seam gas production capacity according to claim 1 is characterized in that: described coal-seam gas production capacity potential coefficient subregion and evaluation comprise:
(1) data normalization;
(2) thematic map complex superposition;
(3) set up coal-seam gas production capacity potential coefficient method evaluation model;
(4) production capacity potential coefficient subregion is estimated.
8. the potential coefficient evaluation method of a kind of prediction coal-seam gas production capacity according to claim 7 is characterized in that: described production capacity potential coefficient subregion is estimated, and is that coal-seam gas production capacity potential coefficient is divided into 5 sub-areas:
is than the high-withdrawal area;
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