CN107092032B - A method of utilizing well-log information quantitative assessment coal-bed gas exploitation complexity - Google Patents
A method of utilizing well-log information quantitative assessment coal-bed gas exploitation complexity Download PDFInfo
- Publication number
- CN107092032B CN107092032B CN201710340246.7A CN201710340246A CN107092032B CN 107092032 B CN107092032 B CN 107092032B CN 201710340246 A CN201710340246 A CN 201710340246A CN 107092032 B CN107092032 B CN 107092032B
- Authority
- CN
- China
- Prior art keywords
- coal
- bed gas
- index
- coal seam
- gas exploitation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/40—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
- G01V1/44—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging using generators and receivers in the same well
- G01V1/48—Processing data
- G01V1/50—Analysing data
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/61—Analysis by combining or comparing a seismic data set with other data
- G01V2210/616—Data from specific type of measurement
- G01V2210/6169—Data from specific type of measurement using well-logging
Landscapes
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Acoustics & Sound (AREA)
- Environmental & Geological Engineering (AREA)
- Geology (AREA)
- Remote Sensing (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Solid Fuels And Fuel-Associated Substances (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
A method of using well-log information quantitative assessment coal-bed gas exploitation complexity, first carries out coal bed gas extraction water yield and build coal bed gas extraction water yield prediction model with log parameter correlation analysis：Coal Pore Structure index, the completion qualitative index of prediction of coal reservoir, calculating coal-bed gas exploitation complexity evaluation number are calculated again, it is final to determine that coal-bed gas exploitation complexity evaluation criterion divides the evaluation of coal-bed gas exploitation complexity：The present invention had not only fully considered influence of the mining water yield to coal-bed gas exploitation complexity, but also had taken into account the influence of Coal Pore Structure and completion qualitative index, and the coal-bed gas exploitation complexity evaluated more is coincide with coal-bed gas exploitation practical condition.
Description
Technical field
The present invention relates to the Quantitative Evaluation with Well Logging technologies during coal-bed gas exploitation, more particularly to a kind of to utilize well-log information
The method of quantitative assessment coal-bed gas exploitation complexity.
Background technology
For efficiently exploiting coal bed methane, it is necessary to assess the complexity of coal-bed gas exploitation.In general, coal seam reservoirs pressure
It splits that rear water yield is small, then depressurization desorption is fast, is conducive to output coal bed gas, then coal-bed gas exploitation is relatively easy to；If Coal Pore Structure
For deformation coals such as granulated coal, rotten rib coals, and brittleness index is low, completion qualitative index is small, then difficulty or ease success pressure break, or even coal occurs
Powder blocks the case where fissure channel, then coal gas exploitation difficulty is larger.
By time, both at home and abroad even without the method using well-log information quantitative assessment coal-bed gas exploitation complexity.
In existing achievement in research report, it is limited only to the influence research of mining water yield and coal seam reservoirs compressibility to cbm development.
In fact, coal-bed gas exploitation complexity is not only related with mining water yield, and have with Coal Pore Structure, completion qualitative index
It closes.In existing coal-bed gas exploitation complexity evaluation, coalbed gas logging data is not made full use of even to calculate mining water outlet
Amount, Coal Pore Structure and completion qualitative index, and then to carry out quantitative assessment to coal-bed gas exploitation complexity, this is opened to coal bed gas
Hair is made troubles.
Invention content
In order to overcome the shortcomings of above-mentioned existing method, quantitatively commented using well-log information the purpose of the present invention is to provide a kind of
The method of valence coal-bed gas exploitation complexity is based on coal bed gas extraction water yield, Coal Pore Structure and completion qualitative index, establishes
Coal-bed gas exploitation complexity quantitative evalution model and standard draw coal-bed gas exploitation complexity with this evaluation criterion
Point, technical support will be provided for coal bed gas Efficient Development.
In order to achieve the above object, the technical scheme is that：
A method of using well-log information quantitative assessment coal-bed gas exploitation complexity, include the following steps：
Step 1: coal bed gas extraction water yield and log parameter correlation analysis：Utilize log parameter and practical coal bed gas
Mining water yield carries out correlation analysis, filters out the more sensitive log parameter of coal bed gas extraction water yield；
Step 2: structure coal bed gas extraction water yield prediction model：Based on step 1 it is found that the water outlet of coal bed gas roof and floor
Amount has good correlation with sandstone thickness, porosity and sandstone away from coal seam distance, accordingly, constructs following Seam Roof And Floor
Water yield prediction model：
In formula：QwtbFor coal bed gas extraction water yield, m3/d；HtbFor adjoining rock thickness, m；Φ is sandstone pores
Degree, %；S is distance of the sandstone away from coal seam, m；W1、W2、W3To be respectively sandstone thickness, porosity and sandstone away from coal seam distance
Weight coefficient, dimensionless.
It is studied it is found that density, interval transit time, resistivity and coal seam thickness by coal seam mining itself water yield responsive parameter
It is more close with coal seam water outlet magnitude relation, then, coal seam itself mining water yield shown in formula (2) is constructed using this group of parameter
Prediction model：
Qwc=-7.518-0.375 × ρb+0.021×Δt-0.184×log(Rt)+0.128×Hc R2=0.739 (2)
In formula：QwcFor coal seam itself mining water yield, m3/d；ρbFor the bulk density in coal seam, g/cm3；Δ t is coal seam
Interval transit time, μ s/m；Rt is the resistivity in coal seam, Ω .m；HcFor the thickness in coal seam, m；Other parameters dimension is the same；
Based on Seam Roof And Floor and itself mining water yield, coal bed gas extraction water yield shown in equation (3) can be obtained.
QW=Qwtb+Qwc (3)
In formula：QWFor total mining water yield, m3/d；Other parameters dimension is the same；
Step 3: calculating Coal Pore Structure index：The integrity factor in coal seam can reflect Coal Pore Structure to a certain extent,
Then integrity factor is introduced when building Coal Pore Structure index computation model, accordingly, Coal Pore Structure refers to shown in definition (4)
Number well logging computation model.
In formula：ICSFor Coal Pore Structure index, dimensionless；KvFor the integrity factor in coal seam, dimensionless；VpFor the vertical of rock mass
Wave sound speed can be replaced, m/s with well logging longitudinal wave velocity；VrFor the theoretical longitudinal wave velocity of rock matrix, m/s；Other parameters dimension is same
Before；
Coal Pore Structure index ICSIt is bigger, show that coal petrography more levels off to primary structure coal；Coal Pore Structure index ICSIt is smaller, table
Bright coal petrography more levels off to granulated coal and rotten rib coal.
Step 4: the completion qualitative index of prediction of coal reservoir：Poisson's ratio reflects energy to fracture of the coal petrography under stress
Power, and elasticity modulus reflects the enabling capabilities after coal petrography rupture, elasticity modulus is higher, Poisson's ratio is lower, and the brittleness of coal petrography is got over
By force, then, the brittleness index of coal petrography is calculated using formula (6)~formula (8).
In formula：IBE、IBμThe brittleness index that respectively Young's modulus and Poisson's ratio method calculate, %；IBRefer to for the brittleness in coal seam
Number, %；E be coal seam Young's modulus, 104MPa；μ is the Poisson's ratio in coal seam；Δt,ΔtsFor the P-wave And S time difference in coal seam, μ s/
m；Other parameters physical significance is the same；
With the Young's modulus of the longitudinal and shear wave time difference and density log material computation compared with the Young's modulus of rock matrix relatively come
The development degree of micro cracks in oil in coal seam is characterized, shown in development degree of micro cracks in oil index computation model such as equation (11)：
In formula：RFFor the fracture development index in coal seam；EtmaFor the Young's modulus value in free from flaw coal seam, MPa；Other parameters
Dimension is as previously shown；
Shown in coal seam and the horizontal deviator stress accounting equation of roof and floor interlayer such as formula (12).
Δ σ=σs-σc (12)
In formula：Ground stress deviations of the Δ σ between coal seam and its roof and floor, MPa；σsFor the minimum horizontal principal stress of roof and floor,
MPa；σcFor the minimum horizontal principal stress in coal seam, MPa；σvFor vertical crustal stress, MPa；A is Biot coefficients, dimensionless；PpFor ground
Layer pore pressure, MPa；β is tectonic stress coefficient, dimensionless；Other parameters dimension is as previously shown；
Horizontal stress coefficient of variation inside coal seam is calculated using equation (14)：
In formula：KHFor the different coefficient of the horizontal deviator stress in coal seam, dimensionless；σ1For the maximum horizontal principal stress in coal seam, MPa；σ2
For the minimum horizontal principal stress in coal seam, MPa.
Conducive to the brittleness index in coal seam, fracture development coefficient, interlayer ground stress deviation and horizontal stress coefficient of variation, construct
Completion qualitative index prediction model in coal seam shown in equation (15)：
In formula：ICPFor coal seam completion qualitative index, dimensionless；Other parameters dimension is as previously shown.
Step 5: calculating coal-bed gas exploitation complexity evaluation number：Based on going out for the calculating in step 2~step 4
Water, Coal Pore Structure index and completion qualitative index, after being normalized, it is contemplated that 1m has 8 well logging hits
The influence at strong point, coal seam thickness and roof and floor thickness, and in view of water content increase can increase coal-bed gas exploitation difficulty, coal body knot
It is easy to successfully pressure break when structure index and high completion qualitative index value, constructs coal-bed gas exploitation complexity shown in equation (16)
The quantitative calculation of evaluation number：
In formula：IERFor coal-bed gas exploitation complexity evaluation number, dimensionless；I is that log data to be calculated is counted, nothing
Dimension；ICSN、ICPN、QWNCoal Pore Structure index, completion qualitative index and mining water yield after respectively normalizing, dimensionless；
Step 6: determining coal-bed gas exploitation complexity evaluation criterion：It is difficult according to the coal-bed gas exploitation calculated in step 5
Easy degree evaluation exponential quantity gives coal bed gas shown in table 1 and opens on the basis of system coal seam correlation gas actual development data
Adopt complexity grading standard：
1 coal-bed gas exploitation complexity opinion rating of table divides table
| Coal-bed gas exploitation difficulty type | Coal-bed gas exploitation complexity index IER |
| Easily | IER> 0.8 |
| It is easier to | 0.6<IER≤0.8 |
| It is more difficult | 0.4<IER≤0.6 |
| It is difficult | IER≤0.4 |
Step 7: coal-bed gas exploitation complexity is evaluated：Based on the coal-bed gas exploitation difficulty or ease journey in step 2~step 4
Each evaluation index computation model is spent, on the basis of Directorate Of Organization manages interpretive program, calculates water yield, Coal Pore Structure index and complete
Well qualitative index, and then the model in Utilization plan five calculates coal-bed gas exploitation complexity evaluation number, last foundation side
Coal-bed gas exploitation complexity evaluation criterion shown in case six determines evaluated coal-bed gas exploitation complexity evaluation.
The present invention is directed to coal-bed gas exploitation complexity for the first time, it is proposed that a kind of quantitative assessment coal-bed gas exploitation complexity
Method, well-log information can be effectively utilized, three indexs of coal-bed gas exploitation complexity are calculated, to be coal seam
Gas exploitation provides borehole logging technical support, has both fully considered influence of the mining water yield to coal-bed gas exploitation complexity,
The influence for having taken into account Coal Pore Structure and completion qualitative index again, the coal-bed gas exploitation complexity evaluated are real with coal-bed gas exploitation
The border condition of production is more coincide.
Description of the drawings
Fig. 1 is the quantitative assessment coal-bed gas exploitation complexity method flow diagram in the present invention.
Fig. 2 is relational graph between the coal bed gas water yield per day in the present invention and sandstone thickness.
Fig. 3 is the coal bed gas water yield per day in the present invention and sandstone away from relational graph between the distance of coal seam.
Fig. 4 is relational graph between coal bed gas water yield per day and porosity in the present invention.
Fig. 5 is relational graph between coal seam itself water yield per day in the present invention and density.
Fig. 6 is relational graph between coal seam itself water yield per day in the present invention and interval transit time.
Fig. 7 is relational graph between coal seam itself water yield per day in the present invention and resistivity.
Fig. 8 is relational graph between coal seam itself water yield per day in the present invention and coal seam thickness.
Fig. 9 is the hole diameter and resistivity cross plot of the identification Coal Pore Structure in the present invention.
Figure 10 is the density and interval transit time cross plot of the identification Coal Pore Structure in the present invention.
Figure 11 is the coal-bed gas exploitation complexity quantitative assessment result map in the present invention.
Specific implementation mode
Technical scheme of the present invention is described in detail below in conjunction with the accompanying drawings.
Referring to Fig.1, a kind of evaluation method of quantitative assessment coal-bed gas exploitation complexity, includes the following steps：
Step 1: coal bed gas extraction water yield and log parameter correlation analysis：When the direct roof and floor in coal seam is sandstone, object
Property it is preferable, and sandstone thickness is bigger, then the property of water-bearing of roof and floor sandstone is stronger, the mining water outlet of roof and floor sandstone after coal bed fracturing
It measures larger.Mapping ability of the Geophysical Logging to coal bed gas extraction water yield is fully taken into account, from roof and floor and coal seam
Itself two aspect carries out water yield analysis.With reference to Fig. 2~Fig. 5, using sandstone thickness, sandstone away from coal seam distance and porosity and day
Water yield correlation analysis learns that the sensitivity to parameter such as mining water yield per day and sandstone thickness, porosity are stronger, then utilizes this
Group parameter is come the water yield prediction model of adjoining rock when building mining.With reference to Fig. 6~Fig. 9, the density in coal seam, sound wave are utilized
The time difference and the correlation analysis of resistivity and coal seam thickness and water yield per day learn that interval transit time and coal seam thickness are discharged with coal seam
Magnitude relation is more close, and coal seam bulk density and resistivity also have certain sensibility to the coal seam property of water-bearing, therefore utilizing should
Parameter is organized to build the water yield prediction model in coal seam itself.
Step 2: structure coal bed gas extraction water yield prediction model：Based on step 1 it is found that the water outlet of coal bed gas roof and floor
Amount has good correlation with sandstone thickness, porosity and sandstone away from coal seam distance.Accordingly, following Seam Roof And Floor is constructed
Water yield prediction model：
In formula：QwtbFor coal bed gas extraction water yield, m3/d；HtbFor the thickness of adjoining rock, m；Φ is sandstone pores
Degree, %；S is distance of the sandstone away from coal seam, m；W1、W2、W3To be respectively sandstone thickness, porosity and sandstone away from coal seam distance
Weight coefficient, dimensionless.
It is learnt by step 1, density, interval transit time, resistivity and coal seam thickness and coal seam water outlet magnitude relation are more close,
Then, coal seam itself the mining water yield prediction model as shown in formula (2) is constructed using this group of parameter.
Qwc=-7.518-0.375 × ρb+0.021×Δt-0.184×log(Rt)+0.128×Hc R2=0.739 (2)
In formula：QwcFor coal seam itself mining water yield, m3/d；ρbFor the bulk density in coal seam, g/cm3；Δ t is coal seam
Interval transit time, μ s/m；Rt is the resistivity in coal seam, Ω .m；HcFor the thickness in coal seam, m；Other parameters dimension is the same.
Based on Seam Roof And Floor and itself mining water yield, coal bed gas extraction water yield shown in equation (3) can be obtained.
QW=Qwtb+Qwc (3)
In formula：QWFor total mining water yield, m3/d；Other parameters dimension is the same.
Step 3: calculating Coal Pore Structure index：Deformation coal mechanical strength is low, Coal Pore Structure is loose, is unable to brittle cracking, in
It is to be difficult to form crack.While forming slotted wall when pressure break, a large amount of coal dusts that these calvings are peeled off can block seam, and then cause
The permeance property in coal seam cannot improve.Referring to Fig.1 0, Figure 11, the resistivity curve of primary structure coal generally in amplitude,
Density is high level, interval transit time is low value；And the density of deformation coal reduces, resistivity is middle low value, interval transit time increase.Pass through
System dissects the logging response character of the primary structure coal in research area, fragmentation coal, granulated coal and rotten rib coal, finds with coal body knot
Structure is reduced from primary structure coal to rotten rib coal transition, density log value and resistivity value, and interval transit time and hole diameter increase.Due to
Resistivity, density and interval transit time are influenced by expanding, can not when then building Coal Pore Structure index Logging estimation model
This parameter of introducing hole diameter.The integrity factor in coal seam can reflect Coal Pore Structure to a certain extent, then in structure coal body
Integrity factor is introduced when structure index computation model.Accordingly, Coal Pore Structure index shown in definition (4).
In formula：ICSFor Coal Pore Structure index, dimensionless；KvFor the integrity factor in coal seam, dimensionless；VpFor the vertical of rock mass
Wave sound speed can be replaced, m/s with well logging longitudinal wave velocity；VrFor the theoretical longitudinal wave velocity of rock matrix, m/s；Other parameters dimension is same
Before.
Coal Pore Structure index ICSIt is bigger, show that coal petrography more levels off to primary structure coal；Coal Pore Structure index ICSIt is smaller, table
Bright coal petrography more levels off to granulated coal and rotten rib coal.
Step 4: the completion qualitative index of prediction of coal reservoir：Poisson's ratio reflects energy to fracture of the coal petrography under stress
Power, and elasticity modulus reflects the enabling capabilities after coal petrography rupture.Elasticity modulus is higher, Poisson's ratio is lower, and the brittleness of coal petrography is got over
By force.Then, the brittleness index of coal petrography is calculated using formula (6)~formula (8).
In formula：IBE、IBμThe brittleness index that respectively Young's modulus and Poisson's ratio method calculate, %；IBRefer to for the brittleness in coal seam
Number, %；E be coal seam Young's modulus, 104MPa；μ is the Poisson's ratio in coal seam；Δt,ΔtsFor the P-wave And S time difference in coal seam, μ s/
m；Other parameters physical significance is the same.
With the Young's modulus of the longitudinal and shear wave time difference and density log material computation compared with the Young's modulus of rock matrix relatively come
Characterize the development degree of micro cracks in oil in coal seam.Shown in development degree of micro cracks in oil index computation model such as equation (11).
In formula：RFFor the fracture development index in coal seam；EtmaFor the Young's modulus value of free from flaw rock, MPa；Other parameters
Dimension is as previously shown.
Shown in coal seam and the horizontal deviator stress accounting equation of roof and floor interlayer such as formula (12).
Δ σ=σs-σc (12)
In formula：Ground stress deviations of the Δ σ between coal seam and its roof and floor, MPa；σsFor the minimum horizontal principal stress of roof and floor,
MPa；σcFor the minimum horizontal principal stress in coal seam, MPa；σvFor vertical crustal stress, MPa；A is Biot coefficients, dimensionless；PpFor ground
Layer pore pressure, MPa；β is tectonic stress coefficient, dimensionless；Other parameters dimension is as previously shown.
Horizontal stress coefficient of variation inside coal seam is calculated using equation (14).
In formula：KHFor the different coefficient of the horizontal deviator stress in coal seam, dimensionless；σ1For the maximum horizontal principal stress in coal seam, MPa；σ2
For the minimum horizontal principal stress in coal seam, MPa.
Coal seam reservoirs fracturing effect is directly proportional to the brittleness index in coal seam, development degree of micro cracks in oil；Between coal seam and its roof and floor
When ground stress deviation is larger, pressure-break is easily controllable inside coal seam, without linking up roof and floor water-bearing layer；Coal seam horizontal principal stress
Coefficient of variation is smaller, and pressure break is to be easy to form complicated chicken-wire cracking inside coal seam, and then be conducive to coal seam drainage and step-down.It is based on
The understanding is conducive to brittleness index, fracture development coefficient, interlayer ground stress deviation and the horizontal stress coefficient of variation in coal seam, constructs
Completion qualitative index prediction model in coal seam shown in equation (15).
In formula：ICPFor coal seam completion qualitative index, dimensionless；Other parameters dimension is as previously shown.
Step 5: calculating coal-bed gas exploitation complexity evaluation number：Based on going out for the calculating in step 2~step 4
Water, Coal Pore Structure index and completion qualitative index, after being normalized, it is contemplated that 1m has 8 well logging hits
The influence at strong point, coal seam thickness and roof and floor thickness, and in view of water content increase can increase coal-bed gas exploitation difficulty, coal body knot
It is easy to successfully pressure break when structure index and high completion qualitative index value, constructs coal-bed gas exploitation complexity shown in equation (16)
The quantitative calculation of evaluation number：
In formula：IERFor coal-bed gas exploitation complexity evaluation number, dimensionless；I is that log data to be calculated is counted, nothing
Dimension；ICSN、ICPN、QWNCoal Pore Structure index, completion qualitative index and mining water yield after respectively normalizing, dimensionless.
Step 6: determining coal-bed gas exploitation complexity evaluation criterion：It is difficult according to the coal-bed gas exploitation calculated in step 5
Easy degree evaluation exponential quantity gives coal bed gas shown in table 1 and opens on the basis of system coal seam correlation gas actual development data
Adopt complexity grading standard：
1 coal-bed gas exploitation complexity opinion rating of table divides table
| Coal-bed gas exploitation difficulty type | Coal-bed gas exploitation complexity index IER |
| Easily | IER> 0.8 |
| It is easier to | 0.6<IER≤0.8 |
| It is more difficult | 0.4<IER≤0.6 |
| It is difficult | IER≤0.4 |
Step 7: coal-bed gas exploitation complexity is evaluated：Based on the coal-bed gas exploitation difficulty or ease journey in step 2~step 4
Each evaluation index computation model is spent, on the basis of Directorate Of Organization manages interpretive program, calculates water yield, Coal Pore Structure index and complete
Well qualitative index, and then the model in Utilization plan five calculates coal-bed gas exploitation complexity evaluation number, last foundation side
Coal-bed gas exploitation complexity evaluation criterion shown in case six determines evaluated coal-bed gas exploitation complexity evaluation.
The present invention is tried out in practical coalfield.In the application of the quantitative assessment coal-bed gas exploitation complexity of X wells, ginseng
According to Figure 11, well main force coalbed methane reservoir section 573.5-577.4m, thickness 3.9m, without apparent dirt band in layer.The coal bed gas is stored up
Layer top 573.5-576.0m well sections, log show that coal quality is preferable, and coal core analysis air content is 8.9~19.4m3/ t,
It is shown to be Enriching Coalbed Methane well section.However, Coal Pore Structure index, the completion qualitative index that the coal seam section calculates are smaller, well logging
The water yield per day of prediction is higher, and the coal-bed gas exploitation complexity index calculated using the invention the method is between 0.4~0.6
Between, show that the well section is difficult to exploiting coal bed methane.In actual production, pressure break is carried out to the coal seam section, but three are drained after pressure break
Wheat harvesting period outlet not yet.Fracturing effect monitors and mining dynamic shows the coal seam section due to completion poor quality, pressing crack construction process
A large amount of coal dusts that middle calving is peeled off plug seam.The coalbed methane reservoir lower part 576.0-577.4m well sections, fixed carbon is in content
It is relatively low, content of ashes is higher, the air content of calculating of logging well is 6.3-10.2m3/ t, coalbed methane reservoir quality are relatively poor；But it should
Coal seam section Coal Pore Structure index, completion qualitative index are high compared with superjacent section, and the water yield per day of prediction is relatively low, utilizes the hair
The coal-bed gas exploitation complexity index that bright the method calculates is more than 0.8, shows that the well section is easy to exploiting coal bed methane.On top
After the failure of coal seam section pressure break, pressure break is carried out to the lower coal interval again, after being drained more than 20 days after pressing crack construction, daily gas 873
Side.This absolutely proves that the coal-bed gas exploitation complexity of this research quantitative assessment is more coincide with actual production feature.
This method had not only fully considered influence of the mining water yield to coal-bed gas exploitation complexity, but also had taken into account coal body knot
The influence of structure, completion qualitative index, the coal-bed gas exploitation complexity evaluated more are coincide with coal bed gas practical condition.
Each evaluation index in the method can be sought from coalfield borehole logging data, and almost all of coalfield all has largely
Borehole logging data.Therefore, coal-bed gas exploitation complexity Quantitative Evaluation with Well Logging method of the present invention has good push away
Wide application prospect and value.
It will be understood by those of skill in the art that since well-log information is easily influenced by expanding equal borehole environments, in order to more
The complexity for accurately evaluating coal-bed gas exploitation, it is very necessary, and complete to carry out the correction method of surroundings effecting to its well-log information
Involved rock mechanics parameters have to pass through dynamic static conversion in the evaluation of well qualitative index, and coal-bed gas exploitation complexity is quantitative
Evaluation result just has higher precision.
Claims (1)
1. a kind of method using well-log information quantitative assessment coal-bed gas exploitation complexity, which is characterized in that including following step
Suddenly：
Step 1: coal bed gas extraction water yield and log parameter correlation analysis：Utilize log parameter and practical coal bed gas extraction
Water yield carries out correlation analysis, filters out the more sensitive log parameter of coal bed gas extraction water yield；
Step 2: structure coal bed gas extraction water yield prediction model：Based on step 1 it is found that the water yield of coal bed gas roof and floor with
Sandstone thickness, porosity and sandstone have good correlation away from coal seam distance, accordingly, construct following Seam Roof And Floor water outlet
Measure prediction model：
In formula：QwtbFor coal bed gas extraction water yield, m3/d；HtbFor adjoining rock thickness, m；Φ is sandstone porosity, %；S
For distance of the sandstone away from coal seam, m；W1、W2、W3To be respectively the weight coefficient of sandstone thickness, porosity and sandstone away from coal seam distance,
Dimensionless；
It is studied it is found that density, interval transit time, resistivity and coal seam thickness and coal by coal seam mining itself water yield responsive parameter
Layer water outlet magnitude relation is more close, then, constructs coal seam itself mining water yield shown in formula (2) using this group of parameter and predicts
Model：
Qwc=-7.518-0.375 × ρb+0.021×Δt-0.184×log(Rt)+0.128×Hc R2=0.739 (2)
In formula：QwcFor coal seam itself mining water yield, m3/d；ρbFor the bulk density in coal seam, g/cm3；Δ t is the sound wave in coal seam
The time difference, μ s/m；Rt is the resistivity in coal seam, Ω .m；HcFor the thickness in coal seam, m；Other parameters dimension is the same；
Based on Seam Roof And Floor and itself mining water yield, coal bed gas extraction water yield shown in equation (3) can be obtained；
QW=Qwtb+Qwc (3)
In formula：QWFor total mining water yield, m3/d；Other parameters dimension is the same；
Step 3: calculating Coal Pore Structure index：The integrity factor in coal seam can reflect Coal Pore Structure to a certain extent, then
Integrity factor is introduced when building Coal Pore Structure index computation model, accordingly, Coal Pore Structure index shown in definition (4) is surveyed
Well computation model；
In formula：ICSFor Coal Pore Structure index, dimensionless；KvFor the integrity factor in coal seam, dimensionless；VpFor the longitudinal wave sound of rock mass
Speed can be replaced, m/s with well logging longitudinal wave velocity；VrFor the theoretical longitudinal wave velocity of rock matrix, m/s；Other parameters dimension is the same；
Coal Pore Structure index ICSIt is bigger, show that coal petrography more levels off to primary structure coal；Coal Pore Structure index ICSIt is smaller, show coal petrography
More level off to granulated coal and rotten rib coal；
Step 4: the completion qualitative index of prediction of coal reservoir：Poisson's ratio reflects breakage of the coal petrography under stress, and
Elasticity modulus reflects the enabling capabilities after coal petrography rupture, and elasticity modulus is higher, Poisson's ratio is lower, and the brittleness of coal petrography is stronger, in
It is that the brittleness index of coal petrography is calculated using formula (6)~formula (8)；
In formula：IBE、IBμThe brittleness index that respectively Young's modulus and Poisson's ratio method calculate, %；IBRefer to for the brittleness in coal seam
Number, %；E be coal seam Young's modulus, 104MPa；μ is the Poisson's ratio in coal seam；Δt,ΔtsFor the P-wave And S time difference in coal seam, μ s/
m；Other parameters physical significance is the same；
It is relatively characterized compared with the Young's modulus of rock matrix with the Young's modulus of the longitudinal and shear wave time difference and density log material computation
The development degree of micro cracks in oil in coal seam, shown in development degree of micro cracks in oil index computation model such as equation (11)：
In formula：RFFor the fracture development index in coal seam；EtmaFor the Young's modulus value in free from flaw coal seam, MPa；Other parameters dimension is such as
Shown in preceding；
Shown in coal seam and the horizontal deviator stress accounting equation of roof and floor interlayer such as formula (12)；
Δ σ=σs-σc (12)
In formula：Ground stress deviations of the Δ σ between coal seam and its roof and floor, MPa；σsFor the minimum horizontal principal stress of roof and floor, MPa；σc
For the minimum horizontal principal stress in coal seam, MPa；σvFor vertical crustal stress, MPa；α is Biot coefficients, dimensionless；PpFor formation pore
Pressure, MPa；β is tectonic stress coefficient, dimensionless；Other parameters dimension is as previously shown；
Horizontal stress coefficient of variation inside coal seam is calculated using equation (14)：
In formula：KHFor the different coefficient of the horizontal deviator stress in coal seam, dimensionless；σ1For the maximum horizontal principal stress in coal seam, MPa；σ2For coal
The minimum horizontal principal stress of layer, MPa；
Conducive to the brittleness index in coal seam, fracture development coefficient, interlayer ground stress deviation and horizontal stress coefficient of variation, equation is constructed
(15) completion qualitative index prediction model in coal seam shown in：
In formula：ICPFor coal seam completion qualitative index, dimensionless；Other parameters dimension is as previously shown；
Step 5: calculating coal-bed gas exploitation complexity evaluation number：Water yield based on the calculating in step 2~step 4,
Coal Pore Structure index and completion qualitative index, after being normalized, it is contemplated that 1m have 8 well logging sampled data points,
The influence of coal seam thickness and roof and floor thickness, and in view of water content increase can increase coal-bed gas exploitation difficulty, Coal Pore Structure refers to
Number and completion qualitative index value are easy to successfully pressure break when high, construct coal-bed gas exploitation complexity shown in equation (16) and evaluate
The quantitative calculation of index：
In formula：IERFor coal-bed gas exploitation complexity evaluation number, dimensionless；I is that log data to be calculated is counted, immeasurable
Guiding principle；ICSN、ICPN、QWNCoal Pore Structure index, completion qualitative index and mining water yield after respectively normalizing, dimensionless；
Step 6: determining coal-bed gas exploitation complexity evaluation criterion：According to the coal-bed gas exploitation difficulty or ease journey calculated in step 5
Evaluation number value is spent, on the basis of system coal seam correlation gas actual development data, it is difficult to give coal-bed gas exploitation shown in table 1
The easy intensity grade criteria for classifying：
1 coal-bed gas exploitation complexity opinion rating of table divides table
Step 7: coal-bed gas exploitation complexity is evaluated：It is each based on the coal-bed gas exploitation complexity in step 2~step 4
A evaluation index computation model calculates water yield, Coal Pore Structure index and completion product on the basis of Directorate Of Organization manages interpretive program
Matter index, and then coal-bed gas exploitation complexity evaluation number is calculated using the model in step 5, it is last according to step 6
Shown in coal-bed gas exploitation complexity evaluation criterion, determine the evaluation of evaluated coal-bed gas exploitation complexity.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710340246.7A CN107092032B (en) | 2017-05-15 | 2017-05-15 | A method of utilizing well-log information quantitative assessment coal-bed gas exploitation complexity |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710340246.7A CN107092032B (en) | 2017-05-15 | 2017-05-15 | A method of utilizing well-log information quantitative assessment coal-bed gas exploitation complexity |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107092032A CN107092032A (en) | 2017-08-25 |
| CN107092032B true CN107092032B (en) | 2018-11-06 |
Family
ID=59637797
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710340246.7A Expired - Fee Related CN107092032B (en) | 2017-05-15 | 2017-05-15 | A method of utilizing well-log information quantitative assessment coal-bed gas exploitation complexity |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107092032B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108416282B (en) * | 2018-02-28 | 2021-06-04 | 西安石油大学 | Method for extracting acoustic velocity of echo signal of underground working fluid level based on tubing coupling |
| CN110413951B (en) * | 2018-04-28 | 2023-04-25 | 中国石油天然气股份有限公司 | Determination method for coal bed methane well drainage and production speed |
| CN109064016B (en) * | 2018-07-30 | 2021-08-24 | 西安科技大学 | Method for evaluating hydraulic fracturing permeability-increasing effect of low-permeability coal seam |
| CN111353218B (en) * | 2020-02-20 | 2023-03-24 | 西安石油大学 | Logging quantitative evaluation method for coal bed gas-dense gas reservoir compaction property |
| CN116819644B (en) * | 2023-06-26 | 2024-08-27 | 中国石油天然气股份有限公司 | Method and device for determining minimum horizontal principal stress of shale oil reservoir |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2649504C (en) * | 2005-05-24 | 2014-08-19 | Yates Petroleum Corporation | Methods of evaluating undersaturated coalbed methane reservoirs |
| CN104483706B (en) * | 2014-10-22 | 2016-08-24 | 西安科技大学 | A kind of Coal Pore Structure based on coal petrography mechanics parameter well logging quantitative identification method |
| CN105114068A (en) * | 2015-09-07 | 2015-12-02 | 中国地质大学（北京） | Method of predicting high-water-yield area in coalbed methane area via logging information |
| CN106599377A (en) * | 2016-11-22 | 2017-04-26 | 长江大学 | Method for quantitative division of coal body structure based on logging data and coal body structure parameters |
| CN107066749B (en) * | 2017-04-25 | 2018-03-02 | 西安石油大学 | A kind of method of quantitative assessment Seam Roof And Floor capping performance |
-
2017
- 2017-05-15 CN CN201710340246.7A patent/CN107092032B/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| CN107092032A (en) | 2017-08-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107092032B (en) | A method of utilizing well-log information quantitative assessment coal-bed gas exploitation complexity | |
| CN104314563B (en) | A kind of Quantitative Evaluation with Well Logging method of coalbed methane reservoir pressure break | |
| CN106869911B (en) | Evaluation method for describing compressibility of shale reservoir | |
| CN108009705B (en) | Shale reservoir compressibility evaluation method based on support vector machine technology | |
| CN113283108B (en) | Method and system for quantitatively evaluating fracturing property of shale oil reservoir | |
| KR101642951B1 (en) | GIS-based real time earthquake prediction method | |
| Sandıkkaya et al. | Site classification of Turkish national strong-motion stations | |
| CN102830442B (en) | A kind of potential coefficient partition method of prediction Coalbed Methane Productivity | |
| CN109441422A (en) | A kind of shale gas well spacing optimizing exploitation method | |
| CN109594968A (en) | Fracture parameters evaluation method and system after a kind of shale gas multistage pressure break horizontal well pressure | |
| CN106599482B (en) | Identification method of unconventional overpressure compact gas effective reservoir | |
| CN104199121A (en) | Shale gas pool construction and production favorable area comprehensive determining method | |
| CN106054279B (en) | A kind of determination method of coal petrography brittleness index | |
| CN107066749B (en) | A kind of method of quantitative assessment Seam Roof And Floor capping performance | |
| CN112132454B (en) | Comprehensive evaluation method for water-rich property of water-bearing layer of roof or floor of coal seam | |
| CN106295042B (en) | A kind of coal seam top rock stability Quantitative Evaluation with Well Logging method | |
| CN110058323A (en) | A kind of tight sand formation brittleness index calculation method | |
| CN117744362B (en) | Quantitative evaluation method, system, equipment and terminal for fracturing property of tight sandstone reservoir | |
| CN116122801A (en) | Shale oil horizontal well volume fracturing compressibility comprehensive evaluation method | |
| CN116146176A (en) | Geological-engineering factor-based quantitative classification method for deep coalbed methane reservoir logging | |
| CN109142669A (en) | One kind being based on the relevant coal-bed gas parameter rapid assay methods of data | |
| CN111353218B (en) | Logging quantitative evaluation method for coal bed gas-dense gas reservoir compaction property | |
| CN109522579A (en) | Fractured horizontal well construction Fracturing Pressure Prediction method | |
| CN107605474A (en) | A kind of method and device of prediction while drilling gas-bearing formation yield | |
| CN106097133A (en) | A kind of coal seam water content and aquifer yield Forecasting Methodology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20181106 Termination date: 20190515 |