CN109339771A - A kind of shale oil-gas Layer pore pressure prediction method and system - Google Patents
A kind of shale oil-gas Layer pore pressure prediction method and system Download PDFInfo
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- CN109339771A CN109339771A CN201710648490.XA CN201710648490A CN109339771A CN 109339771 A CN109339771 A CN 109339771A CN 201710648490 A CN201710648490 A CN 201710648490A CN 109339771 A CN109339771 A CN 109339771A
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B47/00—Survey of boreholes or wells
- E21B47/06—Measuring temperature or pressure
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
- E21B49/005—Testing the nature of borehole walls or the formation by using drilling mud or cutting data
Abstract
Disclose a kind of shale oil-gas Layer pore pressure prediction method and system.This method comprises: 1) be based on seismic data, CRP gather is extracted；2) it is based on the CRP gather, carries out the N kind elastic parameter at pre-stack elastic inversion acquisition drilling fluid density test point；3) the N kind elastic parameter value at the drilling fluid density test point is fitted respectively with the Pore Pressure force value at the test point；4) the highest M of the goodness of fit is chosen in N kind elastic parameter, establishes the M member fitting formula of pressure prediction, wherein M < N；5) it is based on the M member fitting formula, calculates shale oil-gas Layer pore pressure using selected M kind elastic parameter value.Compared to traditional API prediction technique, the pressure error value of shale oil-gas Layer pore pressure prediction method according to the present invention is whole smaller, and distribution is relatively more steady, highly reliable.
Description
Technical field
The present invention relates to oil gas geophysics fields, more particularly, to a kind of shale oil-gas Layer pore pressure prediction side
Method and system.
Background technique
Shale gas resource concentration is firstly the need of abundant material base, as in the sedimentary facies belt of deep shelf, shale
Development has scale, is in mature and post-mature stage etc. rich in organic matter, brittle mineral content height, kerogen.But for Fuling
The shale of regional marine deposit, in the metastable situation of material base, the preservation condition of shale reservoir determines shale gas
Yield.These preservation conditions include: good roof and floor, moderate buried depth, flat far from opening fault, tectonic style
Slow, reservoir pressure coefficient height etc..In these preservation conditions, tectonic movement transformation is weak, opening fault agensis is that shale gas is protected
An important factor for depositing condition, and reservoir pressure coefficient is then the comprehensive descision index of shale gas preservation condition, reservoir high pressure-superelevation
Pressure often shows that preservation condition is good, stratum energy foot.
Formation pore pressure is substantially pressure possessed by fluid in formation pore or crack (oil, gas and water), and abnormal high
Pressure or low pressure refer to that pore pressure is higher or lower than fluid pressure.Formed strata pressure extremely can there are many factor, such as
Disequilibrium compaction (fast deposition), construction squeeze (such as tomography), hydro-thermal pressurization, hydro carbon-generation, montmorillonite dehydration, concentration difference with against dense
Difference, gypsum/anhydrite conversion, fluid density difference, the scrambling in flow of water face (foot of the hill drilling well), deep gas fill compartment
Separation and lifting etc..And for the shale formation pressure anomaly of burnt-five peak group of masonry dam area Longma small stream, it is considered that mainly
Since rammell Organic Matter Enrichment causes huge hydro carbon-generation, so that high-quality shale interval and region are enriched large-scale gas
Body forms the mechanism of abnormal high pressure.The core experiment measurement in laboratory also confirms that: the shale rock sample different for TOC content, with
Land the increase of stressor layer, and the content of adsorbed gas is also to gradually increase.In The Southeast of Sichuan Basin and its periphery is practical surveys
The effect of spy also indicates that the either China Petroleum block or Sinopec block range, formation fluid pressure coefficient the high right
The shale gas yield answered often be also it is higher, such as homogeneous kernel fracture to the west of one phase of burnt masonry dam block, average pressure system
Number can be to 1.5, and corresponding gas testing yield is daily for ten thousand side of 11-50, and Peng's page block average pressure system to the east of homogeneous kernel fracture
Number is only 1.0 or so, and practical gas testing yield is only that 20,000 sides are daily.And in the reality of burnt one phase of masonry dam main body and periphery multiple wells
Test yield result and its reservoir pressure coefficient have good positive correlation, i.e. shale formation pressure coefficient is higher, corresponding
Final shale gas yield it is also bigger.It can be said that abnormal high pressure is the key factor of marine facies shale gas enrichment high yield.
In addition, the prediction of strata pressure can reduce drilling risk, improve efficiency, reduce cost (Gutierrez,
2006), most important for shale dessert quality prediction and work arrangement construction.
Formation pressure prediction method, be generally divided into brill before forecast for seismic data, with bore formation pressure monitoring and bore after log well
Three classes are detected, in the exploration phase, concern is primarily with how to utilize the distribution characteristics of forecast for seismic data abnormal formation pressure.State
The inside and outside research about Formation pressure prediction method is after many decades, although the method for description subsurface pressure information and model have
A variety of, from the point of view of the thinking principle of each method, the formula for really characterizing subsurface pressure balance is the Terzaghi formula of nineteen twenty-six:
PP=Po-Pe (1)
Wherein, PpRepresent formation pore pressure；PoRepresent overlying formation pressure, PeRepresent vertical effective stress.Burden pressure
Refer to pressure caused by the overall weight for covering rock matrix and interstitial space fluid, thickness, skeletal density with overlying rock
It is related with gap fluid density.Vertical effective stress refers to that the compaction for the vertical direction that formation skeleton or rock stratum are born produces
Raw stress, also referred to as frame stress, not directly measure.
There are many models or method to describe pore pressure or effective stress in formula 3.6.1, Jin Erzhi at present
Connect or strata pressure predicted indirectly, as equivalent depth method (1965), Eaton method (1976), Bowers method (1995),
Filippone method (1982), Eberhart-Phillips method (1985) etc..The establishment of the selection especially parameter of these methods
All there is extremely strong provincial characteristics, first and last, operates relatively cumbersome.It corresponds, since above-mentioned pressure prediction model is equal
By establishing behind zonal laboratory or the screening of pit shaft test parameter, usually there are stronger corresponding with certain sensitive parameters
The parameters such as relationship, such as formation velocity, interval transit time and density.Thus, in PRESSURE DATA than in more rich situation, Ke Yijin
The screening of row elastic parameter, establishes the peculiar model, such as API prediction technique (2015) etc. for being suitble to regional pressure prediction.However
Still there are larger associations with the correlation of elastic parameter for the precision of such methods, and exist greatly regional.Therefore, having must
It develops and a kind of is distributed steady, highly reliable shale oil-gas Layer pore pressure prediction method and system.
The information for being disclosed in background of invention part is merely intended to deepen the reason to general background technique of the invention
Solution, and it is known to those skilled in the art existing to be not construed as recognizing or imply that the information is constituted in any form
Technology.
Summary of the invention
With going deep into for shale gas resources exploration, especially for China Fuling shale gas field Productivity Construction region,
The pressure prediction precision of shale oil-gas Layer directly determines the ultimate output of shale gas.Burnt regional-five peak group of Longma small stream in masonry dam south
Rammell experienced violent tectonism, and earth's surface is with a varied topography changeable, and existing probing and pressure test data are rare, it is difficult to
Carry out the strata pressure based on pressure balance method to be effectively predicted, it is also difficult to determine effective pressure prediction elastic parameter and combination shape
Formula.To solve the above-mentioned problems, the present invention is based on calculated at drilling fluid density test point Pore Pressure force value and corresponding p-wave impedance,
The pass of the elastic parameters such as S-wave impedance, velocity of longitudinal wave, shear wave velocity, density, Young's modulus, Poisson's ratio and P-S wave velocity ratio
System tests the goodness of fit under various combination exponential fitting, finally screens and establish a kind of shale oil-gas Layer pore pressure earthquake
Multivariate exponential prediction technique, the regional rammell pore pressure in focusing masonry dam south predicted.
According to an aspect of the invention, it is proposed that a kind of shale oil-gas Layer pore pressure prediction method.This method specifically includes that
1) it is based on seismic data, extracts CRP gather；
2) it is based on the CRP gather, carries out the N kind bullet at pre-stack elastic inversion acquisition drilling fluid density test point
Property parameter；
3) to the Pore Pressure force value point at the N kind elastic parameter value and the test point at the drilling fluid density test point
It is not fitted；
4) goodness of fit highest M are chosen in N kind elastic parameter, the M member fitting formula of pressure prediction is established, wherein M <
N；
5) it is based on the M member fitting formula, calculates shale oil-gas Layer Pore Pressure using selected M kind elastic parameter value
Power.
Preferably, the N kind elastic parameter includes p-wave impedance, S-wave impedance, velocity of longitudinal wave, shear wave velocity, density, poplar
Family name's modulus, Poisson's ratio, P-S wave velocity ratio.
Preferably, to the N kind elastic parameter value and the test point at the drilling fluid density test point in step 3)
The Pore Pressure force value at place carries out the fitting of exponential form respectively.
Preferably, M member fitting formula are as follows:
Wherein, PpFor shale oil-gas Layer pore pressure, XiIt is selected goodness of fit highest for corresponding elastic parameter
One of M elastic parameter, AiAnd BiFor the coefficient of different elastic parameter equivalency index fitting formulas, RiFor different elastic parameters
The corresponding goodness of fit.
Preferably, step 1) includes carrying out relative amplitude preserved processing to seismic data to obtain CRP gather.
According to another aspect of the invention, it is proposed that a kind of shale oil-gas Layer pore pressure prediction system.The system includes depositing
Reservoir, processor and storage are on a memory and the computer program that can run on a processor, which is characterized in that the place
Reason device performs the steps of when executing described program
1) it is based on seismic data, extracts CRP gather；
2) it is based on the CRP gather, carries out the N kind bullet at pre-stack elastic inversion acquisition drilling fluid density test point
Property parameter；
3) to the Pore Pressure force value point at the N kind elastic parameter value and the test point at the drilling fluid density test point
It is not fitted；
4) goodness of fit highest M are chosen in N kind elastic parameter, the M member fitting formula of pressure prediction is established, wherein M <
N；
5) it is based on the M member fitting formula, calculates shale oil-gas Layer Pore Pressure using selected M kind elastic parameter value
Power.
Preferably, the N kind elastic parameter includes p-wave impedance, S-wave impedance, velocity of longitudinal wave, shear wave velocity, density, poplar
Family name's modulus, Poisson's ratio, P-S wave velocity ratio.
Preferably, to the N kind elastic parameter value and the test point at the drilling fluid density test point in step 3)
The Pore Pressure force value at place carries out the fitting of exponential form respectively.
Preferably, M member fitting formula are as follows:
Wherein, PpFor shale oil-gas Layer pore pressure, XiIt is selected goodness of fit highest for corresponding elastic parameter
One of M elastic parameter, AiAnd BiFor the coefficient of different elastic parameter equivalency index fitting formulas, RiFor different elastic parameters
The corresponding goodness of fit.
Preferably, step 1) includes carrying out relative amplitude preserved processing to seismic data to obtain CRP gather.
Compared to traditional API prediction technique, the pressure of shale oil-gas Layer pore pressure prediction method according to the present invention
Error amount is whole smaller, and distribution is relatively more steady, highly reliable.
Methods and apparatus of the present invention has other characteristics and advantages, these characteristics and advantages are attached from what is be incorporated herein
It will be apparent in figure and subsequent specific embodiment, or will be in the attached drawing and subsequent specific implementation being incorporated herein
It is stated in detail in example, these the drawings and specific embodiments are used together to explain specific principle of the invention.
Detailed description of the invention
Exemplary embodiment of the present is described in more detail in conjunction with the accompanying drawings, of the invention is above-mentioned and other
Purpose, feature and advantage will be apparent, wherein in exemplary embodiments of the present invention, identical reference label is usual
Represent same parts.
Fig. 1 is the flow chart of the shale oil-gas Layer pore pressure prediction method of exemplary implementation scheme according to the present invention；
Fig. 2 a-2h be different elastic parameters and pressure cross and exponential fitting curve graph, wherein the elasticity ginseng in Fig. 2 a
Number is p-wave impedance Ip, and the elastic parameter in Fig. 2 b is S-wave impedance Is, and the elastic parameter in Fig. 2 c is velocity of longitudinal wave Vp, Fig. 2 d
In elastic parameter be shear wave velocity Vs, the elastic parameter in Fig. 2 e is density p, and the elastic parameter in Fig. 2 f is Young's modulus
Elastic parameter in Ymod, Fig. 2 g is Poisson ratioσ, and the elastic parameter in Fig. 2 h is P-S wave velocity ratio Vp/Vs；
Fig. 3 is actual pressure and two methods forecast pressure comparison diagram at practical sampling point, wherein dotted line is theoretical value,
For prediction technique of the invention,For traditional API prediction technique；
Fig. 4 is two methods forecast pressure at practical sampling point through absolute error comparison diagram, whereinIt is of the invention pre-
Survey method,For traditional API prediction technique；
Fig. 5 is strata pressure distribution map of the high-quality shale section in burnt masonry dam south according to the prediction of API prediction technique；
Fig. 6 is the high-quality shale section in the burnt masonry dam south strata pressure distribution map that method is predicted according to the present invention.
Specific embodiment
The present invention will be described in more detail below with reference to accompanying drawings.Although showing the preferred embodiment of the present invention in attached drawing,
However, it is to be appreciated that may be realized in various forms the present invention and should not be limited by the embodiments set forth herein.On the contrary, providing
These embodiments are of the invention more thorough and complete in order to make, and can will fully convey the scope of the invention to ability
The technical staff in domain.
According to pressure balance principle (formula 1), the pressure prediction method of mainstream is to be first depending on density information and calculate to cover
Pressure then selects suitable model and parameter to simulate pore pressure or effective stress, to characterize the hole on stratum
Pressure.The precision of prediction of strata pressure depends on accurate and the level of detail of data, and its predicting means operating process is complicated, shadow
The factor of sound is more, must carry out stage by stage in real work.
In fact, strata pressure is often with certain sensitive parameters, there are stronger corresponding relationships, such as when formation velocity, sound wave
The parameters such as difference and density.Thus, in PRESSURE DATA than elastic parameter screening in more rich situation, can be carried out, establishes and be suitble to
The peculiar model of regional pressure prediction.Such as API method:
Wherein, σ is Poisson's ratio, and Ip represents p-wave impedance, and C is the pressure coefficient factor.
However, different elastic parameters have different degrees of reflection to pressure information in different regions, characterization seismic velocity with
The Eaton model (1976) of pore pressure relationship, seismic velocity and vertical effective stress relationship Bowers model (1976),
Filippone model (1982) etc. is all based on what mass data statistics was established with laboratory measurement, each parameter is to pressure
The contribution form of information has stringent demonstration.In contrast, the empirical equation based on elastic parameter fitting often lacks laboratory
Demonstration, is of limited application.
The regional rammell in burnt masonry dam south experienced violent tectonism, and earth's surface is with a varied topography changeable, existing probing and
Pressure test data is rare, it is difficult to carry out the strata pressure based on pressure balance method and be effectively predicted, it is also difficult to determine effective pressure
Power predicts elastic parameter and combining form.For this purpose, the present invention is based on calculating Pore Pressure force value at drilling fluid density test point and not
Different types of fitting is carried out with elastic parameter, screening sensitive parameter establishes multiple predictors, thus to the stratum of rammell
Pressure is predicted.
The shale oil-gas Layer pore pressure prediction side of exemplary implementation scheme according to the present invention is described in detail referring to Fig. 1
Method.
This method specifically includes that
Step 1: being based on seismic data, extract CRP gather.
In one example, relative amplitude preserved processing is carried out to seismic data, extracts high-quality common reflection point (CRP) trace gather.
Step 2: being based on the CRP gather, carry out the N at pre-stack elastic inversion acquisition drilling fluid density test point
Kind elastic parameter.
In one example, N kind elastic parameter include p-wave impedance, S-wave impedance, velocity of longitudinal wave, shear wave velocity, density,
Young's modulus, Poisson's ratio, P-S wave velocity ratio.It will be appreciated by those skilled in the art that N kind elastic parameter can be arbitrarily suitably
Elastic parameter type.
Step 3: to the pore pressure at the N kind elastic parameter value and the test point at the drilling fluid density test point
Value is fitted respectively.
Shale probing is generally balanced drilling, and used drilling fluid density corresponds to gravity and is similar to strata pressure substantially.Certain
The pressure data that drilling fluid density generates at one depth point are as follows:
Wherein, H is the vertical height of overlying rock, and ρ is drilling fluid density, and g is acceleration of gravity.For example, according to burnt stone
Burnt page 5-7 well straight well section drilling fluid density information, can calculate corresponding pressure data in the work area Ba Nan.
In real work, between variable may not all wired sexual intercourse, as take medicine after blood concentration and time relationship；Disease is treated
The relationship of effect and course for the treatment of length；The normal curved relationship such as toxic dose and the relationship of lethality.Curve matching refers to that selection is appropriate
Curve type to be fitted observation data, and analyze the relationship between two variables with the curvilinear equation of fitting.With full curve approximation
Ground portray or compare discrete point composition coordinate between functional relation, nonlinearized money can be directly characterized by simple variable
Material and problem.
Fig. 2 a-2h is pressure data and phase at the vertical 42 actual measurement drilling fluid density points of well section of the burnt burnt page 5-7 well in masonry dam south
The elastic parameter at position is answered to cross figure, wherein the elastic parameter in Fig. 2 a is p-wave impedance Ip, and the elastic parameter in Fig. 2 b is
Elastic parameter in S-wave impedance Is, Fig. 2 c is velocity of longitudinal wave Vp, and the elastic parameter in Fig. 2 d is shear wave velocity Vs, in Fig. 2 e
Elastic parameter is density p, and the elastic parameter in Fig. 2 f is Young's modulus Ymod, and the elastic parameter in Fig. 2 g is Poisson ratioσ, Fig. 2 h
In elastic parameter be P-S wave velocity ratio Vp/Vs, PpFor shale oil-gas Layer pore pressure.As can be seen that using exponential form
There is the fitting of different degree of agreement to the different combinations that cross.
The form of fitting then needs to be evaluated according to the identical relationship of itself and practical non-linear point, general excellent using being fitted
Degree is to indicate.The goodness of fit refers to that regression straight line is between expression dependent variable and all independents variable to the fitting degree of observation
Overall relation.The statistic of the measurement goodness of fit is the coefficient of determination (also known as determining coefficient) R2, and value range is [0,1].Tool
Body R is equal to regression sum of square ratio shared in total sum of squares, i.e., regression equation construable dependent variable variability hundred
Divide ratio.The value of R2 illustrates that regression straight line is better to the fitting degree of observation closer to 1；Conversely, the value of R2 is closer to 0, explanation
Regression straight line is poorer to the fitting degree of observation.Following table is the corresponding exponentially fitted formulae of 8 figures that cross and phase of Fig. 2 a-2h
Answer the goodness of fit, wherein PpFor strata pressure namely pore pressure.
The exponential fitting form and the goodness of fit of table 1 different elastic parameters and pressure
From table 1 it follows that pressure-p-wave impedance, pressure-velocity of longitudinal wave have the highest goodness of fit, it is higher than pressure-
S-wave impedance and pressure-shear wave velocity cause air content to increase and ground lamination because of a large amount of hydrocarbons in shale organic matter hole
Power increases, and corresponding velocity of longitudinal wave often reduces, and shear wave is the shearing wave propagated along rock matrix, and sensitivity is not high.
In addition, pressure-Young's modulus, pressure-Poisson's ratio have the stronger goodness of fit.
Step 4: the highest M of the goodness of fit is chosen in N kind elastic parameter, the M member fitting formula of pressure prediction is established,
Middle M < N.
The goodness of fit is highest several in selection elastic parameter, carries out the polynomial fitting formula building of pressure prediction.For example,
Since pressure-density but has a minimum goodness of fit, p-wave impedance and velocity of longitudinal wave itself have an extremely strong correlation again, therefore can be with
The only selection highest pressure of the goodness of fit-p-wave impedance combination, combination pressure-Young's modulus, pressure-Poisson's ratio etc. two are two outer
The combination of the higher goodness of fit constructs ternary Index Prediction Model.
The exponential fitting common version of different elastic parameters are as follows:
Wherein, PpFor shale oil-gas Layer pore pressure, XiFor elastic parameter, AiAnd BiFor the fitting of elastic parameter equivalency index
The coefficient of formula.
It is further introduced into goodness of fit building shale oil-gas Layer pore pressure Multiple Seismic Index Prediction Model are as follows:
Wherein, PpFor shale oil-gas Layer pore pressure, XiIt is selected goodness of fit highest for corresponding elastic parameter
One of M elastic parameter, AiAnd BiFor the coefficient of different elastic parameter equivalency index fitting formulas, RiFor different elastic parameters
The corresponding goodness of fit.
For example, the highest p-wave impedance of the goodness of fit, Young's modulus, Poisson's ratio these three elastic parameters in selection table 1
In the case where, the ternary exponential forecasting formula established are as follows:
PP=180.61e-2E-7·Ip+30.03·e-2E-11·Ymod+43.27·e-6.059·σ (5)
Wherein, Ip is p-wave impedance, and Ymod is Young's modulus, and σ is Poisson's ratio.
Step 5: being based on the M member fitting formula, calculate shale oil-gas Layer hole using selected M kind elastic parameter value
Pressure.
For example, the highest p-wave impedance of the goodness of fit in selection table 1, Young's modulus, Poisson's ratio these three elastic parameters
In the case of, then can be based on formula (5), using at drilling fluid density test point p-wave impedance, Young's modulus, Poisson's ratio this three
The value of a elastic parameter calculates the pore pressure at these test points.
Using example
A concrete application example is given below in the scheme and its effect of the embodiment of the present invention for ease of understanding.This field
It should be understood to the one skilled in the art that the example is only for the purposes of understanding the present invention, any detail is not intended to be limited in any way
The system present invention.
Select traditional API prediction technique and Multiple Seismic exponential pressure prediction technique proposed by the present invention (at this respectively
It is earthquake ternary exponential pressure prediction technique in example, selected is the highest p-wave impedance of the goodness of fit, Young's modulus, pool
Pine is than these three elastic parameters) pressure data is predicted at vertical 42 actual measurement drilling fluid density points of well section of page 5-7 well of focusing,
And compared with the pressure data calculated according to drilling fluid density, as shown in Figure 3.Parameter C foundation and the reality of API prediction technique
Border pressure error minimum principle is selected, specially C=2.37E16.
Obviously, the result general trend of two kinds of prediction techniques prediction is consistent, substantially identical as theoretical value, this is because the two
It is in accordance with the formula of p-wave impedance and Poisson's ratio foundation.But the information due to introducing Young's modulus, substantially it can be seen that
The error of prediction technique of the present invention is smaller, and especially in preceding 18 sampling point positions, the precision based on the prediction of API prediction technique wants bright
The aobvious result lower than the method for the present invention prediction.More the comparison of details can be observed from the comparison of the absolute error of Fig. 4, although
Traditional adjustable figure parameters of API prediction technique are so that the main body distribution of predicted value is close with theoretical value, but discontinuously exists
At preceding 12 sampling points, there are great errors at the 20th sampling point and the 31st sampling point.In contrast, the method for the present invention prediction
Pressure error value is whole smaller, and distribution is relatively more steady, highly reliable.
Fig. 5 and Fig. 6 be for the high-quality shale interval of the peak burnt masonry dam Nan Longmaxi-five group respectively according to API prediction technique and
The strata pressure distribution of earthquake ternary index forecasting method prediction proposed by the present invention.P-wave impedance used by two methods,
The elastic parameters such as Young's modulus and Poisson's ratio are to obtain according to area's pre-stack elastic inversion, and multiple wave and line are utilized before prestack inversion
Property noise removal, random noise decaying and the means such as earth's surface-consistent residual static correction improve trace gather quality, adopted in refutation process
Aggravate density model degree of restraint especially with strict quality control strategy to improve inversion accuracy.
As can be seen that the stratigraphic anormaly high-pressure area of two methods prediction is respectively positioned on level bridge faulted anticline, Baima to oblique advantage
The disconnected nose central and north of position, Wujiang River anticlinal belt and sand a small bay in a river and level bridge faulted anticline are with the bulk zone of northwest.However, the two exists
Difference, the strata pressure based on the prediction of shale oil-gas Layer pore pressure earthquake ternary index forecasting method change more in details
Add continuously, and bigger in above-mentioned several objective zone ranges, more coincide with geological condition.Particularly, traditional API approach prediction
Result in burnt 8 well location of page to set place's pressure value lower, be not inconsistent with actual production, and the page burnt as the result is shown of the method for the present invention prediction
8 well locations coincide in the edge of level bridge faulted anticline abnormal high pressure band, corresponding high shale gas yield with practical condition.
It will be understood by those skilled in the art that above to the purpose of the description of the embodiment of the present invention only for illustratively saying
The beneficial effect of bright the embodiment of the present invention is not intended to limit embodiments of the invention to given any example.
Various embodiments of the present invention are described above, above description is exemplary, and non-exclusive, and
It is not limited to disclosed each embodiment.Without departing from the scope and spirit of illustrated each embodiment, for this skill
Many modifications and changes are obvious for the those of ordinary skill in art field.The selection of term used herein, purport
In the principle, practical application or improvement to the technology in market for best explaining each embodiment, or make the art
Other those of ordinary skill can understand each embodiment disclosed herein.
Claims (10)
1. a kind of shale oil-gas Layer pore pressure prediction method characterized by comprising
1) it is based on seismic data, extracts CRP gather；
2) it is based on the CRP gather, the N kind elasticity that pre-stack elastic inversion obtains at drilling fluid density test point is carried out and joins
Number；
3) at the drilling fluid density test point N kind elastic parameter value and the test point at Pore Pressure force value respectively into
Row fitting；
4) the highest M of the goodness of fit is chosen in N kind elastic parameter, establishes the M member fitting formula of pressure prediction, wherein M < N；
5) it is based on the M member fitting formula, calculates shale oil-gas Layer pore pressure using selected M kind elastic parameter value.
2. shale oil-gas Layer pore pressure prediction method according to claim 1, which is characterized in that the N kind elasticity ginseng
Number includes p-wave impedance, S-wave impedance, velocity of longitudinal wave, shear wave velocity, density, Young's modulus, Poisson's ratio, P-S wave velocity ratio.
3. shale oil-gas Layer pore pressure prediction method according to claim 1, which is characterized in that institute in step 3)
It states the Pore Pressure force value at N kind elastic parameter value and the test point at drilling fluid density test point and carries out exponential form respectively
Fitting.
4. shale oil-gas Layer pore pressure prediction method according to claim 1, which is characterized in that M member fitting formula are as follows:
Wherein, PpFor shale oil-gas Layer pore pressure, XiIt is the highest M of the selected goodness of fit for corresponding elastic parameter
One of elastic parameter, AiAnd BiFor the coefficient of different elastic parameter equivalency index fitting formulas, RiIt is corresponding for different elastic parameters
The goodness of fit.
5. shale oil-gas Layer pore pressure prediction method according to claim 1, which is characterized in that step 1) includes over the ground
Shake data carries out relative amplitude preserved processing and obtains CRP gather.
6. a kind of shale oil-gas Layer pore pressure prediction system, which is characterized in that the system comprises memory, processor and
Store the computer program that can be run on a memory and on a processor, which is characterized in that the processor executes the journey
It is performed the steps of when sequence
1) it is based on seismic data, extracts CRP gather；
2) it is based on the CRP gather, the N kind elasticity that pre-stack elastic inversion obtains at drilling fluid density test point is carried out and joins
Number；
3) at the drilling fluid density test point N kind elastic parameter value and the test point at Pore Pressure force value respectively into
Row fitting；
4) the highest M of the goodness of fit is chosen in N kind elastic parameter, establishes the M member fitting formula of pressure prediction, wherein M < N；
5) it is based on the M member fitting formula, calculates shale oil-gas Layer pore pressure using selected M kind elastic parameter value.
7. shale oil-gas Layer pore pressure prediction system according to claim 6, which is characterized in that the N kind elasticity ginseng
Number includes p-wave impedance, S-wave impedance, velocity of longitudinal wave, shear wave velocity, density, Young's modulus, Poisson's ratio, P-S wave velocity ratio.
8. shale oil-gas Layer pore pressure prediction system according to claim 6, which is characterized in that institute in step 3)
It states the Pore Pressure force value at N kind elastic parameter value and the test point at drilling fluid density test point and carries out exponential form respectively
Fitting.
9. shale oil-gas Layer pore pressure prediction system according to claim 6, which is characterized in that M member fitting formula are as follows:
Wherein, PpFor shale oil-gas Layer pore pressure, XiIt is the highest M of the selected goodness of fit for corresponding elastic parameter
One of elastic parameter, AiAnd BiFor the coefficient of different elastic parameter equivalency index fitting formulas, RiIt is corresponding for different elastic parameters
The goodness of fit.
10. shale oil-gas Layer pore pressure prediction system according to claim 6, which is characterized in that step 1) includes pair
Seismic data carries out relative amplitude preserved processing and obtains CRP gather.
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