CN107703543A - It is a kind of based on generalized Poisson than formation pore pressure Forecasting Methodology and system - Google Patents
It is a kind of based on generalized Poisson than formation pore pressure Forecasting Methodology and system Download PDFInfo
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Abstract
Protectiveness of the present invention announce it is a kind of based on generalized Poisson than formation pore pressure Forecasting Methodology and system, method include：S1, according to country rock velocity of longitudinal wave and country rock shear wave velocity, obtain the generalized Poisson slowness of country rock, according to pseudo-p wave speed, intend shear wave velocity and mathematics amplifier, obtain the generalized Poisson slowness of reservoir；S2, according to the generalized Poisson slowness of country rock, the generalized Poisson slowness of reservoir, mathematics amplifier, country rock velocity of longitudinal wave, pseudo-p wave speed, country rock shear wave velocity and intend shear wave velocity, obtain containing sign construction feature generalized Poisson ratio；S3, according to generalized Poisson ratio, depth of stratum and empirical coefficient, obtain formation pore pressure coefficient.The beneficial effects of the invention are as follows：Consider a variety of abnormal pressure influence factors simultaneously, by expanding the geophysical anomaly after reservoir gas-bearing, reach the purpose of prediction strata pressure.
Description
Technical field
The present invention relates to oil exploration and development fields, it is more particularly to a kind of based on generalized Poisson than formation pore pressure it is pre-
Survey method and system.
Background technology
Stratum mesopore Fluid pressure deviates the change of underground fluid hydrostatic pressure, referred to as abnormal formation pressure.Ground is laminated
The problem of power problem is extremely important in petroleum geology and oil-gas exploration.Strata pressure is the important motivity of Gas Accumulation, is stream
The basis of body posture prediction.Pressure anomaly reflects hydrocarbon source condition, Seal Condition and the hydrocarbon supercharging, heating supercharging, hydrocarbon on stratum
The various geological processes such as class liquid-gas conversion supercharging and Clay Mineral Transformation supercharging.Accurate prediction formation pore pressure is for boring
Well mud balance, cannula series design, predict distribution of source rock, reflect that possible oil-gas migration sensing etc. has important work
With.
The method of prediction Abnormal Formation Pressure mainly has three classes：Prediction before drilling method, monitoring while drilling method and the lamination of actual measurement ground
Power.Latter two method mainly predicts strata pressure using well-log information, has property and locality afterwards；Prediction before drilling method master
To utilize seismic data, its area coverage is wide, abundant information, can obtain Pressure Distribution in transverse direction and longitudinal direction, before having
Looking forward or upwards property and of overall importance, turns into one of Main Means of pre-drilling pressure forecasting.Pre-drilling pressure forecasting model more commonly used at present has
Eaton methods, Fillippone methods, equivalent depth method and integrated interpretation method using sound speed detection strata pressure etc., these sides
Method is based primarily upon undercompaction theory, is only applicable to the situation of " stratum undercompaction caused by disequilibrium compaction process " high pressure, and absolutely
Most of method is only limitted to use in sand shale, without universality.
The content of the invention
The invention provides it is a kind of based on generalized Poisson than formation pore pressure Forecasting Methodology and system, solve existing
The technical problem of technology.
The technical scheme that the present invention solves above-mentioned technical problem is as follows：
It is a kind of based on generalized Poisson than formation pore pressure Forecasting Methodology, including：
S1, according to country rock velocity of longitudinal wave and country rock shear wave velocity, the generalized Poisson slowness of country rock is obtained, according to pseudo-p wave speed
Degree, intend shear wave velocity and mathematics amplifier, obtain the generalized Poisson slowness of reservoir；
S2, according to the generalized Poisson slowness of the country rock, the generalized Poisson slowness of the reservoir, the mathematics amplifier,
The country rock velocity of longitudinal wave, the pseudo-p wave speed, the country rock shear wave velocity and the plan shear wave velocity, obtain containing sign
The generalized Poisson ratio of construction feature；
S3, according to generalized Poisson ratio, depth of stratum and the empirical coefficient, obtain formation pore pressure coefficient.
The beneficial effects of the invention are as follows：To different regions, different spaces lithology abnormal pressure Genetic Mechanism basis
On, using compressional wave and shear wave velocity, while take into account the influence of vertical and horizontal stress, while consider a variety of abnormal pressures influence because
Element, by expanding the geophysical anomaly after reservoir gas-bearing, reach the purpose of prediction strata pressure, there is universality.
On the basis of above-mentioned technical proposal, the present invention can also do following improvement.
Preferably, step S1 is specifically included：
According to below equation (1), the generalized Poisson slowness D of country rock is obtained0；
According to below equation (2), the generalized Poisson slowness D of reservoir is obtainedg；
Wherein, Vp0For country rock velocity of longitudinal wave, Vs0For country rock shear wave velocity, VzpFor pseudo-p wave speed, VzsTo intend shear wave speed
Degree, C is mathematics amplifier.
Preferably, step S2 is specifically included：
According to below equation (3), generalized Poisson is obtained than Δ σg；
Wherein, D0For the generalized Poisson slowness of country rock, DgFor the generalized Poisson slowness of reservoir, Δ VzpFor country rock velocity of longitudinal wave
Vp0With pseudo-p wave speed VzpDifference, Δ VzsFor country rock shear wave velocity Vs0With intending shear wave velocity VzsDifference, C be mathematics amplification
Device.
Preferably, step S3 is specifically included：
According to below equation (4), formation pore pressure coefficient gamma is obtained；
Wherein, Δ σgFor generalized Poisson ratio, a, b, c are empirical coefficient, and H is depth of stratum, bH2For characterize fluid expansion and
The expansion factor that undercompaction influences.
Preferably, the mathematics amplifier is intends the ratio of interval transit time and actual interval transit time, the plan interval transit time
For the actual interval transit time with, the sum of products of calibration coefficient and natural gamma, the actual interval transit time passes through actual survey
Well obtains.
It is a kind of based on generalized Poisson than formation pore pressure forecasting system, including：
First acquisition module, for according to country rock velocity of longitudinal wave and country rock shear wave velocity, the generalized Poisson for obtaining country rock to be slow
Degree, according to pseudo-p wave speed, intend shear wave velocity and mathematics amplifier, obtain the generalized Poisson slowness of reservoir；
Second acquisition module, for the generalized Poisson slowness according to the country rock, the generalized Poisson slowness of the reservoir, institute
State mathematics amplifier, the country rock velocity of longitudinal wave, the pseudo-p wave speed, the country rock shear wave velocity and the plan shear wave speed
Degree, obtain containing the generalized Poisson ratio for characterizing construction feature；
3rd acquisition module, for according to generalized Poisson ratio, depth of stratum and the empirical coefficient, obtaining formation pore pressure
Force coefficient.
Preferably, first acquisition module is specifically used for：
According to below equation (1), the generalized Poisson slowness D of country rock is obtained0；
According to below equation (2), the generalized Poisson slowness D of reservoir is obtainedg；
Wherein, Vp0For country rock velocity of longitudinal wave, Vs0For country rock shear wave velocity, VzpFor pseudo-p wave speed, VzsTo intend shear wave speed
Degree, C is mathematics amplifier.
Preferably, second acquisition module is specifically used for：
According to below equation (3), generalized Poisson is obtained than Δ σg；
Wherein, D0For the generalized Poisson slowness of country rock, DgFor the generalized Poisson slowness Δ V of reservoirzpFor country rock velocity of longitudinal wave
Vp0With pseudo-p wave speed VzpDifference, Δ VzsFor country rock shear wave velocity Vs0With intending shear wave velocity VzsDifference, C be mathematics amplification
Device.
Preferably, the 3rd acquisition module is specifically used for：
According to below equation (4), formation pore pressure coefficient gamma is obtained；
Wherein, Δ σgFor generalized Poisson ratio, a, b, c are empirical coefficient, and H is depth of stratum, bH2For characterize fluid expansion and
The expansion factor that undercompaction influences.
Preferably, the mathematics amplifier is intends the ratio of interval transit time and actual interval transit time, the plan interval transit time
For the actual interval transit time with, the sum of products of calibration coefficient and natural gamma, the actual interval transit time passes through actual survey
Well obtains.
Brief description of the drawings
Fig. 1 be it is provided in an embodiment of the present invention it is a kind of based on generalized Poisson than formation pore pressure Forecasting Methodology flow
Schematic diagram；
Fig. 2 is Siggins and Dewhurst in the test result schematic diagram to water-filling and inflation sandstone in 2003；
Relation schematic diagrams of the Fig. 3 between abnormal high pressure well position and depth；
Fig. 4 is plane comparison diagram of the generalized Poisson than method and Fillippone method prediction results；
Fig. 5 be another embodiment of the present invention provide it is a kind of based on generalized Poisson than formation pore pressure forecasting system
Structural representation.
Embodiment
The principle and feature of the present invention are described below in conjunction with accompanying drawing, the given examples are served only to explain the present invention, and
It is non-to be used to limit the scope of the present invention.
As shown in figure 1, it is a kind of based on generalized Poisson than formation pore pressure Forecasting Methodology, including：
S1, according to country rock velocity of longitudinal wave and country rock shear wave velocity, the generalized Poisson slowness of country rock is obtained, according to pseudo-p wave speed
Degree, intend shear wave velocity and mathematics amplifier, obtain the generalized Poisson slowness of reservoir；
S2, according to the generalized Poisson slowness of country rock, the generalized Poisson slowness of reservoir, mathematics amplifier, country rock velocity of longitudinal wave,
Pseudo-p wave speed, country rock shear wave velocity and plan shear wave velocity, are obtained containing the generalized Poisson ratio for characterizing construction feature；
S3, according to generalized Poisson ratio, depth of stratum and empirical coefficient, obtain formation pore pressure coefficient.
In the overpressured formation of low effective stress, grain sorting is poor, influence of the loose contact to compressional wave compares shear wave
Influence much bigger, speed ratio is the key parameter of rock, and it is directly associated with abnormal pressure.Conventional abnormal pressure Forecasting Methodology
P wave data is only used only, Poisson's ratio is not accounted in Forecasting Methodology.Fig. 2 was Siggins and Dewhurst in 2003
To the test result of water-filling and inflation sandstone, for water-filling, Poisson's ratio reduces with the increase of effective stress；To inflation
For, Poisson's ratio increases with the increase of effective stress.
Poisson's ratio and the important parameter that density is layer description：The value of Poisson's ratio and density is smaller, corresponding reservoir quality
Better.By selecting it is expected the optimal rotary shaft for separating mud stone, salt solution saturation sandstone, oily saturation sandstone, reach discrimination lithology-stream
The purpose of difference between body type (mud stone, salt solution saturation sandstone, oily saturation sandstone).Compared with salt solution saturated sand petrofacies, gas reservoir or
The Poisson impedance value (product of Poisson's ratio and density) of oil reservoir is relatively low, and porosity is higher, so, Poisson impedance is High-quality Reservoir
Important symbol, formation pore pressure prediction can be carried out using generalized Poisson ratio method.The product of pressure coefficient and depth of stratum
As formation pore pressure.
Since P-wave And S is different to the sensitivity of gas reservoir, then, we can copy and SP is borrowed in synthetic seismogram
Curve, the thought of pseudo-acoustic curve is generated, it is different by expanding the geophysics after reservoir gas-bearing using generalized Poisson ratio method
Often, the purpose of predicting reservoir abnormal pressure is reached.
Specifically, step S1 is specifically included：
According to below equation (1), the generalized Poisson slowness D of country rock is obtained0；
According to below equation (2), the generalized Poisson slowness D of reservoir is obtainedg；
Wherein, Vp0For country rock velocity of longitudinal wave, Vs0For country rock shear wave velocity, VzpFor pseudo-p wave speed, VzsTo intend shear wave speed
Degree, C is mathematics amplifier.
Specifically, step S2 is specifically included：
According to below equation (3), generalized Poisson is obtained than Δ σg；
Wherein, D0For the generalized Poisson slowness of country rock, DgFor the generalized Poisson slowness of reservoir, Δ VzpFor country rock velocity of longitudinal wave
Vp0With pseudo-p wave speed VzpDifference, Δ VzsFor country rock shear wave velocity Vs0With intending shear wave velocity VzsDifference, C be mathematics amplification
Device.
Specifically, step S3 is specifically included：
According to below equation (4), formation pore pressure coefficient gamma is obtained；
Wherein, Δ σgFor generalized Poisson ratio, a, b, c are empirical coefficient, and H is depth of stratum, bH2For characterize fluid expansion and
The expansion factor that undercompaction influences.A, b, c be according to the pore pressure coefficient value of actual measurement fit come empirical coefficient.
Specifically, for mathematics amplifier to intend the ratio of interval transit time and actual interval transit time, plan interval transit time is actual sound
The ripple time difference with, the sum of products of calibration coefficient and natural gamma, actual interval transit time is obtained by practical logging.Calibration coefficient is
Given according to observed pressure coefficient.
Mathematics amplifier is the function with spatial variations, is the ratio for intending interval transit time and actual interval transit time.And onomatopoeia
The ripple time difference asks for copying Pseudo-acoustic curve construction method in Application of Logging-constrained Inversion；It can utilize and reflect lithology and change of fluid ratio
The logs such as more sensitive natural gamma GR, natural potential SP and resistivity are converted to the onomatopoeia curve with sound wave dimension
Line." velocity of longitudinal wave " calculated using pseudo-acoustic curve, we term it pseudo-p wave speed, according to vertical shear wave logging data, system
P-and s-wave velocity relation is counted, calculates and intends shear wave velocity parameter, intends shear wave velocity and can also reconstruct to obtain by shear wave velocity.With connection
Hole, the rock stratum for allowing oil gas to store and be percolated wherein are referred to as most of reservoir, the oil and gas reserves having found in the world
From sedimentary type formations, wherein mostly important with sandstone and carbonate reservoir, shale can also be used as reservoir；Igneous rock and change
Matter rock also has industrialness oil and gas discovery in reservoir.Rock mass around reservoir is referred to as country rock, and mud stone belongs to typical weakness and enclosed
Rock.Under normal compaction background, overlying rock (i.e. country rock) weight is constantly by formation compaction, Rock Matrix particle close-packed arrays,
Increase to transmit the rock particles contact point of sound wave, SVEL constantly increases.In the event of abnormal pressure, in reservoir
Pore-fluid assume responsibility for part overburden weight, increase speed of the particle contacts no longer by normal trend, so as to
Deviate the relatively normal velocity of sound Trendline of SVEL.Compaction curve fitting is speed and depth under normal compaction background
Relation, what is obtained is normal compaction rate curve, that is, the country rock speed in calculation formula.If SVEL is relatively just
Normal velocity of sound Trendline deviates, and illustrates to contain oil gas in reservoir, high pressure be present.Can be with using the deviation of these compacting trends
Judge the layer position of abnormal pressure occur, determine the depth of pressure transition zone, as shown in Figure 3.Underlying parameter is ready, by its band
Enter pressure coefficient calculation formula, obtain pressure coefficient value.
Fig. 4 is to be predicted to illustrate with the Comparative result being predicted using prior art using the method for the present embodiment
Figure.Fig. 4 is generalized Poisson than method and Fillippone method prediction result plane comparison diagrams.
In Fig. 4, Fillippone methods prediction sea level changes are larger, rough, and some " buphthalmos " occur, and generalized Poisson ratio
Method prediction result plan is more smooth, and change is gentle, and results contrast is reasonable.
As shown in figure 5, it is a kind of based on generalized Poisson than formation pore pressure forecasting system, including：
First acquisition module 501, for according to country rock velocity of longitudinal wave and country rock shear wave velocity, obtaining the generalized Poisson of country rock
Slowness, according to pseudo-p wave speed, intend shear wave velocity and mathematics amplifier, obtain the generalized Poisson slowness of reservoir；
Second acquisition module 502, put for the generalized Poisson slowness according to country rock, the generalized Poisson slowness of reservoir, mathematics
Big device, country rock velocity of longitudinal wave, pseudo-p wave speed, country rock shear wave velocity and plan shear wave velocity, are obtained containing sign construction feature
Generalized Poisson ratio；
3rd acquisition module 503, for according to generalized Poisson ratio, depth of stratum and empirical coefficient, obtaining formation pore pressure
Force coefficient.
Specifically, the first acquisition module 501 is specifically used for：
According to below equation (1), the generalized Poisson slowness D of country rock is obtained0；
According to below equation (2), the generalized Poisson slowness D of reservoir is obtainedg；
Wherein, Vp0For country rock velocity of longitudinal wave, Vs0For country rock shear wave velocity, VzpFor pseudo-p wave speed, VzsTo intend shear wave speed
Degree, C is mathematics amplifier.
Specifically, the second acquisition module 502 is specifically used for：
According to below equation (3), generalized Poisson is obtained than Δ σg；
Wherein, D0For the generalized Poisson slowness of country rock, DgFor the generalized Poisson slowness of reservoir, Δ VzpFor country rock velocity of longitudinal wave
Vp0With pseudo-p wave speed VzpDifference, Δ VzsFor country rock shear wave velocity Vs0With intending shear wave velocity VzsDifference, C be mathematics amplification
Device.
Specifically, the 3rd acquisition module 503 is specifically used for：
According to below equation (4), formation pore pressure coefficient gamma is obtained；
Wherein, Δ σgFor generalized Poisson ratio, a, b, c are empirical coefficient, and H is depth of stratum, bH2For characterize fluid expansion and
The expansion factor that undercompaction influences.
Specifically, for mathematics amplifier to intend the ratio of interval transit time and actual interval transit time, plan interval transit time is actual sound
The ripple time difference with, the sum of products of calibration coefficient and natural gamma, actual interval transit time is obtained by practical logging.Calibration coefficient is
Given according to observed pressure coefficient.
The foregoing is only presently preferred embodiments of the present invention, be not intended to limit the invention, it is all the present invention spirit and
Within principle, any modification, equivalent substitution and improvements made etc., it should be included in the scope of the protection.
Claims (10)
1. it is a kind of based on generalized Poisson than formation pore pressure Forecasting Methodology, it is characterised in that including：
S1, according to country rock velocity of longitudinal wave and country rock shear wave velocity, obtain the generalized Poisson slowness of country rock, according to pseudo-p wave speed,
Intend shear wave velocity and mathematics amplifier, obtain the generalized Poisson slowness of reservoir；
S2, according to the generalized Poisson slowness of the country rock, the generalized Poisson slowness of the reservoir, the mathematics amplifier, described
Country rock velocity of longitudinal wave, the pseudo-p wave speed, the country rock shear wave velocity and the plan shear wave velocity, obtain constructing containing sign
The generalized Poisson ratio of feature；
S3, according to generalized Poisson ratio, depth of stratum and the empirical coefficient, obtain formation pore pressure coefficient.
2. it is according to claim 1 it is a kind of based on generalized Poisson than formation pore pressure Forecasting Methodology, it is characterised in that
Step S1 is specifically included：
According to below equation (1), the generalized Poisson slowness D of country rock is obtained0；
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<mi>D</mi>
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According to below equation (2), the generalized Poisson slowness D of reservoir is obtainedg；
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Wherein, Vp0For country rock velocity of longitudinal wave, Vs0For country rock shear wave velocity, VzpFor pseudo-p wave speed, VzsTo intend shear wave velocity, C is
Mathematics amplifier.
3. it is according to claim 2 it is a kind of based on generalized Poisson than formation pore pressure Forecasting Methodology, it is characterised in that
Step S2 is specifically included：
According to below equation (3), generalized Poisson is obtained than Δ σg；
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Wherein, D0For the generalized Poisson slowness of country rock, DgFor the generalized Poisson slowness of reservoir, Δ VzpFor country rock velocity of longitudinal wave Vp0With
Pseudo-p wave speed VzpDifference, Δ VzsFor country rock shear wave velocity Vs0With intending shear wave velocity VzsDifference, C is mathematics amplifier.
4. according to claim any one of 1-3 it is a kind of based on generalized Poisson than formation pore pressure Forecasting Methodology, its
It is characterised by, step S3 is specifically included：
According to below equation (4), formation pore pressure coefficient gamma is obtained；
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Wherein, Δ σgFor generalized Poisson ratio, a, b, c are for empirical coefficient, and H is depth of stratum, bH2To characterize fluid expansion and owing
It is compacted the expansion factor influenceed.
5. according to claim any one of 1-3 it is a kind of based on generalized Poisson than formation pore pressure Forecasting Methodology, its
It is characterised by, for the mathematics amplifier to intend the ratio of interval transit time and actual interval transit time, the plan interval transit time is described
Actual interval transit time with, the sum of products of calibration coefficient and natural gamma, the actual interval transit time is obtained by practical logging.
6. it is a kind of based on generalized Poisson than formation pore pressure forecasting system, it is characterised in that including：
First acquisition module, for according to country rock velocity of longitudinal wave and country rock shear wave velocity, obtaining the generalized Poisson slowness of country rock, root
According to pseudo-p wave speed, intend shear wave velocity and mathematics amplifier, obtain the generalized Poisson slowness of reservoir；
Second acquisition module, for the generalized Poisson slowness according to the country rock, the generalized Poisson slowness of the reservoir, the number
Amplifier, the country rock velocity of longitudinal wave, the pseudo-p wave speed, the country rock shear wave velocity and the plan shear wave velocity are learned, is obtained
To the generalized Poisson ratio for containing sign construction feature；
3rd acquisition module, for according to generalized Poisson ratio, depth of stratum and the empirical coefficient, obtaining formation pore pressure system
Number.
7. it is according to claim 6 it is a kind of based on generalized Poisson than formation pore pressure forecasting system, it is characterised in that
First acquisition module is specifically used for：
According to below equation (1), the generalized Poisson slowness D of country rock is obtained0；
<mrow>
<msub>
<mi>D</mi>
<mn>0</mn>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mfrac>
<mn>1</mn>
<msqrt>
<mn>2</mn>
</msqrt>
</mfrac>
<msub>
<mi>V</mi>
<mrow>
<mi>p</mi>
<mn>0</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>V</mi>
<mrow>
<mi>s</mi>
<mn>0</mn>
</mrow>
</msub>
</mrow>
<mrow>
<msubsup>
<mi>V</mi>
<mrow>
<mi>p</mi>
<mn>0</mn>
</mrow>
<mn>2</mn>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>V</mi>
<mrow>
<mi>s</mi>
<mn>0</mn>
</mrow>
<mn>2</mn>
</msubsup>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mrow>
According to below equation (2), the generalized Poisson slowness D of reservoir is obtainedg；
<mrow>
<msub>
<mi>D</mi>
<mi>g</mi>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mfrac>
<mi>C</mi>
<msqrt>
<mn>2</mn>
</msqrt>
</mfrac>
<msub>
<mi>V</mi>
<mrow>
<mi>z</mi>
<mi>p</mi>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>V</mi>
<mrow>
<mi>z</mi>
<mi>s</mi>
</mrow>
</msub>
</mrow>
<mrow>
<msubsup>
<mi>V</mi>
<mrow>
<mi>z</mi>
<mi>p</mi>
</mrow>
<mn>2</mn>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>V</mi>
<mrow>
<mi>z</mi>
<mi>s</mi>
</mrow>
<mn>2</mn>
</msubsup>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, Vp0For country rock velocity of longitudinal wave, Vs0For country rock shear wave velocity, VzpFor pseudo-p wave speed, VzsTo intend shear wave velocity, C is
Mathematics amplifier.
8. it is according to claim 7 it is a kind of based on generalized Poisson than formation pore pressure forecasting system, it is characterised in that
Second acquisition module is specifically used for：
According to below equation (3), generalized Poisson is obtained than Δ σg；
<mrow>
<msub>
<mi>&Delta;&sigma;</mi>
<mi>g</mi>
</msub>
<mo>=</mo>
<mrow>
<mo>(</mo>
<msub>
<mi>D</mi>
<mi>g</mi>
</msub>
<mo>-</mo>
<msub>
<mi>D</mi>
<mn>0</mn>
</msub>
<mo>)</mo>
</mrow>
<mrow>
<mo>(</mo>
<mfrac>
<mi>C</mi>
<msqrt>
<mn>2</mn>
</msqrt>
</mfrac>
<msub>
<mi>&Delta;V</mi>
<mrow>
<mi>z</mi>
<mi>p</mi>
</mrow>
</msub>
<mo>-</mo>
<msub>
<mi>&Delta;V</mi>
<mrow>
<mi>z</mi>
<mi>s</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, D0For the generalized Poisson slowness of country rock, DgFor the generalized Poisson slowness of reservoir, Δ VzpFor country rock velocity of longitudinal wave Vp0With
Pseudo-p wave speed VzpDifference, Δ VzsFor country rock shear wave velocity Vs0With intending shear wave velocity VzsDifference, C is mathematics amplifier.
9. according to claim any one of 6-8 it is a kind of based on generalized Poisson than formation pore pressure forecasting system, its
It is characterised by, the 3rd acquisition module is specifically used for：
According to below equation (4), formation pore pressure coefficient gamma is obtained；
<mrow>
<mi>&gamma;</mi>
<mo>=</mo>
<msup>
<mi>lge</mi>
<mrow>
<msub>
<mi>a&Delta;&sigma;</mi>
<mi>g</mi>
</msub>
<mo>+</mo>
<msup>
<mi>bH</mi>
<mn>2</mn>
</msup>
<mo>+</mo>
<mi>c</mi>
</mrow>
</msup>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>4</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, Δ σgFor generalized Poisson ratio, a, b, c are empirical coefficient, and H is depth of stratum, bH2To characterize fluid expansion and under-voltage
The expansion factor influenceed in fact.
10. according to claim any one of 6-8 it is a kind of based on generalized Poisson than formation pore pressure forecasting system, its
It is characterised by, for the mathematics amplifier to intend the ratio of interval transit time and actual interval transit time, the plan interval transit time is described
Actual interval transit time with, the sum of products of calibration coefficient and natural gamma, the actual interval transit time is obtained by practical logging.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108717202A (en) * | 2018-05-31 | 2018-10-30 | 中国地质大学（武汉） | A kind of shale gas abnormal formation pressure prediction technique considering fluid temperature (F.T.) |
| CN110069751A (en) * | 2019-05-07 | 2019-07-30 | 中国海洋石油集团有限公司 | A kind of non-undercompacted formation pore pressure prediction method |
| CN110297280A (en) * | 2018-03-23 | 2019-10-01 | 中国石油化工股份有限公司 | A kind of prediction technique of carbonate rock superpressure spatial distribution characteristic |
| CN115788419A (en) * | 2022-11-23 | 2023-03-14 | 西南石油大学 | Complex overpressure cause formation pore pressure prediction method |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6374186B1 (en) * | 2000-03-24 | 2002-04-16 | Petrophysical Consulting, Inc. | Method for overpressure detection from compressional-and- shear-wave data |
| CN106368691A (en) * | 2015-07-24 | 2017-02-01 | 中国石油化工股份有限公司 | Method for predicting three-dimensional abnormal pore pressure based on rock physical seismic information |
| CN106368686A (en) * | 2015-07-17 | 2017-02-01 | 中国石油化工股份有限公司 | Method for computing stratum pressure based on rock Poisson's ratio |
-
2017
- 2017-09-11 CN CN201710812873.6A patent/CN107703543B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6374186B1 (en) * | 2000-03-24 | 2002-04-16 | Petrophysical Consulting, Inc. | Method for overpressure detection from compressional-and- shear-wave data |
| CN106368686A (en) * | 2015-07-17 | 2017-02-01 | 中国石油化工股份有限公司 | Method for computing stratum pressure based on rock Poisson's ratio |
| CN106368691A (en) * | 2015-07-24 | 2017-02-01 | 中国石油化工股份有限公司 | Method for predicting three-dimensional abnormal pore pressure based on rock physical seismic information |
Non-Patent Citations (3)
| Title |
|---|
| 朱伟: "碳酸盐岩地层压力预测方法研究", 《CPS/SEG北京2009国际地球物理会议论文集》 * |
| 赵金洲: "《钻井工程技术手册》", 31 August 2006, 中国石化出版社 * |
| 陈鑫: "基于地震资料的探井钻前孔隙压力预测", 《石油与天然气地质》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110297280A (en) * | 2018-03-23 | 2019-10-01 | 中国石油化工股份有限公司 | A kind of prediction technique of carbonate rock superpressure spatial distribution characteristic |
| CN110297280B (en) * | 2018-03-23 | 2021-04-09 | 中国石油化工股份有限公司 | Prediction method for carbonate rock overpressure spatial distribution characteristics |
| CN108717202A (en) * | 2018-05-31 | 2018-10-30 | 中国地质大学（武汉） | A kind of shale gas abnormal formation pressure prediction technique considering fluid temperature (F.T.) |
| CN108717202B (en) * | 2018-05-31 | 2020-01-17 | 中国地质大学（武汉） | Shale gas abnormal formation pressure prediction method considering fluid temperature |
| CN110069751A (en) * | 2019-05-07 | 2019-07-30 | 中国海洋石油集团有限公司 | A kind of non-undercompacted formation pore pressure prediction method |
| CN110069751B (en) * | 2019-05-07 | 2022-05-03 | 中国海洋石油集团有限公司 | Non-undercompacted stratum pore pressure prediction method |
| CN115788419A (en) * | 2022-11-23 | 2023-03-14 | 西南石油大学 | Complex overpressure cause formation pore pressure prediction method |
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