CN106908856A - A kind of earthquake prediction method of lacustrine facies thin layer dolostone reservoirs - Google Patents
A kind of earthquake prediction method of lacustrine facies thin layer dolostone reservoirs Download PDFInfo
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- CN106908856A CN106908856A CN201710038743.1A CN201710038743A CN106908856A CN 106908856 A CN106908856 A CN 106908856A CN 201710038743 A CN201710038743 A CN 201710038743A CN 106908856 A CN106908856 A CN 106908856A
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- dolostone reservoirs
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- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V11/00—Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00
Abstract
The invention discloses a kind of earthquake prediction method of lacustrine facies thin layer dolostone reservoirs, it is related to petroleum industry Geological Engineering field.Methods described includes：Obtain the seismic data cube in target reservoir region and the petrographic thin section of individual well reservoir；Micro-analysis is carried out to the petrographic thin section, the dolostone reservoirs distribution of the individual well reservoir is obtained；The log of the individual well reservoir is obtained by logging method, the log sensitive to the dolostone reservoirs reaction of the individual well reservoir is obtained；According to the sensitive log of the dolostone reservoirs reaction to the individual well reservoir, well logging recognition template is set up；The well logging recognition template is loaded into the seismic data cube, the distribution of the dolostone reservoirs in the target reservoir region is predicted.The predictable thickness in monolayer of method provided in an embodiment of the present invention overcomes the limitation of thin layer dolomite seismic resolution in 0.5 1.5 meters or so lacustrine facies thin layer dolostone reservoirs, can accurately carry out thin layer dolostone reservoirs earthquake prediction, improves drilling success.
Description
Technical field
The present invention relates to petroleum industry Geological Engineering field, more particularly to a kind of earthquake of lacustrine facies thin layer dolostone reservoirs is pre-
Survey method.
Background technology
The large area distribution in Continental Basins In China of lacustrine facies thin layer dolomite, because thickness in monolayer is at 0.5-1.5 meters or so,
Thickness is very thin, and Lithology Discrimination is very big with earthquake prediction difficulty.Petroleum geology expert also is used for knowing without a kind of both at home and abroad at present
Not and prediction the dolomitic effective ways of lacustrine facies thin layer, simply qualitatively recognize and predict, the factor for theoretically considering compared with
It is many, there is no excessive consideration actual well drilled situation, i.e. well shake is not combined well, thus causes certain application office
Limit.Such as, 10 meters of earthquake prediction dolomite thickness, but actually drilling well dolomite thickness is by 0.5-1.5 meters of multi-thin-layer
What dolomite and mud stone alternating layers were constituted.
The content of the invention
In order to preferably lacustrine facies thin layer dolostone reservoirs are identified and are predicted, the present invention provide it is a kind of using it is qualitative with
Quantitative approach combines the earthquake prediction method for carrying out lacustrine facies thin layer dolostone reservoirs.
Specifically, including following technical scheme：
A kind of earthquake prediction method of lacustrine facies thin layer dolostone reservoirs, methods described includes：
Obtain the seismic data cube in target reservoir region and the petrographic thin section of individual well reservoir；
Micro-analysis is carried out to the petrographic thin section, the dolostone reservoirs distribution of the individual well reservoir is obtained；
The log of the individual well reservoir is obtained by logging method, with reference to the dolostone reservoirs point of the individual well reservoir
Cloth, obtains the log sensitive to the dolostone reservoirs reaction of the individual well reservoir；
According to the sensitive log of the dolostone reservoirs reaction to the individual well reservoir, well logging recognition mould is set up
Plate；
The well logging recognition template is loaded into the seismic data cube, the dolomite in the target reservoir region is predicted
The distribution of reservoir.
Preferably, it is described that micro-analysis is carried out to the petrographic thin section, obtain the dolostone reservoirs point of the individual well reservoir
Cloth includes：According to drill cores observation description mineralogical composition, content, cement type, the lithology of the individual well reservoir is differentiated, know
Do not go out the dolostone reservoirs distribution of the individual well reservoir.
Preferably, the means of the drill cores observation include：Petrographic thin section under mirror, casting body flake, fluorescence thin section analysis,
ESEM, cathodoluminescence analysis.
Further, the log sensitive to the dolostone reservoirs reaction of the individual well reservoir includes：From
Right gamma curve, interval transit time curve, compensated neutron curve, density curve and resistivity curve.
Further, the dolostone reservoirs to the individual well reservoir react corresponding to for the sensitive log
The individual well reservoir dolostone reservoirs distribution span be：The GR value of the natural gamma curve 30~
Between 60API, the sound wave value of the interval transit time curve between 210~270 μ s/m, in the compensation of the compensated neutron curve
Between 20~34PU, the density value of the density curve is in 2.35~2.65g/cm for subvalue3Between, the resistivity curve
Resistivity value is more than 6 Ω m.
Preferably, include for setting up the log of the well logging recognition template：When natural gamma curve, sound wave
Difference curve, density curve.
Preferably, it is for setting up the Mathematical Modeling of the well logging recognition template：Z=DEN/ (△ GR* (AC/ACmax)
4), wherein , ⊿ GR=(GR-GRmin)/(GRmax-GRmin)；
Z represents reconstruct curve values；
DEN refers to the density value under a certain desired depth of the individual well reservoir；
AC refers to the sound wave value under a certain desired depth of the individual well reservoir；
GR refers to the natural gamma value under a certain desired depth of the individual well reservoir；
ACmax refers to the maximum of the dolomite section sound wave of the individual well reservoir；
GRmax refers to the maximum of the dolomite section GR of the individual well reservoir；
GRmin refers to the minimum value of the dolomite section GR of the individual well reservoir.
Further, it is described that the well logging recognition template is loaded into the seismic data cube, predict the target storage
The distribution of the dolostone reservoirs in layer region includes：
After the well logging recognition template is loaded into the seismic data cube, explain described in the seismic data cube
The top bottom interface of the dolostone reservoirs in target reservoir region；
Extract it is described top bottom interface in seismic properties, the dolostone reservoirs in target reservoir region described in qualitative forecasting point
Cloth scope；
Application of Logging-constrained Inversion is carried out in the distribution, the dolostone reservoirs in target reservoir region described in quantitative forecast
Distribution.
The beneficial effect of technical scheme provided in an embodiment of the present invention：There is provided one kind prediction dolomite is combined by well shake
The earthquake prediction method of the lacustrine facies thin layer dolostone reservoirs of reservoir distribution.Specifically, first by with drill cores, thin slice number
According to, judge the type of individual well reservoir, then it is combined with the well-log information of individual well reservoir, foundation meets " lithology-electrical " rule
Well logging recognition masterplate, then carry out well shake combine, by seismic properties and Application of Logging-constrained Inversion carry out dolostone reservoirs it is qualitative with
Quantitative forecast.The predictable thickness in monolayer of Forecasting Methodology provided in an embodiment of the present invention is in 0.5-1.5 meters or so lacustrine facies thin layer white clouds
Rock reservoir, overcomes the limitation of thin layer dolomite seismic resolution, can accurately carry out thin layer dolostone reservoirs earthquake prediction, improves and bores
Well success rate.
Brief description of the drawings
Technical scheme in order to illustrate more clearly the embodiments of the present invention, below will be to that will make needed for embodiment description
Accompanying drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the present invention, for
For those of ordinary skill in the art, on the premise of not paying creative work, other can also be obtained according to these accompanying drawings
Accompanying drawing.
Fig. 1 is a kind of method flow of lacustrine facies thin layer dolostone reservoirs earthquake prediction method provided in an embodiment of the present invention
Figure.
Specific embodiment
To make technical scheme and advantage clearer, below in conjunction with accompanying drawing embodiment of the present invention is made into
One step ground is described in detail.Unless otherwise defined, all technical terms used by the embodiment of the present invention are respectively provided with and art technology
The identical implication that personnel are generally understood that.
The present invention provides a kind of earthquake prediction method of lacustrine facies thin layer dolostone reservoirs, and referring to Fig. 1, the method includes as follows
Step：
Step 101：Obtain the seismic data cube in target reservoir region and the petrographic thin section of individual well reservoir；
Specifically, can be blown out by field, receiver is received to obtain geological data, and the heart is carried out with computer in processes
The treatment of geological data, obtains corresponding seismic data cube.Obtain ground at the same time it can also data volume is added in interpretation software
Shake is explained.
The rock core or landwaste of target reservoir section by drilling well, can be collected, is chemically examined by specialty analysis and is polished into petrographic thin section,
Obtain the petrographic thin section of individual well reservoir.
Step 102：Micro-analysis is carried out to the petrographic thin section, the dolostone reservoirs distribution of the individual well reservoir is obtained；
Micro-analysis under mirror is carried out to individual well petrographic thin section using microscope.Can be thin by petrographic thin section, the body of casting under mirror
The data that obtain such as piece, fluorescence thin section analysis, ESEM, cathodoluminescence analysis describe the mineralogical composition of petrographic thin section, contain
Amount, cement type, differentiate lithology, structure and hole, the fractured situation of individual well reservoir, and then by different depth
The petrographic thin section at place carries out micro-analysis, identifies the dolostone reservoirs distribution of individual well reservoir.
Further, micro-analysis is carried out to some individual wells that bored in target reservoir region, target reservoir area can be obtained
The dolostone reservoirs distribution of some individual well reservoirs in domain.It should be noted that due to the whole district, drilling well is very more, and workload is very big,
So selecting several mouthfuls of representational wells to carry out micro-analysis under construction that also can be different from target area and sedimentation setting respectively.
Step 103：The log of the individual well reservoir is obtained by logging method, with reference to the white clouds of the individual well reservoir
Rock reservoir distribution, obtains the log sensitive to the dolostone reservoirs reaction of the individual well reservoir；
Specifically, after the deep degree of planned well is got into drilling well, it is possible to use the physical principle such as electricity, magnetic, sound, heat, core is manufactured
Various loggers, by logging cable G.I.H, ground electrical measuring instrument is continuously recorded with change in depth along pit shaft
Various parameters, obtain the log of individual well reservoir, and the log of all kinds of individual well reservoirs for obtaining can be used for recognizing underground
Rock stratum, such as oil, gas and water layer, coal seam, metalliferous deposit.
The log of the individual well reservoir that will be obtained by logging method, the dolostone reservoirs with individual well reservoir are distributed knot
Close, by way of comparing in same depth, the well logging sensitive to the dolostone reservoirs reaction of individual well reservoir can be obtained bent
Line.The curve sensitive to dolostone reservoirs reaction, can significantly reflect dolomitic characteristic on well-log information.Wherein, it is right
The curve that the dolostone reservoirs reaction of individual well reservoir is sensitive includes：(Gamma Ray curve, i.e. GR are bent for natural gamma curve
Line), interval transit time curve (Acoustic time curve, i.e. AC curves), compensated neutron curve (Compensation
Neutron curve, i.e. CN curves), density curve (Densimentric curve, i.e. DEN curves) and resistivity curve
(Resistivity curve, i.e. RT curves).The feature of the curve sensitive to the reaction of the dolostone reservoirs of individual well reservoir is：From
Right gamma GR curves are presented low state (30~60API), and interval transit time AC curves are in low state (210~270 μ s/m), are mended
Neutron CN curves are repaid in low state (20~34PU), density DEN curves show (2.35~2.65g/cm3), resistance in high level
Rate RT curves show (R in high level>6 Ω m), i.e. " three low two is high " state.
Step 104：According to the sensitive log of the dolostone reservoirs reaction to the individual well reservoir, well logging is set up
Recognition template；
AC, DEN, GR, RT, CN any one curve all cannot accurately, clearly recognize dolomite, accordingly, it would be desirable to reference to
Various curve matchings go out a dolomite indicatrix to be identified dolomite.Normally, may be selected AC, DEN, GR, RT,
Any 2~4 curves in CN, by different Mathematical Modelings, set up template, obtain different reconstruct Z value curves, by than
To Z values curve and dolomitic corresponding relation, most rational template is selected, as reflect dolomite " lithology-electrical " rule
Well logging recognition template.
It should be noted that during template is set up, by being possible to sensitively reflect dolomitic signature logging
Curve values are tried one's best amplification, will reflect that insensitive log value reduces to fit a white clouds as far as possible to dolomite lithology
Rock feature indicative curve, for recognizing dolomite stratigraph position.
In the present embodiment, selected Mathematical Modeling includes：
Model one：Z=10000*RT*DEN/ (AC*GR)；
Model two：Z=DEN*RT/ ((AC/AC mud) * △ GR)；
Model three：Z=DEN*/((AC/AC mud) * △ GR)；
Model four：Z=DEN/ (△ GR* (AC/ACmax) 4).
Wherein , ⊿ GR=(GR-GRmin)/(GRmax-GRmin)
Z represents reconstruct curve values；
AC refers to the sound wave value under a certain desired depth of individual well reservoir；
DEN refers to the density value under a certain desired depth of individual well reservoir；
RT refers to the resistivity value under a certain desired depth of individual well reservoir；
GR refers to the natural gamma value under a certain desired depth of individual well reservoir；
AC mud refers to the sound wave value of the muddy intercalation of individual well reservoir；
ACmax refers to the maximum of the dolomite section sound wave of individual well reservoir；
GRmax refers to the maximum of the dolomite section GR of individual well reservoir；
GRmin refers to the minimum value of the dolomite section GR of individual well reservoir；
Four kinds of Z value curves of model more than by calculating, are respectively compared different Z values curves and dolomitic relation
It is right, empirical tests, model four：The reconstruct curve Z values of Z=DEN/ (△ GR* (AC/ACmax) 4) are with dolomitic corresponding relation the most
Rationally, therefore the model is selected to set up the well logging recognition template of " lithology-electrically " rule.It is somebody's turn to do the well logging of " lithology-electrical " rule
Recognition template is relative to reduce GR value weights by increasing AC value weights, solves thin dolomite stratigraph GR values and receives shoulder effect larger,
Cause GR excessive, it is impossible to reflect the problem of dolomite lithology.The modelling effect preferably, can preferably separate transition rock and white clouds
Rock is separated, meanwhile, the dolomitic number of plies of Z Curves Recognitions, thickness are consistent with fixed well result, and dolomite thin layer is solved well
The problem of identification.
Reconstruct curve has uniform range, is easy to the whole district to compare.And reconstruct curve codomain is as small as possible, is easy to later stage earthquake solution
Release application.
In addition, during the well logging recognition template of " lithology-electrical " rule is set up, should be noted：
(1) model sets up key element：With model validation as first choice, based on petrophysical well logging reaction, build
Vertical pure mathematics model, does not consider the geological Significance of model temporarily.Link closely geological research analysis results, fully applies and embody white clouds
The characteristics of rock " three low two is high ".It is preferential to choose the log more sensitive to dolomite reaction, and (lithology is removed to ground environment
Insensitive log outward)；Reduce the weights of log easily affected by environment.Amplify dolomitic high-value signal (RT,
DEN), dolomite lower value signals (GR, AC) is reduced, it is therefore an objective to increase the electrical property difference of dolomite and other lithology.
(2) model optimum principle：Well logs are made full use of as far as possible.Improve the discrimination to thin layer.Subtract as far as possible
The non-rock character interference of few country rock interference and reduction stratum.It is convenient to carry out, reduce the influence for the treatment of people subjective factor.
Step 105：The well logging recognition template is loaded into the seismic data cube, the target reservoir region is predicted
Dolostone reservoirs distribution.
Specifically, after well logging recognition template is loaded into seismic data cube, the objective of interpretation reservoir in seismic data cube
The top bottom interface of the dolostone reservoirs in region；
Extract the seismic properties in the bottom interface of top, the distribution of the dolostone reservoirs in qualitative forecasting target reservoir region；
Application of Logging-constrained Inversion, the distribution model of the dolostone reservoirs in quantitative forecast target reservoir region are carried out in distribution
Enclose.
The predictable thickness in monolayer of method provided in an embodiment of the present invention is stored up in 0.5-1.5 meters or so lacustrine facies thin layer dolomite
Layer, overcomes the limitation of thin layer dolomite seismic resolution, can accurately carry out thin layer dolostone reservoirs earthquake prediction, improve drilling well into
Power.
The above is for only for ease of it will be understood by those skilled in the art that technical scheme, is not used to limit
The present invention.All any modification, equivalent substitution and improvements within the spirit and principles in the present invention, made etc., should be included in this
Within the protection domain of invention.
Claims (8)
1. a kind of earthquake prediction method of lacustrine facies thin layer dolostone reservoirs, it is characterised in that methods described includes：
Obtain the seismic data cube in target reservoir region and the petrographic thin section of individual well reservoir；
Micro-analysis is carried out to the petrographic thin section, the dolostone reservoirs distribution of the individual well reservoir is obtained；
The log of the individual well reservoir is obtained by logging method, is distributed with reference to the dolostone reservoirs of the individual well reservoir,
Obtain the log sensitive to the dolostone reservoirs reaction of the individual well reservoir；
According to the sensitive log of the dolostone reservoirs reaction to the individual well reservoir, well logging recognition template is set up；
The well logging recognition template is loaded into the seismic data cube, the dolostone reservoirs in the target reservoir region are predicted
Distribution.
2. method according to claim 1, it is characterised in that described that micro-analysis is carried out to the petrographic thin section, obtains
The dolostone reservoirs distribution of the individual well reservoir includes：According to drill cores observation description mineralogical composition, content, cementing species
Type, differentiates the lithology of the individual well reservoir, identifies the dolostone reservoirs distribution of the individual well reservoir.
3. method according to claim 2, it is characterised in that the means of the drill cores observation include：Rock under mirror
Thin slice, casting body flake, fluorescence thin section analysis, ESEM, cathodoluminescence analysis.
4. method according to claim 1, it is characterised in that the dolostone reservoirs reaction to the individual well reservoir is quick
The log of sense includes：Natural gamma curve, interval transit time curve, compensated neutron curve, density curve and resistivity
Curve.
5. method according to claim 4, it is characterised in that the dolostone reservoirs reaction to the individual well reservoir is quick
Sense the log corresponding to the individual well reservoir dolostone reservoirs distribution span be：The GR
The GR value of curve between 30~60API, the sound wave value of the interval transit time curve between 210~270 μ s/m, institute
The compensated neutron value of compensated neutron curve is stated between 20~34PU, the density value of the density curve is in 2.35~2.65g/
cm3Between, the resistivity value of the resistivity curve is more than 6 Ω m.
6. method according to claim 5, it is characterised in that the well logging for setting up the well logging recognition template is bent
Line includes：Natural gamma curve, interval transit time curve, density curve.
7. method according to claim 6, it is characterised in that the Mathematical Modeling for setting up the well logging recognition template
For：Z=DEN/ (△ GR* (AC/ACmax) 4), wherein , ⊿ GR=(GR-GRmin)/(GRmax-GRmin)；
Z represents reconstruct curve values；
DEN refers to the density value under a certain desired depth of the individual well reservoir；
AC refers to the sound wave value under a certain desired depth of the individual well reservoir；
GR refers to the natural gamma value under a certain desired depth of the individual well reservoir；
ACmax refers to the maximum of the dolomite section sound wave of the individual well reservoir；
GRmax refers to the maximum of the dolomite section GR of the individual well reservoir；
GRmin refers to the minimum value of the dolomite section GR of the individual well reservoir.
8. method according to claim 1, it is characterised in that described that the well logging recognition template is loaded into the earthquake
In data volume, predicting the distribution of the dolostone reservoirs in the target reservoir region includes：
After the well logging recognition template is loaded into the seismic data cube, the target is explained in the seismic data cube
The top bottom interface of the dolostone reservoirs of reservoir area；
Extract the seismic properties in the top bottom interface, the distribution model of the dolostone reservoirs in target reservoir region described in qualitative forecasting
Enclose；
Application of Logging-constrained Inversion is carried out in the distribution, the dolostone reservoirs in target reservoir region described in quantitative forecast point
Cloth scope.
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| CN116774285A (en) * | 2022-03-09 | 2023-09-19 | 中国石油化工股份有限公司 | Thin interbed prediction method, device, equipment and medium based on characteristic curve reconstruction |
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| CN112415596A (en) * | 2020-12-09 | 2021-02-26 | 大庆油田有限责任公司 | Dolomite structure type identification method based on logging information |
| CN116774285A (en) * | 2022-03-09 | 2023-09-19 | 中国石油化工股份有限公司 | Thin interbed prediction method, device, equipment and medium based on characteristic curve reconstruction |
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