CN108957532A - Method for predicting reservoir and device - Google Patents

Abstract

The present invention provides a kind of method for predicting reservoir and devices, this method comprises: carrying out Facies Control Modeling based on seismic data, obtain the initial impedance model of reservoir to be predicted；The initial impedance model is synthesized, the corresponding earthquake record of the initial impedance model is obtained；According to the corresponding earthquake record of the initial impedance model, judge whether the reservoir prediction that the reservoir to be predicted can be exported according to the initial impedance model as a result, in the case where the judgment result is yes, exporting reservoir prediction result according to the initial impedance model.The present invention can be improved reservoir prediction resolution ratio.

Description

Method for predicting reservoir and device

Technical field

The present invention relates to oil-gas exploration technical field more particularly to a kind of method for predicting reservoir and device.

Background technique

With the complication of oil-gas exploration and development object, oil-gas exploration and development is increasingly turned to multiple by constructivity Reservoir Development Miscellaneous hidden lithology and untraditional reservoir exploitation carry out the resolution ratio and precision of reservoir prediction using seismic data at the same time It needs higher and higher.Current portraying for thin reservoir is primarily present three prominent problems: (1) reservoir thickness in monolayer is thin, longitudinal mutual It is stacked；(2) reservoir cross directional variations are fast, uncertain strong between well；(3) low porosity and low permeability, porosity type multiplicity, and oil water relation is multiple It is miscellaneous.So how to improve thin reservoir prediction resolution ratio using seismic inversion and precision is exploration geophysics research One of hot and difficult issue problem.

In the past few decades, seismic inversion is continued to develop and is applied widely in petroleum exploration domain. Lindseth proposed recurrence inversion method in 1979, and this method is built upon the one-dimensional wave impedance of poststack based on convolution model On inverting, wave impedance information is rewritten as the form that subsurface formations reflection coefficient sequence is directly summed；Cook and Schneider Propose the inversion method based on model in nineteen eighty-three, this method first with well logging and seismic interpretation achievement establish comprising it is low, High frequency initial impedance model is neutralized, then seismic synthetic profile is made using positive algorithm, composite traces and actual seismic is cutd open Face is compared, and corrects initial model repeatedly, until composite traces and actual seismic section error are minimum, the impedance finally modified Model is inversion result；Bortoli, which is equal to 1992, proposes a kind of Inversion of geostatistics, Haas and Dubrule etc. It also proposed a kind of Inversion of geostatistics in 1994, this kind of method is first on the basis of constrained sparse spike inversion inverting On, seek lateral variogram, then calculate different lithology wave impedance probability density function and vertical variogram, finally with Seismic data is hard constraint, by Markov chain Monte Carlo simulation generate well between wave impedance and corresponding synthetic seismogram, It is iterated calculating using the method that nonlinear optimization solves, until synthetic seismogram matches well with original earthquake data, Obtain final invertomer.

The existing typical inversion method of three of the above respectively has advantage and disadvantage: recurrence inversion method calculating speed is fast, but by earthquake frequency The resolution limiting of band is low, unpredictable thin layer；Model inversion method and Inversion of geostatistics resolution ratio are higher, but anti- Low frequency and high frequency in drilling are all from well logging information, and difference of them is mainly modeling method difference, different modeling algorithms and modeling Parameter is all easy to cause the multi-solution of inversion result, although two methods have certain advantage to the identification of thin sand body, only fits For deposit stablize, well is more and the area of distribution uniform.

Summary of the invention

The present invention provides a kind of method for predicting reservoir and devices, to improve the resolution ratio of reservoir prediction.

The embodiment of the invention provides a kind of method for predicting reservoir, comprising: carries out Facies Control Modeling based on seismic data, obtains The initial impedance model of reservoir to be predicted；The initial impedance model is synthesized, it is corresponding to obtain the initial impedance model Earthquake record；According to the corresponding earthquake record of the initial impedance model, judging whether can be according to the initial impedance mould Type exports the reservoir prediction of the reservoir to be predicted as a result, in the case where the judgment result is yes, according to the initial impedance mould Type exports reservoir prediction result.

The embodiment of the invention also provides a kind of reservoir prediction devices, comprising: Facies Control Modeling unit is used for: being based on earthquake Data carry out Facies Control Modeling, obtain the initial impedance model of reservoir to be predicted；Earthquake record generation unit, is used for: to described first Beginning impedance model is synthesized, and the corresponding earthquake record of the initial impedance model is obtained；Prediction result determination unit, is used for: According to the corresponding earthquake record of the initial impedance model, judge whether can be exported according to the initial impedance model it is described to The reservoir prediction of predicting reservoir is as a result, in the case where the judgment result is yes, it is pre- to export reservoir according to the initial impedance model Survey result.

The embodiment of the invention also provides a kind of computer readable storage mediums, are stored thereon with computer program, the journey The step of above-described embodiment the method is realized when sequence is executed by processor.

The embodiment of the invention also provides a kind of computer equipments, including memory, processor and storage are on a memory And the computer program that can be run on a processor, the processor realize above-described embodiment the method when executing described program The step of.

Method for predicting reservoir, reservoir prediction device, computer readable storage medium and the computer of the embodiment of the present invention are set It is standby, Facies Control Modeling is carried out based on seismic data and obtains the initial impedance model of reservoir to be predicted, rather than is existed using log data Seismic horizon constraint is lower to carry out simple extrapolation and interpolation modeling.And during Facies Control Modeling, it can fully consider that geology is heavy Product background and seismic reflection inner link, so as to avoid using log data seismic horizon constraint under carry out extrapolation and The problem of log data is excessively relied on when interpolation models, therefore Facies Control Modeling modeling accuracy with higher, high-precision impedance Model can be improved the resolution ratio of reservoir prediction.

Detailed description of the invention

In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with It obtains other drawings based on these drawings.In the accompanying drawings:

Fig. 1 is the flow diagram of existing method for predicting reservoir.

Fig. 2 is the flow diagram of the method for predicting reservoir of one embodiment of the invention.

Fig. 3 is to carry out Facies Control Modeling based on seismic data in one embodiment of the invention to obtain the initial impedance of reservoir to be predicted The method flow schematic diagram of model.

Fig. 4 is to carry out lithofacies using multiple seismic properties based on log-petrofacies in one embodiment of the invention to predict to obtain to pre- Survey the method flow schematic diagram of the seismic facies of reservoir.

Fig. 5 is the flow diagram of the method for predicting reservoir of another embodiment of the present invention.

Fig. 6 is to carry out high resolution processing to primary earthquake data based on reservoir characteristic in one embodiment of the invention to obtain earthquake The method flow schematic diagram of data.

Fig. 7 is the reservoir for judging whether to export reservoir to be predicted in one embodiment of the invention according to initial impedance model The method flow schematic diagram of prediction result.

Fig. 8 is the flow diagram of the method for predicting reservoir of further embodiment of this invention.

Fig. 9 is the flow diagram of the method for predicting reservoir of yet another embodiment of the invention.

Figure 10 is the flow diagram of the method for predicting reservoir of a specific embodiment of the invention.

Figure 11 was the existing reservoir prediction result of blind shaft A and the comparison diagram of the method for the present invention reservoir prediction result.

Figure 12 is the comparison for testing the existing method reservoir prediction result and the method for the present invention reservoir prediction result of B well later Figure.

Figure 13 is the structural schematic diagram of the reservoir prediction device of one embodiment of the invention.

Figure 14 is the structural schematic diagram of Facies Control Modeling unit in one embodiment of the invention.

Figure 15 is the structural schematic diagram of seismic facies generation module in one embodiment of the invention.

Figure 16 is the structural schematic diagram of the reservoir prediction device of another embodiment of the present invention.

Figure 17 is the structural schematic diagram of high resolution processing unit in one embodiment of the invention.

Figure 18 is the structural schematic diagram of prediction result determination unit in one embodiment of the invention.

Figure 19 is the structural schematic diagram of the reservoir prediction device of further embodiment of this invention.

Figure 20 is the structural schematic diagram of the reservoir prediction device of yet another embodiment of the invention.

Specific embodiment

Understand in order to make the object, technical scheme and advantages of the embodiment of the invention clearer, with reference to the accompanying drawing to this hair Bright embodiment is described in further details.Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but simultaneously It is not as a limitation of the invention.

Fig. 1 is the flow diagram of existing method for predicting reservoir.As shown in connection with fig. 1, the prior art in layer position by controlling System is lower to be carried out interpolation or extrapolates to obtain composite traces using well-log information, and is sentenced by comparing composite traces and real seismic record Whether disconnected error reaches requirement, is learnt by those principles and its analyzing of applying effects to the prior art, in the prior art The high-resolution of inversion method is shaken mainly from well logging information, and when carrying out reservoir prediction, and the high frequency section of seismic inversion is big Majority is to obtain by the interpolation of well-log information radio-frequency component, extrapolation, or obtained by geological statistics stochastic simulation, to extrapolation mould Type dependence is strong, and the effect very little that seismic data itself constrains the high-resolution of Extrapolating model, this causes inversion result to solve more Property it is strong and very poor to the prediction effect of few well, the area that reservoir heterogeneity is strong, variation is fast.In view of the problems of the existing technology, Inventor is based on seismic data and proposes a kind of method for predicting reservoir by fully excavating the information of earthquake itself.Reservoir prediction Process can be seismic inversion process, so method for predicting reservoir is properly termed as seismic inversion method.

Fig. 2 is the flow diagram of the method for predicting reservoir of one embodiment of the invention.As shown in Fig. 2, the storage of the present embodiment Layer prediction method, it may include:

Step S110: Facies Control Modeling is carried out based on seismic data, obtains the initial impedance model of reservoir to be predicted；

Step S120: synthesizing the initial impedance model, obtains the corresponding earthquake note of the initial impedance model Record；

Step S130: according to the corresponding earthquake record of the initial impedance model, judging whether can be according to described initial Impedance model exports the reservoir prediction of the reservoir to be predicted as a result, in the case where the judgment result is yes, according to described initial Impedance model exports reservoir prediction result.

In above-mentioned steps S110, seismic data can be original seismic data, or pass through High-resolution Processing Seismic data.It can use existing method or improved method carry out Facies Control Modeling.It may include not in initial impedance model The same corresponding initial impedance of seismic channel.During Facies Control Modeling, it can fully consider that Geologic sedimentary background and earthquake are anti- Penetrate inner link.

In above-mentioned steps S120, the initial impedance in different earthquake road is carried out synthesizing available earthquake record, that is, is closed At record.The earthquake record obtained according to different initial impedance models is different.

In above-mentioned steps S130, existing method can use, that is, will be between earthquake record and real seismic record Difference is and pre- according to the reservoir whether error judgment exports the reservoir to be predicted according to the initial impedance model as error Survey result.Alternatively, can be by carrying out attributive analysis to earthquake record, and error is determined according to attributive analysis result, and according to Whether the error judgment exports the reservoir prediction result of the reservoir to be predicted according to the initial impedance model.Reservoir prediction result It may include reservoir thickness, reservoir physical parameter etc., reservoir physical parameter for example may include porosity, pore size etc..It can Reservoir prediction result is directly obtained or obtained indirectly according to initial impedance model.

In the present embodiment, Facies Control Modeling is carried out based on seismic data and obtains the initial impedance model of reservoir to be predicted, without It is to carry out simple extrapolation and interpolation under seismic horizon constraint using log data to model, can be avoided excessively dependence log data The problem of.During Facies Control Modeling, the inner link of Geologic sedimentary background and seismic reflection, therefore phase can be fully considered Control models modeling accuracy with higher, and high-precision impedance model can be improved the resolution ratio of reservoir prediction.

Fig. 3 is to carry out Facies Control Modeling based on seismic data in one embodiment of the invention to obtain the initial impedance of reservoir to be predicted The method flow schematic diagram of model.As shown in figure 3, above-mentioned steps S110, carries out Facies Control Modeling based on seismic data, obtains to pre- The method for surveying the initial impedance model of reservoir, it may include:

Step S111: attributive analysis is carried out using seismic data, obtains multiple seismic properties；

Step S112: being based on log-petrofacies, carries out lithofacies prediction using the multiple seismic properties, obtains reservoir to be predicted Seismic facies；

Step S113: the initial impedance model of the reservoir to be predicted is established under the phased constraint of the seismic facies.

In above-mentioned steps S111, multiple seismic properties may include the attributes such as amplitude class, frequency class.In above-mentioned steps In S112, which can refer to the lithofacies of fixed well.Based on log-petrofacies, can be deduced using the multiple seismic properties The lithofacies of reservoir to be predicted, such as the lithofacies set of pseudo- well location are to get to seismic facies.In above-mentioned steps S113, by institute The initial impedance model for establishing the reservoir to be predicted under the phased constraint of seismic facies is stated, Geologic sedimentary background and ground are established Shake the inner link of reflection.

In the present embodiment, based on log-petrofacies, lithofacies are predicted using a variety of seismic properties, analyze different lithofacies not With the variation tendency of depth, high-resolution, high-precision impedance model are established under phased constraint, are realized using using earthquake number Facies Control Modeling method is carried out according to much information.The process for carrying out Facies Control Modeling can be the process for carrying out reservoir modeling, according to resistance The anti-available Reservoir Parameter Models of model.

In other embodiments, above-mentioned steps S110 carries out Facies Control Modeling based on seismic data, obtains reservoir to be predicted The method of initial impedance model can be handled using deconvolution, open up the methods of frequency processing realization.

Fig. 4 is to carry out lithofacies using multiple seismic properties based on log-petrofacies in one embodiment of the invention to predict to obtain to pre- Survey the method flow schematic diagram of the seismic facies of reservoir.As shown in figure 4, above-mentioned steps S112, log-petrofacies are based on, using described Multiple seismic properties carry out lithofacies prediction, the method for obtaining the seismic facies of reservoir to be predicted, it may include:

Step S1121: being based on geologic setting, using log data and its explains that data carry out log-petrofacies analysis, obtains Log-petrofacies；

Step S1122: the log-petrofacies are based on, is analyzed using the multiple seismic properties, establishes log-petrofacies Relationship between seismic properties；

Step S1123: the earthquake rock of reservoir to be predicted is exported according to the relationship between the log-petrofacies and seismic properties Phase.

In above-mentioned steps S1121, which may include the geological condition of reservoir, such as rock, rock stratum, formation ring Border etc..The log-petrofacies are the lithofacies of reservoir position locating for fixed well.In above-mentioned steps S1122, log-petrofacies and seismic properties Between relationship can be linearly or nonlinearly relationship.In above-mentioned steps S1123, according to the log-petrofacies and seismic properties it Between relationship can deduce the seismic facies that pseudo- well location is set.

In the present embodiment, the Facies Control Modeling based on seismic multi-attribute is guidance with geologic setting, passes through a variety of well loggings and solution It releases data and carries out log-petrofacies analysis, establish the linear or non-thread of log-petrofacies and seismic properties using a variety of seismic attributes analysis Sexual intercourse, the seismic facies based on seismic properties prediction carry out the modeling of the impedance under phased guidance.

Fig. 5 is the flow diagram of the method for predicting reservoir of another embodiment of the present invention.As shown in figure 5, storage shown in Fig. 2 Layer prediction method, before above-mentioned steps S110, that is, Facies Control Modeling is carried out based on seismic data, obtains the first of reservoir to be predicted Before beginning impedance model, it may also include that

Step S140: being based on reservoir characteristic, carries out high resolution processing to primary earthquake data, obtains the seismic data.

In above-mentioned steps S140, based on reservoir characteristic carry out high resolution processing, be for target zone seismic data into Row high resolution processing, rather than handled for entire seismic profile, so having stronger specific aim.The high resolution processing It can use various existing high resolution processing methods to realize, or realized using improved high resolution processing.Primary earthquake data It can have higher signal quality after high resolution processing.In the case where original seismic data resolution is low, to the original There is seismic data to carry out the High-resolution Processing under constraining based on reservoir characteristic, the resolution ratio of seismic data can be improved.

Fig. 6 is to carry out high resolution processing to primary earthquake data based on reservoir characteristic in one embodiment of the invention to obtain earthquake The method flow schematic diagram of data.As shown in fig. 6, above-mentioned steps S140, is based on reservoir characteristic, primary earthquake data are carried out high Resolution processing, the method for obtaining the seismic data, it may include:

Step S141: the primary earthquake data by treating target zone in predicting reservoir carry out time frequency analysis, and to described Target zone carries out becoming reservoir thickness forward modeling, establishes the relationship of reservoir thickness and dominant frequency and bandwidth；

Step S142: frequency parameter is opened up in the relationship based on the reservoir thickness and dominant frequency and bandwidth, adjusting, described first to suppress Interference noise in beginning seismic data and the bandwidth for improving useful signal in the primary earthquake data.

In above-mentioned steps S141, the primary earthquake data by treating target zone in predicting reservoir carry out time frequency analysis, The thickness that can tentatively judge reservoir can further be predicted to store up by carrying out change reservoir thickness forward modeling to the target zone The thickness of layer, the result of integrated Time-frequency Analysis and change reservoir thickness forward modeling as a result, establishing reasonable reservoir thickness and master The relationship of frequency and bandwidth.Time frequency analysis and change reservoir thickness forward modeling are carried out for target zone, rather than for entire What seismic profile carried out, so, the high resolution processing method of the present embodiment considers reservoir characteristic, more targetedly.

In above-mentioned steps S142, the reservoir thickness and dominant frequency and the relationship of bandwidth include the pass of thickness degree and dominant frequency The relationship of system and reservoir thickness and bandwidth.Opening up frequency parameter for example may include dominant frequency, bandwidth etc..Foundation is adjusted because existing, reason Opening up frequency parameter by height-regulating on can be improved the resolution ratio of primary earthquake data, but actually since there are interference noise, institutes Frequency parameter is opened up unconfined cannot be turned up.Frequency parameter is opened up in relationship adjusting based on the reservoir thickness and dominant frequency and bandwidth, and Simultaneously in view of suppressing the interference noise in the primary earthquake data and improving useful signal in the primary earthquake data Bandwidth can achieve the purpose that rationally to adjust and open up frequency parameter.

In the present embodiment, high resolution processing is carried out based on reservoir characteristic constraint, mainly to original seismic data target zone Time frequency analysis is carried out, carries out Varying-thickness forward modeling for target zone, establishes the relationship of reservoir thickness and dominant frequency and bandwidth, and In the case where considering signal-to-noise ratio, frequency processing parameter is opened up in adjusting, is reached and is improved effectively under the premise of suppressing interference noise as far as possible The purpose of signal bandwidth.It is analyzed by reservoir Varying-thickness model Seismic forward technology, determines that suitable this area reservoir prediction is effective Seismic band range, using frequency handling principle is opened up, improved as far as possible effective on the basis of keeping original seismic data signal-to-noise ratio The energy of signal, the dominant frequency of seismic data and bandwidth can be significantly improved after treatment.Therefore, seismic data high score Resolution processing is that the inversion result of reservoir prediction has high-resolution one of the main reasons.It can be kept away by High-resolution Processing Exempt from conventional inverting high-resolution mainly from the radio-frequency component problem of well-log information.

Fig. 7 is the reservoir for judging whether to export reservoir to be predicted in one embodiment of the invention according to initial impedance model The method flow schematic diagram of prediction result.As shown in fig. 7, above-mentioned steps S130, correspondingly according to the initial impedance model Shake record, judges whether the side that the reservoir prediction result of the reservoir to be predicted can be exported according to the initial impedance model Method, it may include:

Step S131: seismic attributes analysis is carried out using the corresponding earthquake record of the initial impedance model, is obtained multiple Primary earthquake attribute；

Step S132: to multiple effective seismic properties in the multiple primary earthquake attribute by corresponding weight coefficient into Row weighted sum, the prediction seismic properties after being weighted；

Step S133: earthquake category is calculated according to the actual seismic attribute after the prediction seismic properties and weighting after the weighting Property error；Wherein, the actual seismic attribute after the weighting is multiple effective earthquakes according to multiple actual seismic attributes Attribute is weighted summation by corresponding weight coefficient and obtains, and the multiple actual seismic attribute is according to the earthquake number It is obtained according to attributive analysis is carried out；

Step S134: whether setting error amount is less than according to the seismic properties error, judging whether can be according to described Initial impedance model exports the reservoir prediction result of the reservoir to be predicted.

Constraint condition is arranged in weighted sum based on multiple seismic properties, and judging whether can be according to the initial impedance model The reservoir prediction of the reservoir to be predicted is exported as a result, rather than only considering single seismic properties or individually considering multiple earthquake categories Constraint condition is arranged in property, so the precision of reservoir prediction can not only be improved, while the more of inversion result can also be effectively reduced Xie Xing.

In the present embodiment, based on the initial impedance model under phased guidance, synthesis earthquake is made using positive algorithm Section and the effective earthquake combinations of attributes of extraction will be missed compared with the combinations of attributes weighting corresponding with actual seismic road of these attributes Difference.Error is relatively determined by the weighting of a variety of attribute informations, has been comprehensively considered a variety of seismic properties, rather than has been remembered according only to synthesis It records and determines error, so the error that this kind of method determines is more accurate, so as to further increase the precision of reservoir prediction, effectively Reduce the multi-solution of inversion result.

It, can be by correcting initial impedance model repeatedly, until the seismic properties group of the earthquake record of synthesis in embodiment Close with actual seismic road combinations of attributes weighted error it is minimum until, the impedance model that obtains at this time as final inversion result, with This can make reservoir prediction meet setting error requirements, to further increase the resolution ratio of reservoir prediction.

Fig. 8 is the flow diagram of the method for predicting reservoir of further embodiment of this invention.As shown in figure 8, storage shown in Fig. 2 Layer prediction method may also include that

Step S150: the reservoir prediction of the reservoir to be predicted can not be exported according to the initial impedance model in judgement As a result in the case where, the initial impedance model is modified, modified impedance model is obtained；

Step S120 ': synthesizing the modified impedance model, and it is corresponding to obtain the modified impedance model Earthquake record；

Step S130 ': according to the corresponding earthquake record of the modified impedance model, judging whether can be according to described Modified impedance model exports the reservoir prediction of the reservoir to be predicted as a result, in the case where the judgment result is yes, according to The modified impedance model exports reservoir prediction result.

Above-mentioned steps S120 ' and step S130 ' is to repeat to hold using modified impedance model replacement preliminary examination impedance model The process of row step S120 and step S130.Above-mentioned steps S120 ' and step S130 ' specific embodiment are referred to step The embodiment of S120 and step S130 execute.It is obtaining initial impedance model and is modifying the process of the initial impedance model In, quantification Reservoir Parameter Models, so, the present embodiment is able to carry out the reservoir prediction of quantification.

It, can be by constantly modifying impedance model in the present embodiment, and synthetic seismogram again, and rejudge and be The no reservoir prediction that the reservoir to be predicted can be exported according to the modified impedance model as a result, successively iteration carry out, Until judging result be it is yes, reservoir prediction result is exported according to the modified impedance model.It is hindered by optimizing iterative modifications Anti- model can find the impedance model met the requirements.

Fig. 9 is the flow diagram of the method for predicting reservoir of yet another embodiment of the invention.As shown in figure 9, storage shown in Fig. 2 Layer prediction method may also include that

Step S160: it is theoretical based on log data and rock physics, determine the multiple effective seismic properties and the phase The weight coefficient answered.

Above-mentioned steps S160, it is theoretical based on log data and rock physics, obtain the multiple effective seismic properties and institute State corresponding weight coefficient, it may include:

Step S161: the geological model of the reservoir to be predicted is generated according to log data；

Step S162: the geophysical model of the reservoir to be predicted is established according to the geological model；

Step S163: it is based on rock physics theory and the geophysical model, establishes the reservoir of the reservoir to be predicted Parameter model；

Step S164: it is screened to obtain the multiple effective earthquake category sensitive to reservoir according to the Reservoir Parameter Models Property, and be that the weight coefficient is arranged in each effective seismic properties according to the sensitive degree of reservoir.

In above-mentioned steps S163, specifically, it can be established under rock physics guidance based on the geophysical model Variation relation between reservoir properties and reservoir spread speed further obtains the relationship between physical property, speed and density, according to Relationship between speed and density establishes impedance model, to obtain Reservoir Parameter Models.

In above-mentioned steps S164, specifically, composite traces can be obtained according to impedance model, be carried out according to composite traces Attributive analysis obtains seismic properties, judges which seismic properties to reservoir thickness using the figure that crosses of seismic properties and reservoir properties Sensitivity, and degree that can be sensitive to reservoir thickness according to seismic properties assign a corresponding weight coefficient to the seismic properties. Above-mentioned seismic properties for example can be the attributes such as amplitude class, frequency class.The dominant frequency of seismic data after determining high resolution processing and Then bandwidth determines Varying-thickness and varied property parameter model, the available property set sensitive to reservoir.

In the present embodiment, it is guidance with rock physics theory, carries out the physical parameters mould such as reservoir Varying-thickness and variable orifice porosity Type Seismic forward, analysis forward modeling seismic channel attribute and reservoir thickness transitivity Parameter Variation, it is excellent according to the size of correlation A variety of effective earthquake combinations of attributes are selected, and assign different weight coefficients, the bigger weight coefficient of correlation to the seismic properties preferably gone out It is bigger, on the contrary it is smaller.Due to considering rock physics theory, so the Reservoir Parameter Models for the reservoir to be predicted established are more smart Really.On the basis of the model Seismic forward based on reservoir characteristic, preferred a variety of effective attributes out, and utilize a variety of effective earthquake categories Property weighted iteration constrain the inverting condition of convergence jointly, improve conventional impedance model inversion merely with seismic amplitude information for convergence The limitation of constraint.Due to consideration that a variety of attributes and reservoir change relevant earthquake information, therefore improving the same of inversion accuracy When the multi-solution of inversion result can be effectively reduced.

The purpose of the present invention, implementation process and effect are illustrated with a specific embodiment below.

Exploration practices the result shows that: most of the high frequency section of existing seismic inversion is by well-log information radio-frequency component Interpolation, extrapolation, or the result by geological statistics stochastic simulation.Seismic data itself to the effect of the high-resolution of model constraint very It is small, therefore cause inversion result multi-solution strong and poor to few well, reservoir heterogeneity is strong, variation is fast regional prediction effect.It is based on This, the present embodiment proposes a kind of reservoir quantification prediction technique, that is, the high score under multidimensional information constraint of the kind based on reservoir characteristic Resolution seismic inversion method.Based on seismic data, the information of earthquake itself is fully excavated, research and development do not rely on well-log information excessively Seismic inversion method, with reduce inversion result multi-solution, improve the vertical resolution of thin layer, cross directional variations predictive ability and Reservoir properties quantitatively characterizing ability has important theory significance and practical value.The method of the present embodiment inherits conventional reservoir Prediction technique basic procedure, while larger improve and perfect has been done to some key technologies aspects.For example, in original seismic data In the case that resolution ratio is low, High-resolution Processing is carried out to seismic data based on reservoir characteristic constraint；In terms of reservoir modeling, answer Facies Control Modeling is carried out with seismic data much information；In the condition of inverting iteration convergence, by earthquakes categories such as amplitude class, frequency classes Property class carry out aggregative weighted summation to calculate error, and using the error as iterative constrained condition.Skill is improved eventually by these Art can not only effectively improve reservoir prediction resolution ratio and precision, and inversion result is greatly reduced well-log information dependence, It is applicable in the area that well-log information is few, reservoir heterogeneity is strong, variation is fast.

Figure 10 is the flow diagram of the method for predicting reservoir of a specific embodiment of the invention.As shown in Figure 10, this implementation The method for predicting reservoir of example is the High-resolution Seismic Inversion method under the multidimensional information constraint based on reservoir characteristic, improvement It is main to include four aspects: first is that, based on the high resolution processing under reservoir characteristic constraint, the content of this aspect is mainly to original Seismic data target zone carries out time frequency analysis, carries out Varying-thickness forward modeling for target zone, establish reservoir thickness and dominant frequency with The relationship of bandwidth, in the case where considering signal-to-noise ratio, frequency processing parameter is opened up in adjusting, is reached as far as possible before suppressing interference noise Put the purpose for improving useful signal bandwidth；Second is that being based on seismic multi-attribute Facies Control Modeling technology, this aspect is to the effect that It is guidance with geologic setting, carries out log-petrofacies analysis by a variety of well loggings and interpretation data (known log data), using more Kind seismic attributes analysis establishes the linearly or nonlinearly relationship of log-petrofacies and seismic properties, the earthquake based on seismic properties prediction Lithofacies carry out the modeling of the impedance under phased guidance；Third is that being guidance with rock physics theory, carry out reservoir Varying-thickness and variable orifice gap The parameter models Seismic forwards such as degree, analysis forward modeling seismic channel attribute and reservoir thickness transitivity Parameter Variation, according to correlation Property size preferably a variety of effective earthquake combinations of attributes, and to preferably go out seismic properties assign different weight coefficients, correlation Bigger weight coefficient is bigger, conversely, smaller；Fourth is that utilizing positive algorithm system based on the initial impedance model under phased guidance Make seismic synthetic profile and extract effective earthquake combinations of attributes, these attributes combinations of attributes corresponding with actual seismic road is weighted Compare, correct initial model repeatedly, until composite traces seismic properties are combined with actual seismic road combinations of attributes weighted error most Until small, the impedance model obtained at this time is final inversion result.

The method of the embodiment inherits conventional the advantages of being based on model inversion, while generally depositing for "current" model inverting The problem of propose corresponding technological improvement, preferable effect is mainly achieved in terms of following three:

First, the method for embodiment seismic inversion resolution ratio with higher.Just by the earthquake of reservoir Varying-thickness model The analysis of artistic skills art determines the suitable effective seismic band range of this area reservoir prediction, is keeping original seismic data signal-to-noise ratio On the basis of, using frequency handling principle is opened up, the energy of useful signal is improved as far as possible, after treatment the dominant frequency and frequency of seismic data Width is all significantly improved.Therefore, High resolution seismic data processing is that the high-resolution of this method inversion result is mainly former One of because, conventional inverting high-resolution is avoided mainly from the radio-frequency component problem of well-log information.

Second, the method for embodiment modeling accuracy with higher.High-precision initial impedance model is model inversion Key.The present embodiment predicts lithofacies based on log-petrofacies, using a variety of seismic properties, analyzes different lithofacies in different depths The variation tendency of degree establishes high-resolution and high-precision impedance model under phased constraint.Due in modeling process, fully Geologic sedimentary background and seismic reflection inner link are considered, is avoided simple outer under seismic horizon constraint using well-log information It pushes away and lays a good foundation with interpolation modeling problem, therefore this method modeling accuracy with higher for high-resolution reservoir prediction.

The multi-solution of inversion result can be effectively reduced in the method for third, the embodiment.The present embodiment is being based on reservoir On the basis of the model Seismic forward of feature, preferred a variety of effective attributes out, and innovatively propose and utilize a variety of effective earthquake categories Property weighted iteration constrain the inverting condition of convergence jointly, improve conventional impedance model inversion merely with seismic amplitude information for convergence The limitation of constraint.Due to consideration that a variety of and reservoir changes relevant earthquake information, therefore the inversion method of the present embodiment is mentioning The multi-solution of inversion result can be effectively reduced while high inversion accuracy.

The method of the present embodiment, main flow are divided into two steps: first is that establishing the earthquake of reservoir characteristic parameter just by geological model It drills, preferably the seismic properties set of reservoir parameter sensitivity；Second is that time frequency analysis and High-resolution Processing are carried out to seismic data, It is established under phased constraint on the basis of initial impedance model, composite traces is made by Seismic forward method and analyzes its earthquake category Property set and actual seismic data attribute set weighting compare, using iteration optimizing algorithm modify impedance model, until the two category Property set weighted error it is minimum until.On the basis of traditional seismic inversion thinking, a variety of seismic properties such as amplitude, frequency are introduced Rate, phase etc. and reservoir relevant information are that constraint condition by iteration optimizing and attribute weight method makes forward modeling synthetically Shake data is most preferably coincide in amplitude and other attribute informations earthquake attribute weight corresponding with actual seismic data, final pattern number According to being inversion result.Therefore, the method for the present embodiment, the multidimensional information based on reservoir characteristic constrain lower seismic inversion new method It can effectively improve the resolution ratio and precision of prediction of inverting, the ground few suitable for well-log information, reservoir heterogeneity is strong, variation is fast Area.

In an Application Example, using the method for the embodiment of the present invention to certain domestic oil field block Quaternary Period clast Rock thin interbed has carried out reservoir prediction test.The shallower block target zone buried depth is 200~1000m, and depositional environment is shore Vlei It mutually deposits, develops the storage lid combination of shore Vlei ach-bar sandbody and shore Vlei mud.Based on reservoir lithology siltstone, sand shale on longitudinal direction Thin interbed is developed very much, but reservoir single thin layer, based on 0.5~2m, lateral reservoir variation is fast.Figure 11 was the existing storage of blind shaft A The comparison diagram of layer prediction result and the method for the present invention reservoir prediction result.As shown in figure 11, (a) was partially blind shaft A routine mould Type seismic inversion, (b) be partially blind shaft A it is of the invention based on reservoir characteristic multidimensional information constraint under high-resolution Seismic inversion.It can be seen that conventional model resolution of inversion is low from the comparison in Figure 11, unpredictable area storage in transverse direction Layer distribution, well point prediction result and actual well drilled are coincide poor；Using the method for the present invention it can be seen that resolution of inversion obviously compared with Height, well point earthquake prediction reservoir thickness and position and actual well drilled all coincide preferably, and reservoir distribution is clear in transverse direction, entire earthquake Inverting section fine description reservoir transverse direction heterogeneity is strong, changes fast rule, prediction result and practical geological knowledge it is identical compared with It is good.Efficiency of inverse process inspection is carried out to 15 mouthfuls of blind shafts of the whole district using the method for the present invention, statistical result shows that reservoir prediction thickness is kissed Conjunction rate is up to 92% or more.

In another Application Example, certain external oil field block Jurassic system carbonate rock is stored up using the method for the present invention Layer has carried out reservoir prediction test.The block target zone buried depth is 3000~4000m, and depositional environment is that platform margin~leading edge is oblique Slope mutually deposits, organic reef and beach development.Based on target zone lithology grainstone, a set of thin mud stone is developed close to target zone top, With a thickness of 1~10m；It more than mud stone develops three sets of huge thick cream rock stratum and presss from both sides two sets of rock salts, formation thickness changes greatly.By cream rock and salt Rock influences, and local area seismic data quality is poor, and resolution ratio and signal-to-noise ratio are low, and target zone top structure explains that difficulty is big.Due to top Mud stone is although thin, but the whole district develops, therefore utilizes this set mud stone of High-resolution Seismic Inversion technological prediction of the present invention, further falls Real local area target zone top structure.

Figure 12 is the comparison for testing the existing method reservoir prediction result and the method for the present invention reservoir prediction result of B well later Figure.As shown in figure 12, (a) part figure is to test B well common seismic section and target zone top, bottom structure interpretation, (b) part figure later Section is predicted for the high-resolution mud stone under the multidimensional information constraint of the invention based on reservoir characteristic.From mud stone prediction section Analysis, it is larger that target zone top structure should be red locations and existing explanation difference in figure.B well is posteriority well, shakes and marks by well After fixed, mud stone earthquake prediction position and thickness and actual well drilled coincide preferably, and mud stone thickness is only 2m at the top of the well target zone.Benefit Efficiency of inverse process inspection is carried out to 25 mouthfuls of blind shafts of the whole district and 5 mouthfuls of fixed wells with the method for the present invention, statistical result shows that mud stone is predicted Position and the identical rate of thickness are up to 90% or more.

Therefore, pass through two above application example effect analysis, the results showed that the multidimensional information constraint based on reservoir characteristic Under High-resolution Seismic Inversion new method effectively increase the vertical resolution of thin layer, cross directional variations predictive ability and storage Layer physical property quantitatively characterizing ability, to instruct next step exploration and development have important theory significance and practical value.

Based on inventive concept identical with method for predicting reservoir shown in Fig. 2, the embodiment of the present application also provides a kind of storages Layer prediction means, as described in following example.The principle and method for predicting reservoir phase solved the problems, such as due to the reservoir prediction device Seemingly, therefore the implementation of the reservoir prediction device may refer to the implementation of method for predicting reservoir, and overlaps will not be repeated.

Figure 13 is the structural schematic diagram of the reservoir prediction device of one embodiment of the invention.As shown in figure 13, the present embodiment Reservoir prediction device, it may include: Facies Control Modeling unit 210, earthquake record generation unit 220 and prediction result determination unit 230, Above-mentioned each unit is linked in sequence.

Facies Control Modeling unit 210, is used for: carrying out Facies Control Modeling based on seismic data, obtains the initial resistance of reservoir to be predicted Anti- model；

Earthquake record generation unit 220, is used for: synthesizing to the initial impedance model, obtains the initial impedance The corresponding earthquake record of model；

Prediction result determination unit 230, is used for: according to the corresponding earthquake record of the initial impedance model, judging whether The reservoir prediction of the reservoir to be predicted can be exported according to the initial impedance model as a result, the case where judging result, which is, is Under, reservoir prediction result is exported according to the initial impedance model.

Figure 14 is the structural schematic diagram of Facies Control Modeling unit in one embodiment of the invention.As shown in figure 14, described phased to build Form unit 220, it may include: seismic properties generation module 221, seismic facies generation module 222 and impedance model generation module 223, above-mentioned each sequence of modules connection.

Seismic properties generation module 221, is used for: carrying out attributive analysis using seismic data, obtains multiple seismic properties；

Seismic facies generation module 222, is used for: being based on log-petrofacies, it is pre- to carry out lithofacies using the multiple seismic properties It surveys, obtains the seismic facies of reservoir to be predicted；

Impedance model generation module 223, is used for: the reservoir to be predicted is established under the phased constraint of the seismic facies Initial impedance model.

Figure 15 is the structural schematic diagram of seismic facies generation module in one embodiment of the invention.As shown in figure 15, describedly Shake lithofacies generation module 222, it may include: log-petrofacies generation module 2221, lithofacies and relation on attributes establish module 2222 and ground Shake lithofacies output module 2223, above-mentioned each sequence of modules connection.

Log-petrofacies generation module 2221, is used for: being based on geologic setting, using log data and its explains that data are surveyed Well lithofacies analysis, obtains log-petrofacies；

Lithofacies and relation on attributes establish module 2222, are used for: being based on the log-petrofacies, utilize the multiple seismic properties It is analyzed, establishes the relationship between log-petrofacies and seismic properties；

Seismic facies output module 2223, is used for: according between the log-petrofacies and seismic properties relationship output to The seismic facies of predicting reservoir.

Figure 16 is the structural schematic diagram of the reservoir prediction device of another embodiment of the present invention.As shown in figure 16, shown in Figure 13 Reservoir prediction device, may also include that high resolution processing unit 240, connect with Facies Control Modeling unit 210.

High resolution processing unit 240, is used for: being based on reservoir characteristic, carries out high resolution processing to primary earthquake data, obtain The seismic data.

Figure 17 is the structural schematic diagram of high resolution processing unit in one embodiment of the invention.As shown in figure 17, the high score Distinguish processing unit 240, it may include: thickness and dominant frequency and bandwidth relationship establish module 241 and open up frequency parameter adjustment module 242, and two Person is connected with each other.

Thickness and dominant frequency and bandwidth relationship establish module 241, are used for: by treating in predicting reservoir target zone initially Shake data and carry out time frequency analysis, and the target zone is carried out to become reservoir thickness forward modeling, establish reservoir thickness and dominant frequency and The relationship of bandwidth；

Open up frequency parameter adjustment module 242, be used for: frequency is opened up in the relationship based on the reservoir thickness and dominant frequency and bandwidth, adjusting Parameter, to suppress the interference noise in the primary earthquake data and improve the frequency of useful signal in the primary earthquake data It is wide.

Figure 18 is the structural schematic diagram of prediction result determination unit in one embodiment of the invention.As shown in figure 18, described pre- Survey result determination unit 230, it may include: initial attribute generation module 231, weight estimation attribute generation module 232, attribute error Generation module 233 and prediction result determining module 234, above-mentioned each sequence of modules connection.

Initial attribute generation module 231, is used for: carrying out earthquake category using the corresponding earthquake record of the initial impedance model Property analysis, obtain multiple primary earthquake attributes；

Weight estimation attribute generation module 232, is used for: to multiple effective earthquake categories in the multiple primary earthquake attribute Property is weighted summation by corresponding weight coefficient, the prediction seismic properties after being weighted；

Attribute error generation module 233, is used for: according to after the weighting prediction seismic properties and weighting after practically It shakes attribute and calculates seismic properties error；Wherein, the actual seismic attribute after the weighting is according in multiple actual seismic attributes The multiple effective seismic properties are weighted summation by corresponding weight coefficient and obtain, the multiple actual seismic attribute It is to carry out attributive analysis according to the seismic data to obtain；

Prediction result determining module 234, is used for: whether being less than setting error amount according to the seismic properties error, judges Whether the reservoir prediction result of the to be predicted reservoir can be exported according to the initial impedance model.

Figure 19 is the structural schematic diagram of the reservoir prediction device of further embodiment of this invention.As shown in figure 19, shown in Figure 13 Reservoir prediction device, may also include that impedance model modification unit 240, earthquake record re-generate unit 220 ' and prediction result Weight determination unit 230 ', above-mentioned each sequence of modules connection.

Impedance model modifies unit 240, is used for: can not be exported according to the initial impedance model in judgement described to pre- In the case where the reservoir prediction result for surveying reservoir, the initial impedance model is modified, modified impedance model is obtained；

Earthquake record re-generates unit 220 ', is used for: synthesizing to the modified impedance model, obtains described repair The corresponding earthquake record of impedance model after changing；

Prediction result weight determination unit 230 ', is used for: according to the corresponding earthquake record of the modified impedance model, sentencing It is disconnected that the reservoir prediction of the reservoir to be predicted whether can be exported according to the modified impedance model as a result, in judging result In the case where being, reservoir prediction result is exported according to the modified impedance model.

Figure 20 is the structural schematic diagram of the reservoir prediction device of yet another embodiment of the invention.As shown in figure 20, shown in Figure 13 Reservoir prediction device, may also include that effective attribute and weight determining unit 250, be connected to 220 He of earthquake record generation unit Between prediction result determination unit 230.

Effective attribute and weight determining unit 250, are used for: it is theoretical based on log data and rock physics, it determines described more A effective seismic properties and corresponding weight coefficient.

Wherein, effective attribute and weight determining unit 250, it may include: geological model generation module 251, earth object Reason model generation module 252, Reservoir Parameter Models establish module 253 and effectively attribute and weight generation module 254, above-mentioned each mould Block is linked in sequence.

Geological model generation module 251, is used for: the geological model of the reservoir to be predicted is generated according to log data；

Geophysical model generation module 252, is used for: the earth of the reservoir to be predicted is established according to the geological model Physical model；

Reservoir Parameter Models establish module 253, are used for: being based on rock physics theory and the geophysical model, establish The Reservoir Parameter Models of the reservoir to be predicted；

Effective attribute and weight generation module 254, are used for: screening to obtain according to the Reservoir Parameter Models sensitive to reservoir The multiple effective seismic properties, and be that the weight is arranged in each effective seismic properties according to the sensitive degree of reservoir Coefficient.

The embodiment of the present invention also provides a kind of computer readable storage medium, is stored thereon with computer program, the program The step of the various embodiments described above the method is realized when being executed by processor.

The embodiment of the present invention also provides a kind of computer equipment, including memory, processor and storage are on a memory simultaneously The computer program that can be run on a processor, the processor realize the various embodiments described above the method when executing described program The step of.

In conclusion the method for predicting reservoir of the embodiment of the present invention, reservoir prediction device, computer readable storage medium and Computer equipment carries out Facies Control Modeling based on seismic data and obtains the initial impedance model of reservoir to be predicted, rather than utilizes and survey Well data carry out simple extrapolation and interpolation modeling under seismic horizon constraint.And during Facies Control Modeling, it can fully examine Consider Geologic sedimentary background and seismic reflection inner link, so as to avoid using log data seismic horizon constraint under into The problem of excessively relying on log data when row extrapolation and interpolation modeling, therefore Facies Control Modeling modeling accuracy with higher, it is high-precision The impedance model of degree can be improved the resolution ratio of reservoir prediction.Further, primary earthquake data are carried out based on reservoir characteristic high Resolution handles to obtain the seismic data, and the resolution ratio of seismic data can be improved.Further, it is based on multiattribute weighted sum Judge whether that the reservoir prediction of the reservoir to be predicted can be exported according to initial impedance model as a result, it is possible to which prediction is effectively reduced The multi-solution of inversion result in the process.

In the description of this specification, reference term " one embodiment ", " specific embodiment ", " some implementations Example ", " such as ", the description of " example ", " specific example " or " some examples " etc. mean it is described in conjunction with this embodiment or example Particular features, structures, materials, or characteristics are included at least one embodiment or example of the invention.In the present specification, Schematic expression of the above terms may not refer to the same embodiment or example.Moreover, the specific features of description, knot Structure, material or feature can be combined in any suitable manner in any one or more of the embodiments or examples.Each embodiment Involved in the step of sequence be used to schematically illustrate implementation of the invention, sequence of steps therein is not construed as limiting, can be as needed It appropriately adjusts.

It should be understood by those skilled in the art that, the embodiment of the present invention can provide as method, system or computer program Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the present invention, which can be used in one or more, The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces The form of product.

The present invention be referring to according to the method for the embodiment of the present invention, the process of equipment (system) and computer program product Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates, Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or The function of being specified in multiple boxes.

These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one The step of function of being specified in a box or multiple boxes.

Particular embodiments described above has carried out further in detail the purpose of the present invention, technical scheme and beneficial effects Describe in detail it is bright, it should be understood that the above is only a specific embodiment of the present invention, the guarantor being not intended to limit the present invention Range is protected, all within the spirits and principles of the present invention, any modification, equivalent substitution, improvement and etc. done should be included in this Within the protection scope of invention.

Claims (18)

1. a kind of method for predicting reservoir characterized by comprising

Facies Control Modeling is carried out based on seismic data, obtains the initial impedance model of reservoir to be predicted；

The initial impedance model is synthesized, the corresponding earthquake record of the initial impedance model is obtained；

According to the corresponding earthquake record of the initial impedance model, judge whether that institute can be exported according to the initial impedance model The reservoir prediction of reservoir to be predicted is stated as a result, in the case where the judgment result is yes, exporting and storing up according to the initial impedance model Layer prediction result.

2. method for predicting reservoir as described in claim 1, which is characterized in that carry out Facies Control Modeling based on seismic data, obtain The initial impedance model of reservoir to be predicted, comprising:

Attributive analysis is carried out using seismic data, obtains multiple seismic properties；

Based on log-petrofacies, lithofacies prediction is carried out using the multiple seismic properties, obtains the seismic facies of reservoir to be predicted；

The initial impedance model of the reservoir to be predicted is established under the phased constraint of the seismic facies.

3. method for predicting reservoir as claimed in claim 2, which is characterized in that be based on log-petrofacies, utilize the multiple earthquake Attribute carries out lithofacies prediction, obtains the seismic facies of reservoir to be predicted, comprising:

Based on geologic setting, using log data and its explains that data carry out log-petrofacies analysis, obtain log-petrofacies；

Based on the log-petrofacies, is analyzed, established between log-petrofacies and seismic properties using the multiple seismic properties Relationship；

The seismic facies of reservoir to be predicted are exported according to the relationship between the log-petrofacies and seismic properties.

4. method for predicting reservoir as described in claim 1, which is characterized in that carry out Facies Control Modeling based on seismic data, obtain Before the initial impedance model of reservoir to be predicted, further includes:

Based on reservoir characteristic, high resolution processing is carried out to primary earthquake data, obtains the seismic data.

5. method for predicting reservoir as claimed in claim 4, which is characterized in that be based on reservoir characteristic, to primary earthquake data into Row high resolution processing obtains the seismic data, comprising:

Primary earthquake data by treating target zone in predicting reservoir carry out time frequency analysis, and carry out change storage to the target zone Thickness degree forward modeling establishes the relationship of reservoir thickness and dominant frequency and bandwidth；

Relationship based on the reservoir thickness and dominant frequency and bandwidth, frequency parameter is opened up in adjusting, to suppress in the primary earthquake data Interference noise and improve the bandwidth of useful signal in the primary earthquake data.

6. method for predicting reservoir as described in claim 1, which is characterized in that according to the corresponding earthquake of the initial impedance model Record, judges whether the reservoir prediction result that the reservoir to be predicted can be exported according to the initial impedance model, comprising:

Seismic attributes analysis is carried out using the corresponding earthquake record of the initial impedance model, obtains multiple primary earthquake attributes；

Summation is weighted by corresponding weight coefficient to multiple effective seismic properties in the multiple primary earthquake attribute, is obtained Prediction seismic properties after to weighting；

Seismic properties error is calculated according to the actual seismic attribute after the prediction seismic properties and weighting after the weighting；Wherein, Actual seismic attribute after the weighting is multiple effective seismic properties according to multiple actual seismic attributes by the phase The weight coefficient answered is weighted summation and obtains, and the multiple actual seismic attribute is to carry out attribute point according to the seismic data Analysis obtains；

Whether it is less than setting error amount according to the seismic properties error, judging whether can be defeated according to the initial impedance model The reservoir prediction result of the reservoir to be predicted out.

7. method for predicting reservoir as described in claim 1, which is characterized in that further include:

In the case where judgement can not export the reservoir prediction result of the reservoir to be predicted according to the initial impedance model, The initial impedance model is modified, modified impedance model is obtained；

The modified impedance model is synthesized, the corresponding earthquake record of the modified impedance model is obtained；

According to the corresponding earthquake record of the modified impedance model, judging whether can be according to the modified modulus of impedance Type exports the reservoir prediction of the reservoir to be predicted as a result, in the case where the judgment result is yes, according to the modified resistance Anti- model exports reservoir prediction result.

8. method for predicting reservoir as claimed in claim 6, which is characterized in that the method for predicting reservoir, further includes:

It is theoretical based on log data and rock physics, determine the multiple effective seismic properties and corresponding weight coefficient；

Wherein, theoretical based on log data and rock physics, obtain the multiple effective seismic properties and corresponding weight Coefficient, comprising:

The geological model of the reservoir to be predicted is generated according to log data；

The geophysical model of the reservoir to be predicted is established according to the geological model；

Based on rock physics theory and the geophysical model, the Reservoir Parameter Models of the reservoir to be predicted are established；

It is screened to obtain the multiple effective seismic properties sensitive to reservoir according to the Reservoir Parameter Models, and according to reservoir Sensitive degree is that the weight coefficient is arranged in each effective seismic properties.

9. a kind of reservoir prediction device characterized by comprising

Facies Control Modeling unit, is used for: carrying out Facies Control Modeling based on seismic data, obtains the initial impedance model of reservoir to be predicted；

Earthquake record generation unit, is used for: synthesizing to the initial impedance model, it is corresponding to obtain the initial impedance model Earthquake record；

Prediction result determination unit, is used for: according to the corresponding earthquake record of the initial impedance model, judging whether being capable of basis The initial impedance model exports the reservoir prediction of the reservoir to be predicted as a result, in the case where the judgment result is yes, according to The initial impedance model exports reservoir prediction result.

10. reservoir prediction device as claimed in claim 9, which is characterized in that the Facies Control Modeling unit, comprising:

Seismic properties generation module, is used for: carrying out attributive analysis using seismic data, obtains multiple seismic properties；

Seismic facies generation module, is used for: being based on log-petrofacies, carries out lithofacies prediction using the multiple seismic properties, obtain The seismic facies of reservoir to be predicted；

Impedance model generation module, is used for: the initial of the reservoir to be predicted is established under the phased constraint of the seismic facies Impedance model.

11. reservoir prediction device as claimed in claim 10, which is characterized in that the seismic facies generation module, comprising:

Log-petrofacies generation module, is used for: being based on geologic setting, using log data and its explains that data carry out log-petrofacies point Analysis, obtains log-petrofacies；

Lithofacies and relation on attributes establish module, are used for: being based on the log-petrofacies, divided using the multiple seismic properties Analysis, establishes the relationship between log-petrofacies and seismic properties；

Seismic facies output module, is used for: exporting reservoir to be predicted according to the relationship between the log-petrofacies and seismic properties Seismic facies.

12. reservoir prediction device as claimed in claim 9, which is characterized in that further include:

High resolution processing unit, is used for: being based on reservoir characteristic, carries out high resolution processing to primary earthquake data, obtain describedly Shake data.

13. reservoir prediction device as claimed in claim 12, which is characterized in that the high resolution processing unit, comprising:

Thickness and dominant frequency and bandwidth relationship establish module, are used for: the primary earthquake data by treating target zone in predicting reservoir Time frequency analysis is carried out, and the target zone is carried out to become reservoir thickness forward modeling, establishes reservoir thickness and dominant frequency and bandwidth Relationship；

Open up frequency parameter adjustment module, be used for: frequency parameter is opened up in the relationship based on the reservoir thickness and dominant frequency and bandwidth, adjusting, with It suppresses the interference noise in the primary earthquake data and improves the bandwidth of useful signal in the primary earthquake data.

14. reservoir prediction device as claimed in claim 9, which is characterized in that the prediction result determination unit, comprising:

Initial attribute generation module, is used for: seismic attributes analysis is carried out using the corresponding earthquake record of the initial impedance model, Obtain multiple primary earthquake attributes；

Weight estimation attribute generation module, is used for: to multiple effective seismic properties in the multiple primary earthquake attribute by phase The weight coefficient answered is weighted summation, the prediction seismic properties after being weighted；

Attribute error generation module, is used for: according to the actual seismic attribute after the prediction seismic properties and weighting after the weighting Calculate seismic properties error；Wherein, the actual seismic attribute after the weighting is more according to multiple actual seismic attributes A effective seismic properties are weighted summation by corresponding weight coefficient and obtain, and the multiple actual seismic attribute is basis The seismic data carries out attributive analysis and obtains；

Prediction result determining module, is used for: whether being less than setting error amount according to the seismic properties error, judging whether can The reservoir prediction result of the reservoir to be predicted is exported according to the initial impedance model.

15. reservoir prediction device as claimed in claim 9, which is characterized in that further include:

Impedance model modifies unit, is used for: can not export the reservoir to be predicted according to the initial impedance model in judgement Reservoir prediction result in the case where, modify the initial impedance model, obtain modified impedance model；

Earthquake record re-generates unit, is used for: synthesizing to the modified impedance model, obtains the modified resistance The corresponding earthquake record of anti-model；

Prediction result weight determination unit, is used for: according to the corresponding earthquake record of the modified impedance model, judging whether energy It is enough that the reservoir prediction of the reservoir to be predicted is exported as a result, the feelings for being yes in judging result according to the modified impedance model Under condition, reservoir prediction result is exported according to the modified impedance model.

16. reservoir prediction device as claimed in claim 14, which is characterized in that the reservoir prediction device, further includes:

Effective attribute and weight determining unit, are used for: it is theoretical based on log data and rock physics, determine it is the multiple effectively Shake attribute and corresponding weight coefficient；

Wherein, effective attribute and weight determining unit, comprising:

Geological model generation module, is used for: the geological model of the reservoir to be predicted is generated according to log data；

Geophysical model generation module, is used for: the geophysics mould of the reservoir to be predicted is established according to the geological model Type；

Reservoir Parameter Models establish module, are used for: being based on rock physics theory and the geophysical model, establish described to pre- Survey the Reservoir Parameter Models of reservoir；

Effective attribute and weight generation module, are used for: according to the Reservoir Parameter Models screen to obtain to reservoir it is sensitive described in Multiple effective seismic properties, and be that the weight coefficient is arranged in each effective seismic properties according to the sensitive degree of reservoir.

17. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is by processor The step of claim 1 to 8 the method is realized when execution.

18. a kind of computer equipment including memory, processor and stores the meter that can be run on a memory and on a processor Calculation machine program, which is characterized in that the step of processor realizes claim 1 to 8 the method when executing described program.