CN105301647A - Method for distinguishing calcareous mudstone from sandstone - Google Patents
Method for distinguishing calcareous mudstone from sandstone Download PDFInfo
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Abstract
The present invention provides a method for distinguishing calcareous mudstone from sandstone. The method includes the steps as follows: S1, establishing an isochronous stratigraphic framework; S2, performing sparse impulse wave impedance inversion on the basis of the isochronous stratigraphic framework establishment so as to acquire a wave impedance data volume with high lateral continuity; S3, performing sensitivity curve optimization and correction; S4, performing variation function analysis by utilizing the optimized sensitivity curve so as to acquire a parameter probabilistic model with high longitudinal resolution. The method for distinguishing calcareous mudstone from sandstone can increase reservoir prediction precision by utilizing macro-view cognition such as geology and well drilling as a guide, utilizing well log curve as a starting point, and utilizing the corresponding reservoir prediction method as a tool.
Description
Technical field
The present invention relates to oil field prospecting technical field, particularly relate to a kind of method distinguishing grey matter mud stone and sandstone.
Background technology
Reservoir prediction relates generally to amplitude, frequency generic attribute, and conventional method for predicting reservoir comprises RMS amplitude, net amplitude, arc length, frequency division explanation, average reflection intensity, energy half decay time etc.By contrast, the analysis discovery of the method for a series of reservoir prediction, it all can not effectively distinguish grey matter mud stone and sandstone, main because grey matter mud stone has AC, DEN, GR value close with sandstone (pebbly sandstone, packsand, siltstone).The not accuracy of reservoir prediction, greatly reduces exploration success ratio, have impact on exploration progress.
Jiyang depression respectively caves in and all there is the problem that grey matter mud stone affects reservoir prediction precision, in Shengli Oil Field physical prospecting research institute woods, the triumphant people of grade grows section seismic data dominant frequency by statistics grey matter mud stone, extract the frequency division data volume of corresponding frequencies, then utilize this data volume determine time window in adopt amplitude generic attribute to predict grey matter mud stone spread scope, and then reach the object removing the impact of grey matter mud stone, but the limitation of the method is, only can predict the growth scope of grey matter mud stone, while removal grey matter mud stone, sandstone as Effective Reservoirs has also been got rid of in the lump, belong to a kind of semiquantitative method for predicting reservoir, accurately can not reflect the spread of reservoir.
Shu Gao degree of prospecting district, study area, geological knowledge bores abundant information with real, and by existing drilling well and geological analysis identifiable design grey matter mud stone major developmental region, the problem of macroscopic aspect can effectively be solved.When current fine granularing scalability, how effectively to remove the impact of grey matter mud stone on reservoir prediction from microcosmic, find and can become crucial for the structure-lithology of probing, lithologic oil pool.We have invented a kind of method of new differentiation grey matter mud stone and sandstone for this reason, solve above technical matters.
Summary of the invention
The object of this invention is to provide a kind of method distinguishing grey matter mud stone and sandstone, by analyzing the difference between grey matter mud stone and sandstone, distinguishing grey matter mud stone and sandstone, improving the precision of reservoir prediction.
Object of the present invention realizes by following technical measures: the method distinguishing grey matter mud stone and sandstone, and the method for this differentiation grey matter mud stone and sandstone comprises: step 1, sets up Stratigraphic framework when waiting; Step 2, on the basis setting up chronostratigraphic architecture, carries out Sparse Pulse wave impedance inversion, obtains the Wave Impedance Data Volume with higher lateral continuity; Step 3, carries out preferred, the correction of sensitivity curve; And step 4, utilize the sensitivity curve optimized, obtained the parameter probability model with higher longitudinal frame by variogram analysis.
Object of the present invention also realizes by following technical measures:
In step 1, on the basis of Fine structural interpretation T4, T5 type formation, utilize the relative theory of strata slicing, by adding up each sand group proportion, building Ge Shazudi circle, and then setting up the chronostratigraphic architecture of each sand group.
In step 3, in order to more effectively distinguish the lithology of grey matter mud stone and sandstone, carrying out the preferred of logging trace, easily getting according to practicality, principle that geological meaning is clear and definite, select shale index curve by analyzing, contrasting, shale index curve can accurately distinguish grey matter mud stone and sandstone.
In step 4, utilize the sensitivity curve optimized, select suitable variogram model by models fitting, in the spatial feature base analyzing reservoir, obtain the parameter probability model with higher longitudinal frame by variogram analysis
The method of this differentiation grey matter mud stone and sandstone also comprises, and after step 4, Wave Impedance Data Volume and parameter probability model is carried out well shake Combined Treatment, has both been had higher lateral continuity, and had again the reservoir prediction data volume of higher longitudinal frame.
Differentiation grey matter mud stone in the present invention and the method for sandstone, by analyzing the feature of logging trace, selecting the sensitivity curve can distinguishing grey matter mud stone, sandstone, adopting the relative theory of geostatistics, utilize the reservoir characterization technology based on earthquake collaborative modeling, improve the precision of reservoir prediction.Can effectively distinguish grey matter mud stone and sandstone, improve the precision of reservoir prediction, meet the needs of fine granularing scalability.
Attached caption
Fig. 1 is the process flow diagram of a specific embodiment of the method for differentiation grey matter mud stone of the present invention and sandstone;
Fig. 2 is the log response characteristics figure of a well different lithology;
Fig. 3 is sandstone and grey matter mud stone AC curve comparison figure;
Fig. 4 is sandstone and grey matter mud stone DEN curve comparison figure;
Fig. 5 is sandstone, mud stone and grey matter mud stone GR curve comparison figure;
Fig. 6 is sandstone, mud stone and grey matter mud stone SH curve comparison figure;
Fig. 7 is the schematic diagram (5 sand group stochastic inverse reservoir prediction figure) that study area predicts the outcome.
embodiment
For making above and other object of the present invention, feature and advantage can become apparent, cited below particularly go out preferred embodiment, and coordinate institute's accompanying drawings, be described in detail below.
As shown in Figure 1, Fig. 1 is the process flow diagram of the method for differentiation grey matter mud stone of the present invention and sandstone.
In step 101, set up Stratigraphic framework when waiting; On the basis of Fine structural interpretation T4, T5 type formation, utilize the relative theory of strata slicing, by adding up in husky three shared by each sand group ratio in husky three, building Ge Shazudi circle, and then setting up the chronostratigraphic architecture (table 1) of each sand group.
(between T4 ~ T5 stratum) each sand group zone thickness statistical form in table 1 sand three
Flow process enters into step 102.
In step 102, from seismic data, on the basis setting up chronostratigraphic architecture (step 101), carry out Sparse Pulse wave impedance inversion, obtain the Wave Impedance Data Volume with higher lateral continuity.Flow process enters into step 103.
In step 103, preferred, the correction of sensitivity curve.Due to the impact by rock composition, the contrast of section, plane finds that grey matter mud stone has comparatively similar density, speed and GR value (Fig. 2 ~ Fig. 5) to sandstone, in order to more effectively distinguish two kinds of lithology, needs preferred logging trace.Preferably easily should the getting in line with practicality of logging trace, geological meaning are clearly principle, and by analyzing, contrast thinks that shale index curve accurately can distinguish grey matter mud stone and sandstone (Fig. 6).Flow process enters into step 104.
In step 104, utilize the preferred sensitivity curve of step 103, select suitable variogram model by models fitting, in the spatial feature base analyzing reservoir, obtain the parameter probability model with higher longitudinal frame by variogram analysis.Flow process enters into step 105.
In step 105, data volume step 102 and step 104 obtained carries out well shake Combined Treatment, both there is higher lateral continuity, there is again the reservoir prediction data volume (Fig. 7) of higher longitudinal frame, thus reach the impact of removal grey matter mud stone, improve the object of reservoir prediction precision.Flow process terminates.
Claims (5)
1. distinguish the method for grey matter mud stone and sandstone, it is characterized in that, the method for this differentiation grey matter mud stone and sandstone comprises:
Step 1, sets up Stratigraphic framework when waiting;
Step 2, on the basis setting up chronostratigraphic architecture, carries out Sparse Pulse wave impedance inversion, obtains the Wave Impedance Data Volume with higher lateral continuity;
Step 3, carries out preferred, the correction of sensitivity curve; And
Step 4, utilizes the sensitivity curve optimized, and is obtained the parameter probability model with higher longitudinal frame by variogram analysis.
2. the method for differentiation grey matter mud stone according to claim 1 and sandstone, it is characterized in that, in step 1, on the basis of Fine structural interpretation T4, T5 type formation, utilize the relative theory of strata slicing, by adding up each sand group proportion, building Ge Shazudi circle, and then setting up the chronostratigraphic architecture of each sand group.
3. the method for differentiation grey matter mud stone according to claim 1 and sandstone, it is characterized in that, in step 3, in order to more effectively distinguish the lithology of grey matter mud stone and sandstone, carry out the preferred of logging trace, easily get according to practicality, principle that geological meaning is clear and definite, by analyzing, contrast selects shale index curve, and shale index curve can accurately distinguish grey matter mud stone and sandstone.
4. the method for differentiation grey matter mud stone according to claim 1 and sandstone, it is characterized in that, in step 4, utilize the sensitivity curve optimized, suitable variogram model is selected by models fitting, in the spatial feature base analyzing reservoir, obtain the parameter probability model with higher longitudinal frame by variogram analysis.
5. the method for differentiation grey matter mud stone according to claim 1 and sandstone, it is characterized in that, the method of this differentiation grey matter mud stone and sandstone also comprises, after step 4, Wave Impedance Data Volume and parameter probability model are carried out well shake Combined Treatment, both there is higher lateral continuity, there is again the reservoir prediction data volume of higher longitudinal frame.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107339099A (en) * | 2017-07-19 | 2017-11-10 | 中国石油天然气集团公司 | A kind of method and apparatus for determining reservoir lithology |
| CN107977483A (en) * | 2017-10-30 | 2018-05-01 | 中国石油天然气股份有限公司 | Method for predicting distribution of sand shale |
| CN108873064A (en) * | 2018-03-29 | 2018-11-23 | 中国石油天然气股份有限公司 | Establishment method and system of lithofacies probability distribution model |
| CN109061752A (en) * | 2018-06-26 | 2018-12-21 | 西南石油大学 | A kind of resistivity curve bearing calibration on the stratum containing grey matter |
| CN109387873A (en) * | 2017-08-04 | 2019-02-26 | 中国石油化工股份有限公司 | A kind of fracture and cave reservoir inversion method and system |
| CN110821496A (en) * | 2019-10-17 | 2020-02-21 | 中国石油集团长城钻探工程有限公司 | Organic shale phase mode establishing method and organic shale evaluation method |
| CN114763744A (en) * | 2021-01-11 | 2022-07-19 | 中国石油化工股份有限公司 | Glutenite reservoir connectivity description method based on mudstone division |
| CN114763744B (en) * | 2021-01-11 | 2025-03-25 | 中国石油化工股份有限公司 | Connectivity description method of conglomerate reservoir based on mudstone division |
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| CN107339099B (en) * | 2017-07-19 | 2020-06-09 | 中国石油天然气集团公司 | Method and device for determining reservoir lithology |
| CN107339099A (en) * | 2017-07-19 | 2017-11-10 | 中国石油天然气集团公司 | A kind of method and apparatus for determining reservoir lithology |
| CN109387873A (en) * | 2017-08-04 | 2019-02-26 | 中国石油化工股份有限公司 | A kind of fracture and cave reservoir inversion method and system |
| CN107977483A (en) * | 2017-10-30 | 2018-05-01 | 中国石油天然气股份有限公司 | Method for predicting distribution of sand shale |
| CN107977483B (en) * | 2017-10-30 | 2021-01-29 | 中国石油天然气股份有限公司 | Method for predicting distribution of sand shale |
| CN108873064A (en) * | 2018-03-29 | 2018-11-23 | 中国石油天然气股份有限公司 | Establishment method and system of lithofacies probability distribution model |
| CN108873064B (en) * | 2018-03-29 | 2020-06-09 | 中国石油天然气股份有限公司 | Establishment method and system of lithofacies probability distribution model |
| CN109061752A (en) * | 2018-06-26 | 2018-12-21 | 西南石油大学 | A kind of resistivity curve bearing calibration on the stratum containing grey matter |
| CN109061752B (en) * | 2018-06-26 | 2020-01-17 | 西南石油大学 | A method for correcting resistivity curve of ash-bearing strata |
| CN110821496A (en) * | 2019-10-17 | 2020-02-21 | 中国石油集团长城钻探工程有限公司 | Organic shale phase mode establishing method and organic shale evaluation method |
| CN110821496B (en) * | 2019-10-17 | 2021-06-29 | 中国石油天然气集团有限公司 | Organic shale phase mode establishing method and organic shale evaluation method |
| CN114763744A (en) * | 2021-01-11 | 2022-07-19 | 中国石油化工股份有限公司 | Glutenite reservoir connectivity description method based on mudstone division |
| CN114763744B (en) * | 2021-01-11 | 2025-03-25 | 中国石油化工股份有限公司 | Connectivity description method of conglomerate reservoir based on mudstone division |
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