Research Of Reservior Characteristics Of Baibao District Based On Multivariate Data Analysis And Minning Of Oilfield

Under the guidance of the extensive viewpoint of data mining and based on multivariatedata analysis and minning of oilfield,the paper takes Baibao oil field district of Ordos basinfor example,dividing the data mining course of reservoir characteristics into five stages:determination of reservoir data mining target,establishment of project database,datapreprocessing,modeling and evaluation.By referring to abundant references and correlateiveresearch results,comprehensively collecting rock and mineral data and physical property,according to present situation of data dispersion,massive data,left unused seriously butdeficient in knowledge,the task of reservoir data mining target is determined.We extractrelated reservoir data of Baibao oil field district in order to construct reservoir projectdatabase of study area,and then massive,multivariate (multiple) data fusion and integrationcan be achieved and the mechanism of data sharing is established.All these have importanttheoretical and practical significance for promoting quantitative study of reservoir andinformatization development of oil field.By adopting research method of data mining visualization techniques,reservoir datapreprocessing,quality audit,data statistic analysis and modeling are taken to comprehensivelyresearch the reservoirs in the study area,and visual process and result of data mining arerealized,finally through statistical characteristics and spatial distributions laws of geologicalparameters,the reservoirs are described and predicted,related geology problems of reservoirare further studied to guide the further exploration and development of oil and gas field.Member 6 of Yanchang Formation of upper-triassic in Ordos basin is one of the mostimportant exploration target stratum in Baibao district.By taking Chang 6 as the researchobject,according to reservoir database of Baibao district,by using the theory ofsedimentology,petroleum geology and geophysics,based on the course of reservoir datamining,the paper takes provenance analysis and clustering partition,rock type discriminationand distribution law,modeling of porosity and permeability,reservoir spatial distributioncharacteristics research and comprehensive evaluation of reservoir.The main researchcontents and research progress are proposed as follows:1.On the basis of qualitative provenance analysis of the study area,taking detritalcomposition and pore filling mineral composition into consideration,the paper takes spatialcluster analysis by extracting 655 samples of rock thin section database of Chang 6.The studyarea is divided into three provenance partitions.From planar distribution law of spatial clusterresult of Chang 6,the reservoir is mainly sourced from northeast,secondly from southwest,and in the belt of Yuan cheng-Baima-Wujiao,it is overlapping influenced by the two sourcedirection and formed mixing source region.The division of provenance partition lay afoundation for quantitative study of petrological characteristics and reservoir property of eachprovenance partition. 2.In the research of rock type,by establishing automatic recognition model,the papermakes it simple to quantitative study the large data of composition.The analysis results ofrock type show that in Chang 6 Formation in the study area,the most of reservoir rock isdebris feldspar sandstone and secondly is feldsparthic sandstone and small part of feldspathiclithic sandstone.By further analysis of rock type of different provenance partition,it showsthat northeast provenance is mainly debris feldspar sandstone,and minor is feldsparthicsandstone,the mixed source area is dominated by debris feldspar sandstone,secondary isfeldspathic lithic sandstone,and southwest provenance is mainly feldspathic lithic sandstone,and minor debris feldspar sandstone.3.Based on the core analysis data and multi-logging information,by using neuralnetwork technology,the paper predicts the reservoir parameter of Chang 6 in order to provideprecise interpretation of reservoir parameter.The changing trend of porosity and permeabilitypredicted by neural network equates with that of coring well data.In contrast with traditionalregression analysis,the prediction accuracy of neural network is somewhat increased,whichmeet the need of reservoir heterogeneity research.By using the method,the paper establishesthe relationship between well logging response and core analysis data,and then makes up forthe deficiency of number of coring well.Accordingly,we can take analysis of the correlationand heterogeneity of porosity and permeability,and spatial distribution law of quantitativeparametersmore accurate and more detailed.4.In the study of reservoir property,the paper analyzes the correlation between porosityand permeability and studies the reservoir heterogeneity of each sublayer of Chang 6.It isconsidered that porosity heterogeneity of Chang 6 is far less than permeability,and the formeris relatively homogeneous,and the heterogeneity of the latter is relatively strong.It shows thatthe permeability heterogeneity (level difference,mutation coefficient and coefficient ofvariation) of Chang 6~3 is larger than that of Chang 6~2 and Chang 6~1,while the heterogeneity ofChang6~1 is weakest.By using two important physical parameters-porosity and permeability,the paper then takes primary classification of Chang 6 reservoir by cluster analysis.In order tostudy the relation between petrologic characteristics and reservoir property,the paper matchesthe samples of rock thin section and reservoir property and then analyzes the influencingfactors through relation maps.Intergranular pore,areal porosity and the content of chlorite isrespectively proportional to porosity and permeability,and rock density,contents of carbonatecements and clay cement is respectively inversely proportional to porosity and permeability.5.By extracting well position information and layered data,through data processing flow,and by using modeling software of Rockworks,the paper takes the research ofthree-dimensional geological modeling.The three dimension strata model shows the realvisage underground,which can visually show the geometric shape of underground reservoirsand space distributing characteristics.The information reflected by strata model is consistentwith the characteristics of regional sediment-structural evolution.Based on the establishmentof strata model,the paper also sets up three-dimensional structure model and reservoirparameter model.The 3D structural model of Chang 6 shows that there exist three rows of low relief nose-like structure,extended from west to east on the background of monoclinalstructure.Some well in the nose fold have commercial oil flows.That indicates that to someextent,the nose-like structure controls hydrocarbon enrichment and oil and waterdifferentiation of oil reservoir.6.At last,the paper completely evaluates the reservoir of Chang 6.Firstly,selectevaluation parameters by using feature selection algorithm.Secondly,determine the weight ofeach influencing factors by grey relational analysis.Then determine the evaluation score ofeach parameter by the method of maximal value normalization.Finally,calculate the generalscore.Based on the procedure,reservoir classification evaluation was taken by cluster model.The statistics analysis based on the reservoir evaluation results shows that the reservoircharacteristics of each type is obvious and has a high coherence with the actual characteristicsof the reservoir.Statistics analysis indicates that Chang 6 reservoir mostly is classâ…¡andclassâ…¢,and a few classâ…£and classâ… .The reservoir quality of Chang 6~3 sublayer isobviously better than Chang 6~1 and Chang 6~2.As the best and the better reservoir in the studyarea,classâ… and classâ…¡are the favorable zones for oil.