改进的模糊模式识别方法在测井曲线分层中的应用

应用改进的基于数域上的模糊模式识别方法，综合多条测井曲线进行自动分层。首先，找出各条曲线总的上升沿（或下降沿），然后，在对上升沿（或下降沿）中各采样点构造模糊集时采用测井曲线的斜率，而不是采用测井曲线值。在求取各点隶属度时，采用各条曲线中的最大斜率值，反映了地层分层点在测井曲线拐点这一客观规律。最后，应用贴近度准则分层。该方法给出了更合理的分层点。     

Using Artificial Neural Networks to Predict the Presence of Overpressured Zones in the Anadarko Basin,Oklahoma

Many sedimentary basins throughout the world exhibit areas with abnormal pore-fluid pressures (higher or lower than normal or hydrostatic pressure). Predicting pore pressure and other parameters (depth, extension, magnitude, etc.) in such areas are challenging tasks. The compressional acoustic (sonic) log (DT) is often used as a predictor because it responds to changes in porosity or compaction produced by abnormal pore-fluid pressures. Unfortunately, the sonic log is not commonly recorded in most oil and/or gas wells. We propose using an artificial neural network to synthesize sonic logs by identifying the mathematical dependency between DT and the commonly available logs, such as normalized gamma ray (GR) and deep resistivity logs (REID). The artificial neural network process can be divided into three steps: (1) Supervised training of the neural network; (2) confirmation and validation of the model by blind-testing the results in wells that contain both the predictor (GR, REID) and the target values (DT) used in the supervised training; and 3) applying the predictive model to all wells containing the required predictor data and verifying the accuracy of the synthetic DT data by comparing the back-predicted synthetic predictor curves (GRNN, REIDNN) to the recorded predictor curves used in training (GR, REID). Artificial neural networks offer significant advantages over traditional deterministic methods. They do not require a precise mathematical model equation that describes the dependency between the predictor values and the target values and, unlike linear regression techniques, neural network methods do not overpredict mean values and thereby preserve original data variability. One of their most important advantages is that their predictions can be validated and confirmed through back-prediction of the input data. This procedure was applied to predict the presence of overpressured zones in the Anadarko Basin, Oklahoma. The results are promising and encouraging.     

Slotting of borehole sequences

A method is described for comparing and correlating borehole sequences using information from one or more physical logs recorded from the boreholes. The method is illustrated by a small worked example. Ways are described whereby constraints may be imposed on the comparison to allow the incorporation of relevant information, such as the presence of marker beds in the stratigraphic sequences. An account is given of the comparison of three boreholes in the Lansing Group of Kansas, USA, and there is a short discussion on the effects of filtering, standardizing, and weighting the logs.     

Facies,provenance and paleoclimate interpretation using spectral gamma logs: Application to the Lower Cretaceous of the Scotian Basin

Spectral gamma logging has been useful in some settings for correlation of wells, for identification of sediment facies, and for interpretation of hinterland paleoclimate. We have taken advantage of the hundreds of geochemical analyses of sandstones and shales from conventional core that are available from the Scotian Basin to test the relationship of the elements K, U and Th measured by spectral gamma to sedimentary facies. These elements are also known to be useful in characterising provenance of sediment to different parts of the basin. The geochemical and spectral gamma data both show that there are subtle differences in K, U and Th in different lithofacies, such as higher Th/U in low sedimentation rate facies, but they are not sufficiently distinctive to identify the lithofacies of any unknown interval. The main control on abundance of these elements is the effect of grain size, that is the proportion of sand to mud in sediment. Volcanic sources have a high K/Th ratio, and early Albian sediments with relatively high volcanic component have unusually high K/Th. In distal shale-prone successions, the grain size effect is sufficiently small that climate controlled variations in Th/K ratio are recognised in the Early Cretaceous, with the ratio being higher at times of humid weathering on land. The variations in Th/K ratio through time are broadly similar to those known from Western European sections, notably with topmost Hauterivian and topmost Aptian humid events. Overall, this study provides an assessment of the use and pitfalls of spectral gamma logs in a deltaic succession.     

Fuzzy inference system for identification of geological stratigraphy off Prydz Bay, East Antarctica

The analysis of well logging data plays key role in the exploration and development of hydrocarbon reservoirs. Various well log parameters such as porosity, gamma ray, density, transit time and resistivity, help in classification of strata and estimation of the physical, electrical and acoustical properties of the subsurface lithology. Strong and conspicuous changes in some of the log parameters associated with any particular geological stratigraphy formation are function of its composition, physical properties that help in classification. However some substrata show moderate values in respective log parameters and make difficult to identify the kind of strata, if we go by the standard variability ranges of any log parameters and visual inspection. The complexity increases further with more number of sensors involved. An attempt is made to identify the kinds of stratigraphy from well logs over Prydz bay basin, East Antarctica using fuzzy inference system. A model is built based on few data sets of known stratigraphy and further the network model is used as test model to infer the lithology of a borehole from their geophysical logs, not used in simulation. Initially the fuzzy based algorithm is trained, validated and tested on well log data and finally identifies the formation lithology of a hydrocarbon reservoir system of study area. The effectiveness of this technique is demonstrated by the analysis of the results for actual lithologs and coring data of ODP Leg 188. The fuzzy results show that the training performance equals to 82.95% while the prediction ability is 87.69%. The fuzzy results are very encouraging and the model is able to decipher even thin layer seams and other strata from geophysical logs. The result provides the significant sand formation of depth range 316.0- 341.0 m, where core recovery is incomplete.     

A method for stratigraphic correlation of several boreholes

The borehole slotting method previously proposed by Gordon and Reyment for two boreholes may be extended to three or more boreholes, but soon becomes computationally intractable. We propose another method based on the mixture model of cluster analysis, the computational labor of which increases linearly with the number of boreholes. This method produces profiles of the unknown strata to which the individual boreholes are easily matched by the two-borehole slotting method.     

Potential causes of differences between ground and surface air temperature warming across different ecozones in Alberta, Canada

Analysis and modelling of temperature anomalies from 25 selected deep wells in Alberta show that the differences between GST (ground surface temperature) warming for the northern Boreal Forest ecozone and the combined Prairie Grassland ecozone and Aspen Parkland transition region to the south occur during the latter half of this century. This corresponds with recent changes in surface albedo resulting from permanent land development in the northern areas and also to increases in natural forest fires in the past 20 years. Differences between GST and SAT (surface air temperature) warming are much higher in the Boreal Forest ecozone than in the Prairie Grassland ecozone and Aspen Parkland transition region. Various hypotheses which could account for the existing differences between the GST and SAT warming in the different ecozones of Alberta, and western Canada in general, are tested. Analysis of existing data on soil temperature, hydrological piezometric surfaces, snowfall and moisture patterns, and land clearing and forest fires, indicate that large areas of Alberta, characterised by anomalous GST warming, have experienced widespread changes to the surface landscape in this century. It is postulated that this has resulted in a lower surface albedo with a subsequent increase in the absorption of solar energy. Heat flow modelling shows that, after climatic SAT warming, permanent clearing of the land is the most effective and likely cause of the observed changes in the GST warming. The greater GST warming in the Boreal Forest ecozone in the latter half of this century is related to landscape change due to land development and increasing forest fire activity. It appears to account for a portion of the observed SAT warming in this region through a positive feedback loop with the overlying air. The anthropogenic effect on regional climatic warming through 20th century land clearing and landscape alteration requires further study. In future, more accurate quantification of these various forcings will be necessary in order to distinguish between, and to detect, the variety of natural and anthropogenic influences and on climate.     

基于测井资料的辫状河三角洲沉积储层精细描述

通过岩心观察、常规测井和成像测井等资料,对库车坳陷大北克深地区白垩系巴什基奇克组辫状河三角洲沉积储层特征进行了精细研究。结果表明辫状河三角洲前缘发育的水下分流河道、河口坝等构成了主要的骨架砂体类型。通过岩心刻度测井建立了一套较完整的岩性和沉积构造识别模式。在此基础上建立了不同沉积微相的测井识别与划分标准,并探讨了不同沉积微相对储层物性的控制。然后根据粒度中值和成分成熟度指数将沉积微相进一步细分为水下分流河道中砂岩、水下分流河道细砂岩等不同的岩性岩相类型,并分别建立了粒度中值和成分成熟度指数的测井评价模型。在此基础上以成像测井为主,辅以常规测井和岩心资料及粒度参数和成分成熟度指数,实现单井连续的岩性岩相识别与划分。研究成果可为后续沉积储层精细评价乃至天然气勘探开发综合研究奠定基础。     

砂砾岩体内幕岩性识别方法初探——以东营凹陷盐家油田盐22断块砂砾岩体为例

东营坳陷盐家油田砂砾岩体为近物源、快速堆积的近岸水下扇沉积,扇体厚度大,横向变化快。巨厚砂砾岩体内部的精细地层划分对比一直是制约该区进一步勘探开发的难点。根据该区盐22断块砂砾岩体的沉积特征,首先运用测井曲线重构方法划分出砂砾岩体的砂砾岩段、泥岩段,剔去明显的非储层;其次运用聚类分析方法识别砂砾岩段的岩性构成。砂砾岩体内幕岩性划分结果与岩心资料比较吻合率为966%,与成像资料比较吻合率为962%。该方法为该区厚层砂砾岩体内部地层精细划分与对比提供了可靠的地质依据。