Reservoir Classification Research Articles

Mathematical Modelling of Reservoir Rock Properties

Abstract The object of this paper is to present a mathematical technique for reservoir classification. Four tools of time series analysis are employed; autocorrelation, cross correlation, power spectrum and filtering. A1ltocorrelation is used to classify the reservoir as random or stratified, cross correlation is used to determine if the strata can be correlated in the reservoir. Power spectrum is used to determine the sampling distribution of the time series and for picking the sampling interval for digitizing well logs or sampling cores. It is also used for determining the frequencies to be filtered out. The paper presents the theory, sample calculations and applies the data to a sandstone reservoir. The reservoir is stratified and the strata can be correlated from well to well. Introduction To CALCULATE RESERVES and predict the performance of a hydrocarbon-bearing reservoir it is desirable to have information pertaining to the distribution of its rock properties. It is necessary to know the porosity distribution to determine reserves and the variations of permeability to calculate the flow rates. With the increased use of numerical simulations to predict reservoir performance, it is necessary to develop better methods of determining the spatial variations of rock properties. There are three generally accepted ways of sampling a reservoir to determine these properties: well logging, coring and flow tests. In well logging and coring, data are obtained at points which can be assigned a depth within a well. Flow tests usually give average properties of the well's drainage volume. From an engineering point of view, reservoir's can be classified in three ways: random, correlated strata and non-correlated strata. The rock properties at a point in a random reservoir do not depend on the properties within the vertical horizontal neighbourhood of that point. In a correlated stratified reservoir. the rock properties at a point are dependent on the rock properties within a vertical and horizontal neighbourhood of that point. In a non-correlated stratified field, the value at a point depends only on the points in a vertical neighbourhood of that point. In this type of classification the strata are usually one foot to several feet in thickness rather than the very small micro strata that occur in many rocks. At the present time, well logging tools are not available for measuring the properties of these micro strata. The object of this paper is to present a method toclassify reservoirs into one of these three groups. The technique assumes that the data obtained from well logs and core analysis can be regarded as a statistical time-series, with a pseudo time assignment to each depth. The development of time-series analysis methods has been reported in the literature(1–30 but its application has been limited mainly to meteorological(3), seismological(5), chemical processing(2)) and economic data(2); some efforts have also been made to apply it to geological data(6–8). This study will use four time-series tools: autocorrelation, cross correlation, power spectrum and filtering.

Potential Energy Resources of Alberta and Their Strategic Position Within the Circular Mosaic

ABSTRACT Landlocked Alberta, which is flanked on its western side by the majestic Rockies, bounded to the south by the international border and is the gateway tothe north, has vast hydrocarbon resources. In this regard, it is the presentcentroid of Canada's oil and gas industry. Despite a continuing upward mobility, it is observed that the province issurrounded – even up into the Arctic and as far south as Texas and Louisiana -by potential or new sources of oil supply. Subjectively speaking, Alberta is described as a high- value energy areawhich is geographically encircled. It is, indeed, within the circular mosaic ofa highly competitive energy environment. Objectively, the province will becomean energy supplier of strategic significance by assisting to meet anever-increasing U.S. oil deficiency situation. Three particular aspects of Alberta are considered:Pattern of the liquids supply, namely, thecircular mosaic, in 1968, and the achievement of fluidity through optimizationof supply between the U.S. and Canada before the 1980's.Ultimate marketable reserves andproduction rates of the hydrocarbons by means of the logistic-curveapproach.Distribution of the alreadydiscovered oil reserves according to reservoir classification. INTRODUCTION EVEN IN THE JET AGE, or the atomic era, if so preferred, or the globalvillage psychedelic concept of Marshall McLuhan, the enormous expanse of Canadais bewildering. Our national emblem emblazons the subscript "A mari usque admare," and so it is, from sea to sea from Halifax on the Atlantic to Vancouveron the Pacific land distance of 3,000 longitudinal miles; and from the Canada-U.S.A. border to the most northerly of the Arctic Islands on the105-degree meridian -2,200 miles of latitude Alberta holds a predominating position in the known accumulation ofhydrocarbons in Canada at the present time. Transportation of the products tomarkets across Canada and into the U.S.A. becomes an important economic factor.This is particularly so for the liquids, as Alberta has no seaboard which mightpermit a lower cost of movement. Net imports into Eastern Canada amount to200,000 bbls of liquids per day, which is equivalent to 26 per cent of Alberta's daily crude oil and pentane production. Alberta could easily producethis net imports volume without any difficulty whatsoever. The absoluteprovincial oil deliverability is now around 2 million barrels per day.Allowing, say, a 70 per cent efficiency factor, the daily production could be1.4 million barrels, or a doubling of the prevailing rate. The projection ofthe logistic curve shows that oil production lags the discovery cycle by 14years; similarly, for natural gas the lag is 16 years.

Classification of Reservoir of Natural Gas

日本の天然ガスの生産は新鉱床の発見と共に近年著しい増加を示してきた。ところがこの鉱床の分類は源始的な探査技術段階ににおいて仮設定されたものが現在まで踏襲されている。この点鉱床に対する概念の上に誤解を生じ易く, また日本の生産の大半を占める鉱床型式は外国ではあまり着目されていないものであることがわかつてきているので, この分類も独自のものを必要とする。ここには鉱床に対する現在の考え方を明らかにすることを試みた。鉱床の成立している地層の地質時代, 附随水が高鹹性であるか低鹹性であるか, 鉱床内で天然ガスが水と共に存在し液相を示すか, 単独に気相を示すか, あるいは両者の混合相を示すかなどは鉱床を区分する基本となるであろう。地質学的に考察すると, 地層がすべて含水率の高い状態にある時にガスの挙措はきわめて特殊な様相を示す。すなわちガスは水に伴い地層中に瀰漫し, そのreservoirは相互に完全にまたは不完全に連通しているため化学的または物理的に流体の性格が近似する。またreservoirでない部分でもガスを包含していると考えられる (潤成ガス鉱床) これに対して周囲の岩石が流体の流通を遮断する状態に達している場合は鉱床はその透通性のあるものの中にだけあつて周囲から隔絶した状態となる (包蔵ガス鉱床) すなわちreservoir間の異質性が発達する。このような観点のほかに液相ガス鉱床が地質構造からみて相対酌に低位置でなお透通性の大なる部分に形成された場合は溶解量も多く稼行に堪える鉱床となることがある (低位ガス鉱床) 。これに対して相対的に高い位置に形成された気相または二相鉱床は海外で普通に開発されている型となる。 (高位ガス鉱床) これらの流体鉱床は条件如何により相互に変貌し得るものである。日本では過去10年間第三紀高鹹性液相低位潤成鉱床が開発対象め主体を占めてきたが今後はさらに富鉱である第三紀の高鹹性である高位包蔵鉱床がこれにかわるであろう。

Classification of Oil Reservoirs: DISCUSSION

Classification of Oil Reservoirs: DISCUSSION

Classification of Oil Reservoirs: GEOLOGICAL NOTES

Classification of Oil Reservoirs: GEOLOGICAL NOTES

A Classification of Limestone Reservoirs: DISCUSSION

A Classification of Limestone Reservoirs: DISCUSSION

A Classification of Limestone Reservoirs

This paper contains a classification of limestone reservoirs based on the origin of the openings in the rock. It is shown that the most important type of reservoir is one in which porosity has been developed by erosion which took place before the time of deposition of the beds now overlying the reservoir. The other class of reservoir of major importance includes fractured limestones. The distribution of the different types of reservoirs in the United States is discussed briefly.