A Study of Electric Log Interpretation Methods in Shaly Formations

Witte, L. de

doi:10.2118/402-g

Cited by 17 publications

(4 citation statements)

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“…The petrophysical parametres of subsoils are normally extracted from the engineering geophysical sounding (EGS) data using well-log analysis techniques originally developed for deep boreholes (Serra 1984). A deterministic approach for estimating the 3D resistivity distribution from the parametres of EGS measurements was suggested by Nyári et al (2010), in which Archie's (1942) and De Witte's (1955) models were compared. Nuclear data collected by EGS tools provide information about the density, water content, and porosity, which can be used in resistivity calculations for modelling the transport of water and contaminants.…”

Section: Forward Modellingmentioning

confidence: 99%

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Most frequent value‐based factor analysis of direct‐push logging data

Szabó

Balogh

Stickel³

2017

Geophysical Prospecting

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An improved, iteratively re‐weighted factor analysis procedure is presented to interpret engineering geophysical sounding logs in shallow unsaturated sediments. We simultaneously process cone resistance, electric resistivity, and nuclear data acquired by direct‐push tools to give robust estimates of factor variables and water content in unconsolidated heterogeneous formations. The statistical procedure is based on the iterative re‐weighting of the deviations between the measured and calculated data using the most frequent value method famous for its robustness and high statistical efficiency. The iterative approach improves the result of factor analysis for not normally distributed data and extremely noisy measurements. By detecting a strong regression relation between one of the extracted factors and the fractional volume of water, we establish an independent method for water content estimation along the penetration hole. We verify the estimated values of water volume by using a highly over‐determined, quality‐checked interval inversion procedure. The multidimensional extension of the statistical method allows the estimation of water content distribution along both the vertical and the horizontal coordinates. Numerical tests using engineering geophysical sounding data measured in a Hungarian loessy–sandy formation demonstrate the feasibility of the most frequent value‐based factor analysis, which can be efficiently used for a more reliable hydrogeophysical characterisation of the unsaturated zone.

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Section: Forward Modellingmentioning

confidence: 99%

“…In equations (2)−(3), the density and neutron porosity of gas are set to zero. Response function in equation (4), applicable to calculate the resistivity, was suggested by De Witte (1955). In fact, the fluid and matrix properties are not always constant as they may vary in the heterogeneous sediment.…”

Section: Forward Modellingmentioning

confidence: 99%

Most frequent value‐based factor analysis of direct‐push logging data

Szabó

Balogh

Stickel³

2017

Geophysical Prospecting

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“…In Formula (3-2) , parameters (a, b, m, n), called as Archie parameters, are usually determined by rock-electric experiments. Due to the complexity of influence factors of reservoir rock electrical property, Mungan and Moore have analysed and pointed out that Archie Formula contains 3 implicit assumptions [2] , which include that 1. the relation of saturation and resistivity shall be only; 2. for the given reservoir rock, n is constant; 3. all the formation water can conduct current.The above assumptions could be completely or approximately fulfilled only when rock physical property is good and hard to achieve if complex reservoirs, such as argillaceous sandstone or fractured reservoir, is encountered.…”

Section: Classic Archie's Formulamentioning

confidence: 99%

Application of Archie Formula in Areas of Data Deficiencies

Qian¹,

Deng²,

Lu³

et al. 2015

Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics

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Based on the well logging data of the research area and the existing reservoir interpretation, Archie Formula is modified to work out the new saturation model which can be used to accurately calculate reservoir saturation when data of well log is incomplete. This paper introduces the general situation of research area and concludes the new saturation interpretation model by modifying Archie Formula according to characteristics of block, interpreting the 4 wells in research area in remarkably improved remarkably.

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“…Revised manuscript received Dec. 30,1960. Paper presented at SPE Formation Evaluation Symposium Nov. [21][22]1960, in Houston.…”

Section: Assumptionsmentioning

confidence: 99%

Techniques of Electric Log Interpretation

Atkins¹

1961

Journal of Petroleum Technology

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The generally used techniques of electric log interpretation are reviewed and discussed, including the determination offormation water resistivity from the SP curve,true resistivity values from log data,water saturation from electric logs, andformation porosity from resistivity data. Particular emphasis is placed on the assumptions made in log interpretation. It is hoped that efforts will be stimulated which, in the future, will make it possible to reduce the number of assumptions necessary for log interpretation. Introduction Petroleum engineering and geology can be said to be based upon both facts and assumptions. So too, are the various techniques of electric log interpretation. For the last few years, some assumptions which have been made in developing log interpretation methods have been repeated so often that they are now accepted by many persons as facts. In reviewing the principles of resistivity and potential curve interpretations, many of the assumptions (and how they affect the results of interpretation) will be considered. Because this is a review, the purpose of this paper is not to present new methods of interpretation. However, the reader of this review should be stimulated to consider whether he should accept these assumptions as they are made now or whether he would prefer to explore possible ways to reduce the number of assumptions required for log interpretation. Assumptions To emphasize the assumptions used in most interpretations of electric logs, they will be tabulated here and then referred to as each technique of interpretation is discussed. No particular emphasis is inferred by the order of tabulation.

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A Study of Electric Log Interpretation Methods in Shaly Formations

Cited by 17 publications

References 0 publications

Most frequent value‐based factor analysis of direct‐push logging data

Most frequent value‐based factor analysis of direct‐push logging data

Application of Archie Formula in Areas of Data Deficiencies

Techniques of Electric Log Interpretation

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