Correlation of Wireline Logs with a Shaly Sandstone Sequence, Red Fork Sandstone, Payne County, Oklahoma: ABSTRACT

AAPG Bulletin ◽  
1983 ◽  
Vol 67 ◽  
Author(s):  
Michael D. Kuykendall
Keyword(s):  
Wireline Logs ◽  
Shaly Sandstone ◽  
Payne County

scholarly journals Improved well logs clustering algorithm for shale gas identification and formation evaluation

2021 ◽  
Author(s):  
N. P. Szabó ◽  
B. A. Braun ◽  
M. M. G. Abdelrahman ◽  
M. Dobróka
Keyword(s):  
Cluster Analysis ◽  
Shale Gas ◽  
Clustering Algorithm ◽  
Traditional Approach ◽  
Harmful Effect ◽  
Weighted Average ◽  
Well Logs ◽  
Organic Carbon Content ◽  
Wireline Logs ◽  
Most Frequent Value

AbstractThe identification of lithology, fluid types, and total organic carbon content are of great priority in the exploration of unconventional hydrocarbons. As a new alternative, a further developed K-means type clustering method is suggested for the evaluation of shale gas formations. The traditional approach of cluster analysis is mainly based on the use of the Euclidean distance for grouping the objects of multivariate observations into different clusters. The high sensitivity of the L2 norm applied to non-Gaussian distributed measurement noises is well-known, which can be reduced by selecting a more suitable norm as distance metrics. To suppress the harmful effect of non-systematic errors and outlying data, the Most Frequent Value method as a robust statistical estimator is combined with the K-means clustering algorithm. The Cauchy-Steiner weights calculated by the Most Frequent Value procedure is applied to measure the weighted distance between the objects, which improves the performance of cluster analysis compared to the Euclidean norm. At the same time, the centroids are also calculated as a weighted average (using the Most Frequent Value method), instead of applying arithmetic mean. The suggested statistical method is tested using synthetic datasets as well as observed wireline logs, mud-logging data and core samples collected from the Barnett Shale Formation, USA. The synthetic experiment using extremely noisy well logs demonstrates that the newly developed robust clustering procedure is able to separate the geological-lithological units in hydrocarbon formations and provide additional information to standard well log analysis. It is also shown that the Cauchy-Steiner weighted cluster analysis is affected less by outliers, which allows a more efficient processing of poor-quality wireline logs and an improved evaluation of shale gas reservoirs.

Lithofacies Analysis and Qualitative Minerology of the Sediments of #3 Well in the Greater Ughelli Depobelt, Niger Delta Basin

2021 ◽  
Vol 13 (2) ◽  
pp. 601-610
Author(s):  
K. Itiowe ◽  
R. Oghonyon ◽  
B. K. Kurah
Keyword(s):  
Physical Properties ◽  
Clay Minerals ◽  
Niger Delta ◽  
Reservoir Quality ◽  
X Ray Diffraction ◽  
X Ray ◽  
Sandy Shale ◽  
Heterogeneous Nature ◽  
Niger Delta Basin ◽  
Shaly Sandstone

The sediment of #3 Well of the Greater Ughelli Depobelt are represented by sand and shale intercalation. In this study, lithofacies analysis and X-ray diffraction technique were used to characterize the sediments from the well. The lithofacies analysis was based on the physical properties of the sediments encountered from the ditch cuttings.  Five lithofacies types of mainly sandstone, clayey sandstone, shaly sandstone, sandy shale and shale and 53 lithofacies zones were identified from 15 ft to 11295 ft. The result of the X-ray diffraction analysis identified that the following clay minerals – kaolinite, illite/muscovite, sepiolite, chlorite, calcite, dolomite; with kaolinite in greater percentage. The non-clay minerals include quartz, pyrite, anatase, gypsum, plagioclase, microcline, jarosite, barite and fluorite; with quartz having the highest percentage. Therefore, due to the high percentage of kaolinite in #3 well, the pore filing kaolinite may have more effect on the reservoir quality than illite/muscovite, chlorite and sepiolite. By considering the physical properties, homogenous and heterogeneous nature of the #3 Well, it would be concluded that #3 Well has some prospect for petroleum and gas exploration.

Finite-Element Modeling of Spontaneous Potential in an Axisymmetric Reservoir Model with Account of Its Shale Content

2021 ◽  
Author(s):  
Mikhail Epov ◽  
Anastasia Glinskikh ◽  
Oleg Nechaev
Keyword(s):  
Finite Element ◽  
Finite Element Modeling ◽  
Western Siberia ◽  
Potential Method ◽  
Reservoir Model ◽  
Spontaneous Potential ◽  
Element Modeling ◽  
Argillaceous Material ◽  
Experimental Approaches ◽  
Shaly Sandstone

(1) The article is devoted to the development of a theoretical and algorithmic basis for numerical modeling of the spontaneous potential method (SP) as applied to the study of sandy-argillaceous reservoirs. (2) In terms of coupled flows, we consider a physical-mathematical model of SP signals from an electrochemical source, with regard to the case of fluid-saturated shaly sandstone. (3) An algorithm for 2D finite-element modeling of SP signals was developed and implemented in software, along with its internal and external testing with analytical solutions. The numerical SP modeling was carried out, with determining the dependences on the reservoir thickness and porosity, the amount of argillaceous material and the type of minerals. We performed a comparative analysis of the simulated and field SP data, using the results of laboratory core examinations taken from wells in a number of fields in the Latitudinal Ob Region of Western Siberia. (4) The results of the study may be used either for the development of the existing SP techniques, by providing them with a consistent computational model, or for the design of new experimental approaches.

A NOVEL WIRELINE LOGS BASED APPROACH FOR ASSESSMENT OF MINERAL CONCENTRATIONS IN ORGANIC SHALE

Oil Shale ◽  
2014 ◽  
Vol 31 (2) ◽  
pp. 132 ◽  
Author(s):  
M TAN ◽  
Y ZOU ◽  
X WANG ◽  
Y GUO
Keyword(s):  
Wireline Logs ◽  
Mineral Concentrations ◽  
Organic Shale
Sign in / Sign up

Export Citation Format

Share Document