TANAMI-1 OIL DISCOVERY: BARROW SUB-BASIN

1992 ◽  
Vol 32 (1) ◽  
pp. 86
Author(s):  
V. Beales ◽  
E.A. Howell
Keyword(s):  
Lower Cretaceous ◽  
Analysis Data ◽  
Core Analysis ◽  
Residual Oil ◽  
The South ◽  
Reservoir Properties ◽  
Offshore Area ◽  
Early Tertiary ◽  
Porosity And Permeability ◽  
Made In

The Tanami oil discovery was made in 1991. The discovery well was drilled from an onshore location on Varanus Island and deviated into the offshore area. A small, 6.8 m oil column was intersected at the top of the Lower Cretaceous Flag Sandstone Member of the Barrow Group. Beneath the moveable oil, a residual zone of 19.8 m was encountered.Petrophysical, petrological and core analysis data indicate different reservoir properties in the moveable oil, residual oil and water zones. These results show that the oil in place has retarded diagenesis and associated reduction in porosity and permeability values.The residual oil column is interpreted to be a result of northward structural tilting in the early Tertiary, causing oil previously trapped to be spilled to the south.

Research on the Distriution Rules and Calculation Method of the Parameters of Reservoir of Putaohua Groups in Yushulin Oil Field

2014 ◽  
Vol 490-491 ◽  
pp. 468-472
Author(s):  
Ke Zeng ◽  
Zheng Zhou ◽  
Mei Ling Zhang
Keyword(s):  
Physical Property ◽  
Analysis Data ◽  
Well Logging ◽  
Oil Field ◽  
Core Analysis ◽  
The Core ◽  
Reservoir Property ◽  
Porosity And Permeability ◽  
The Relationship ◽  
Parameters Calculation

Based on the Putaohua groups in Yushulin oil field, and through the statiscics and analyses, weve found that the reservoir property of this area is in the range of specially low permeability level. So due to the low porosity and permeability, its necessary to do some reaearch on the parameters calculation method.This papers analysed the relationships between the physical property parameters such as porosity, permeability, shale content and the well logging responses such as AC, SP, GR, then we built the distribution rules histograms of each physical property parameter. And we got the distribution situations of the parameters of the oil groups. Through the multiple regression, we built the relationship formulas between the reservoir property parameters and the well logging responses by using the core analysis data of 53 test wells. Afetr comparing the parameters of calculation and the core analysis data, we found that the deviation is small, which meets the production requires of oil field.

scholarly journals PETROGRAPHIC CHARACTERISTICS OF THE RESERVOIR ROCKS IN THE BAT-UPPER JURASSIC DEPOSITS OF THE SOUTH OF WESTERN-SIBERIAN PETROLEUM BASIN

2019 ◽  
Vol 2 (1) ◽  
pp. 25-31
Author(s):  
Lyudmila Vakulenko ◽  
Aleksey Popov ◽  
Sergey Rodyakin ◽  
Evgeniy Khabarov ◽  
Peter Yan
Keyword(s):  
Oil And Gas ◽  
Upper Jurassic ◽  
The South ◽  
Reservoir Properties ◽  
Petrographic Composition ◽  
Reservoir Rocks ◽  
Regional Sources ◽  
Porosity And Permeability ◽  
Maximum Parameters ◽  
Petroleum Basin

The features of the petrographic composition of the bath-upper Jurassic silt-sand rocks exposed by wells in the South of the West Siberian oil and gas basin are considered. The study is focused on the parameters that had a significant influence on the reservoir properties of rocks: granulometric and mineral-petrographic composition of the clastic part of rocks, cement content, structure and composition. Some conclusions are drawn on the spatial distribution of rocks of different composition within the subisochronous sedimentary complexes. It is assumed that significant variations in their composition are caused by a complex combination of varying degrees of interdependent factors: influence of local and regional sources of clastic material, peculiarities of redistribution of material during its transportation and sedimentation, and post-sedimentation changes. Most variable values of reservoir properties, with a recorded maximum parameters of porosity and permeability are obtained for the rocks of Medium-Upper Oxford complex on Verkhnetarskaya, Dedovskaya, Basinskaya, Veselovskaya, to a lesser extent, Kasmanskaya, Vostochnaya and Tai-Dasskaya drilling sites.

scholarly journals Sedimentology, geochemistry and reservoir properties of Upper Jurassic deep marine sediments (Hareelv Formation) in the Blokelv-1 borehole, Jameson Land Basin, East Greenland

2018 ◽  
pp. 39-64
Author(s):  
Morten Bjerager ◽  
Claus Kjøller ◽  
Mette Olivarius ◽  
Dan Olsen ◽  
Niels H. Schovsbo
Keyword(s):  
Oxygen Depletion ◽  
Upper Jurassic ◽  
High Density ◽  
Core Analysis ◽  
Reservoir Properties ◽  
East Greenland ◽  
Sea Floor ◽  
The Core ◽  
Trace Metal Content ◽  
Porosity And Permeability

The fully cored Blokelv-1 borehole was drilled through Upper Jurassic strata in the central part of the Jameson Land Basin, central East Greenland. The borehole reached a total depth of 233.8 m with nearly 100% recovery of high-quality core. An extensive analytical programme was undertaken on the core; sedimentological interpretation and reservoir characterisation were based on facies analysis combined with conventional core analysis, bulk geochemistry and spectral gamma and density scanning of the core. The Upper Jurassic Hareelv Formation was deposited in relatively deep water in a slope-to-basin setting where background sedimentation was dominated by suspension settling of organic-rich mud in oxygen-depleted conditions. Low- and high-density gravity-flow sandstone interbeds occur throughout the cored succession. About two-thirds of the high-density turbidite sandstones were remobilised and injected into the surrounding mud-rock. The resulting succession comprises nearly equal amounts of mudstones and sandstones in geometrically complex bodies. Ankerite cementation occurs in 37% of the analysed sandstones in varying amounts from minor to pervasive. Such ankerite-cemented sandstones can be identified by their bulk geochemistry where Ca > 2 wt%, Mg > 1 wt% and C > 1 wt%. The analysed mudstones are rich in Al, Fe, Ti and P and poor in Ca, Mg, Na and Mn. The trace-metal content shows a general increase in the upper part of the core reflecting progressive oxygen depletion at the sea floor. The reservoir properties of the Blokelv-1 sandstones were evaluated by both conventional core analysis and using log-derived porosity and permeability curves. The high-density turbidite beds and injectite bodies are a few centimetres to several metres thick and show large variations in porosity and permeability, in the range of 6–26 % for porosity and 0.05–400 mD for permeability. Individual sandstone units that are 1–7 m thick yield a net vertical reservoir thickness of 40 m with porosities of 15–26% and permeabilities of 1–200 mD. Heterolithic sandstone–mudstone units are generally characterised by poor reservoir quality with porosities of 2–14% and permeabilities of 0.1–0.6 mD.

scholarly journals Porosity and Permeability Measurements Integration of The Upper Cretaceous in Balad Field, Central Iraq

2021 ◽  
Vol 54 (1B) ◽  
pp. 24-42
Author(s):  
Fawzi Al-Beyati
Keyword(s):  
Image Analysis ◽  
Log Analysis ◽  
Core Analysis ◽  
Well Log ◽  
Reservoir Properties ◽  
Thin Sections ◽  
Core Samples ◽  
Porosity And Permeability ◽  
Well Log Analysis ◽  
Porosity Range

The corrected porosity image analysis and log data can be used to build 3D models for porosity and permeability. This can be much realistic porosity obtainable because the core test data is not always available due to high cost which is a challenge for petroleum companies and petrophysists. Thus, this method can be used as an advantage of thin section studies and for opening horizon for more studies in the future to obtain reservoir properties. Seventy-two core samples were selected and the same numbers of thin sections were made from Khasib, Sa`di, and Hartha, formations from Ba-1, Ba-4, and Ba-8 wells, Balad Oilfield in Central Iraq to make a comprehensive view of using porosity image analysis software to determine the porosity. The petrophysical description including porosity image analysis was utilized and both laboratory core test analysis and well log analysis were used to correct and calibrate the results. The main reservoir properties including porosity and permeability were measured based on core samples laboratory analysis. The results of porosity obtained from well log analysis and porosity image analysis method are corrected by using SPSS software; the results revealed good correlation coefficients between 0.684 and 0.872. The porosity range values are 9-16% and 9-27% for Khasib and Sa’di in Ba-1 Well, respectively; 10-21%, 9-25%, and 16-27% for Khasib, Sa’di and Hartha in Ba-4 Well, respectively; and 11-24% and 15-24% for Khasib and Hartha in Ba-8 Well, respectively according to petrographic image analysis. By using the laboratory core analysis, the porosity range values are 12-26% and 17-24% for Khasib and Sa’di in Ba-1 Well, respectively; 6-28% and 14-27% for Sa’di and Hartha in Ba-4 Well, respectively; and 17-19% and 15-24% for Sa’di and Hartha in Ba-8 Well, respectively. Finally, the well log analysis showed that the porosity range values are 11-16% and 7-27% for Khasib and Sa’di in Ba-1 Well, respectively; 4-18%, 21-26%, and 16-19% for Khasib, Sa’di and Hartha in Ba-4 Well, respectively; and 9-24% and 15-23% for Khasib and Hartha in Ba-8 Well, respectively. The permeability range values based on laboratory core analysis are 1.51-8.97 md and 0.29-2.77 md for Khasib and Sa’di in Ba-1 Well, respectively; 0.01-24.5 md and 0.28-6.47 md for Sa’di and Hartha in Ba-4 Well, respectively; and 0.86-2.25 md and 0.23-3.66 for Sa’di and Hartha in Ba-8 Well, respectively.

scholarly journals Facies models of the Achimov Formation of East-Urengoiskoe license as the basis for optimizing exploration and field development patterns

Georesursy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 55-61
Author(s):  
Alena V. Khramtsova ◽  
Sergey I. Pakhomov ◽  
Nikita Y. Natchuk ◽  
Мaria P. Kalashnikova ◽  
Sergey V. Romashkin ◽  
...  
Keyword(s):  
Seismic Data ◽  
Lower Cretaceous ◽  
Comprehensive Analysis ◽  
Core Analysis ◽  
Reservoir Properties ◽  
Development Patterns ◽  
Field Development ◽  
Submarine Fans ◽  
Well Correlation ◽  
Marine Basin

The results of sedimentological core analysis of the Achimov Formation (Upper Valanginian, Lower Cretaceous) confirm that it was formed by higher efficiency systems of submarine fans in (relatively) deep marine basin. Lithofacies models of Ach5-6 were generated, well correlation was performed based on the comprehensive analysis of core, well logging and seismic data. Distributary channels and proximal parts of depositional lobes are characterized by the best reservoir properties.

El viaje botánico de Pierre Edmond Boissier por el sur de España (1837). The botanical trip of Pierre Edmond Boissier by the South of Spain

2010 ◽  
Vol 35 ◽  
pp. 5-21 ◽  
Author(s):  
Antonio González Bueno
Keyword(s):  
The South ◽  
200Th Anniversary ◽  
Made In

Español.  Coincidiendo con el 200 aniversario del nacimiento de Pierre-Edmond Boissier (1810-1885), presentamos un análisis de su primer viaje por el Sur de España, realizado en 1837: estudiamos los motivos que le impulsaron a llevarlo a cabo, la información que tuvo disponible, el viaje en sí y la publicación de sus resultados en la más señera de sus obras, el Voyage botanique dans le midi de l’Espagne… (París, 1839-1845).English. In the 200th anniversary of the birth of Pierre-Edmond Boissier (1810-1885) we analized his first trip to the south of Spain, made in 1837, the reasons that prompted him to carry out, the information available, the trip itself and the publication of their results in the most outstanding of his works, the Voyage botanique dans le midi de l’Espagne ... (Paris, 1839-1845).

Petrophysical Facies Classification Based on Fuzzy Inference Networks

2013 ◽  
Vol 634-638 ◽  
pp. 4017-4021
Author(s):  
Jun Hui Pan ◽  
Hui Wang ◽  
Xiao Gang Yang
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Reasoning ◽  
Real Data ◽  
Analysis Data ◽  
Classification Model ◽  
Core Analysis ◽  
Development Zone ◽  
The Real ◽  
Facies Classification ◽  
Quantitative Indicators

Aiming at the petrophysical facies recognition, a novel identification method based on the weighted fuzzy reasoning networks is proposed in the paper. First, the types and indicators are obtained from core analysis data and the results given by experts, and then the standard patterning database of reservoir petrophysical facies is established. Secondly, by integrating expert experiences and quantitative indicators to reflect the change of petrophysical facies, the classification model of petrophysical facies based on the weighted fuzzy reasoning networks is designed. The preferable application results are presented by processing the real data from the Sabei development zone of Daqing oilfield.

A Study of the Chemical and Physical Characteristics of the Soils from the South of Piauí for Soil-Cement Brick Production

2016 ◽  
Vol 869 ◽  
pp. 112-115 ◽  
Author(s):  
Francisca Pereira de Araújo ◽  
Edson Cavalcanti Silva Filho ◽  
João Sammy Nery de Souza ◽  
Josy Anteveli Osajima ◽  
Marcelo Barbosa Furtini
Keyword(s):  
Organic Matter ◽  
Particle Density ◽  
Environmentally Friendly ◽  
Physical Characteristics ◽  
Chemical Characteristics ◽  
The South ◽  
Physical Chemical ◽  
Soil Cement ◽  
Made In

Soil-cement bricks are good examples of environmentally friendly products. This brick is the combination of soil with compacted cement with no combustion in its production. In this work the physical chemical characteristics of the soil from Piaui for producing this material were investigated. Samples of the soil were collected in three potteries from the county of Bom Jesus and pH analysis were carried out, as well as the rate of organic matter, texture, particle density, limits of liquidity and plasticity rates. The results have shown that the soils have acid tones (pH 5,49 a 6,11), which can be neutralized by adding cement, and organic matter percentages up to 1%. The samples have shown predominantly clay-rich textures with adequate plasticity limits, however, values of liquidity limits and particle density above recommended. Altogether, these soils tend to present viability concerning soil-cement brick production, provided that corrections with additives are made in order to minimize this effect.

Significance of The Sedimentology and Stratigraphy for Identification of Low Contras Low Resistivity zones in a Clastic Outcrop of The Upper Talang Akar Formation, Musi Banyuasin, Indonesia

2021 ◽  
Author(s):  
A. F. H. Surbakti
Keyword(s):  
Clay Minerals ◽  
Coarse Grained ◽  
The South ◽  
Reservoir Properties ◽  
Low Contrast ◽  
Facies Distribution ◽  
Low Resistivity ◽  
Different Sources

The Talang Akar Formation is one of the hydrocarbon-producing reservoirs of the South Sumatra Basin. This basin is filled from two different sources in the Eastern part and Western part paleo-high. The bottom Talang Akar consists of coarse-grained sandstone, and the upper part constrains intercalation of sandstone and shale, known as low resistivity low contrast zone (LRLC). The Talang Akar Formation from Air Batu and Sukomoro confers an excellent probability to observe and define LRLC zones over systematic approaches. This paper will provide an analogue of the LRLC reservoir zone by analyzing the relation between facies distribution and reservoir properties, including detailed shale structure. Facies distribution was obtained from the outcrop stratigraphic profile. The reservoir properties are identified by the Thomas Stieber plot and the petrographic section. Seven facies of Talang Akar Formation had been identified, which are: 1) planar cross-bedded sandstone (PCBS), 2) trough cross-bedded sandstone (TCBSS), 3) laminated sandstone (LSS), 4) heterolytic sandstone (HSS), 5) clay-rich sandstone (CSS), 6) mudstone (MS), 7) scour conglomeratic sandstone (SCSS). There are several types of shale distribution: structural shale, dispersed shale, and laminar shale. The laminar and dispersed shale consists of most of the reservoir and fills the pore. The clay structure deduces the disparity in the facies-porosity correlation. The finding of this study revealed that the LRLC zones are caused by lamination structures, thin intercalation layers, heterolytic and clay minerals.

Machine Learning for Multiple Petrophysical Properties Regression Based on Core Images and Well Logs in a Heterogenous Reservoir

2021 ◽  
Author(s):  
Tao Lin ◽  
Mokhles Mezghani ◽  
Chicheng Xu ◽  
Weichang Li
Keyword(s):  
Machine Learning ◽  
Model Building ◽  
Image Features ◽  
Well Logs ◽  
Model Complexity ◽  
Rock Properties ◽  
Core Analysis ◽  
Petrophysical Properties ◽  
Blind Test ◽  
Porosity And Permeability

Abstract Reservoir characterization requires accurate prediction of multiple petrophysical properties such as bulk density (or acoustic impedance), porosity, and permeability. However, it remains a big challenge in heterogeneous reservoirs due to significant diagenetic impacts including dissolution, dolomitization, cementation, and fracturing. Most well logs lack the resolution to obtain rock properties in detail in a heterogenous formation. Therefore, it is pertinent to integrate core images into the prediction workflow. This study presents a new approach to solve the problem of obtaining the high-resolution multiple petrophysical properties, by combining machine learning (ML) algorithms and computer vision (CV) techniques. The methodology can be used to automate the process of core data analysis with a minimum number of plugs, thus reducing human effort and cost and improving accuracy. The workflow consists of conditioning and extracting features from core images, correlating well logs and core analysis with those features to build ML models, and applying the models on new cores for petrophysical properties predictions. The core images are preprocessed and analyzed using color models and texture recognition, to extract image characteristics and core textures. The image features are then aggregated into a profile in depth, resampled and aligned with well logs and core analysis. The ML regression models, including classification and regression trees (CART) and deep neural network (DNN), are trained and validated from the filtered training samples of relevant features and target petrophysical properties. The models are then tested on a blind test dataset to evaluate the prediction performance, to predict target petrophysical properties of grain density, porosity and permeability. The profile of histograms of each target property are computed to analyze the data distribution. The feature vectors are extracted from CV analysis of core images and gamma ray logs. The importance of each feature is generated by CART model to individual target, which may be used to reduce model complexity of future model building. The model performances are evaluated and compared on each target. We achieved reasonably good correlation and accuracy on the models, for example, porosity R2=49.7% and RMSE=2.4 p.u., and logarithmic permeability R2=57.8% and RMSE=0.53. The field case demonstrates that inclusion of core image attributes can improve petrophysical regression in heterogenous reservoirs. It can be extended to a multi-well setting to generate vertical distribution of petrophysical properties which can be integrated into reservoir modeling and characterization. Machine leaning algorithms can help automate the workflow and be flexible to be adjusted to take various inputs for prediction.

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