Electrofacies in gas shale from well log data via cluster analysis: A case study of the Perth Basin, Western Australia

2014 ◽  
Vol 6 (3) ◽  
Author(s):  
Amir Torghabeh ◽  
Reza Rezaee ◽  
Reza Moussavi-Harami ◽  
Biswajeet Pradhan ◽  
Mohammad Kamali ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Gamma Ray ◽  
Cost Effective ◽  
Gas Production ◽  
Sonic Log ◽  
Cost Effective Method ◽  
Distance Data ◽  
Resistivity Log ◽  
Gamma Ray Log

AbstractIdentifying reservoir electrofacies has an important role in determining hydrocarbon bearing intervals. In this study, electrofacies of the Kockatea Formation in the Perth Basin were determined via cluster analysis. In this method, distance data were initially calculated and then connected spatially by using a linkage function. The dendrogram function was used to extract the cluster tree for formations over the study area. Input logs were sonic log (DT), gamma ray log (GR), resistivity log (IND), and spontaneous potential (SP). A total of 30 reservoir electrofacies were identified within this formation. Integrated geochemical and petrophysics data showed that zones with electrofacies 3, 4, 9, and 10 have potential for shale gas production. In addition, the results showed that cluster analysis is a precise, rapid, and cost-effective method for zoning reservoirs and determining electrofacies in hydrocarbon reservoirs.

scholarly journals Geothermal modelling and its application to hydrocarbon generation from agbada formation. a case study of USANi field, Niger delta basin, Nigeria

2017 ◽  
Vol 5 (2) ◽  
pp. 75
Author(s):  
Godwin Aigbadon ◽  
Anthony Okoro ◽  
Elesius Akpunonu ◽  
Rosemary Nimnu ◽  
Azuka Ocheli
Keyword(s):  
Gamma Ray ◽  
Geothermal Gradient ◽  
Hydrocarbon Generation ◽  
Sonic Log ◽  
Resistivity Logs ◽  
Source Rock Evaluation ◽  
Geothermal Model ◽  
Niger Delta Basin ◽  
Gamma Ray Log

The geothermal model was done with the integration of surface. Subsurface temperature's data and formation depth values from suites of well log in the study field. The well comprises Gamma-ray log (GR log), Spontaneous Potential logs (SP log), Resistivity logs, Formationdensity, Neutron log and Sonic log. The suites of welllog within the studied sequences penetrates Agbada and the Benin Formation. The Benin Formation comprises mainly of continental sands, and the Agbada Formation consist of alternating sequence of sand and shales within the study wells. The estimated thickness and temperature values within the study field falls within the range from 1357- 3500m and 101 O C – 120.5 O C with estimated geothermal gradient range of (0.028 - 0.03 O C/100m) in the field. The geo-temperatures results range of 101.60 O C – 119.60 OCat modeled depth of 1357m- 3500m, indicating that the shale sequence at the basal path of the Agbada Formation is thermally matured with sufficient organic matter to generate hydrocarbon in the study field as earlier believe to be immature and cannot generate hydrocarbon. The geothermal model can be applicable to any sedimentary basin in the world. This work is also an important tool in source rock evaluation to compliment petroleum geochemistry and position the hydrocarbon generating window of the study field.

Seismic characterization and origin of clinoforms in lacustrine depositional environments: a case study from the Cretaceous of the South Atlantic

2020 ◽  
pp. SP509-2019-148
Author(s):  
Andrew J. Barnett ◽  
Lucy Fu ◽  
Tolu Rapasi ◽  
Cinzia Scotellaro ◽  
Jaydip Guha ◽  
...  
Keyword(s):  
Sediment Transport ◽  
Lower Energy ◽  
Gamma Ray ◽  
Depositional Environments ◽  
Longshore Sediment Transport ◽  
Seismic Characterization ◽  
Bona Fide ◽  
Flooding Events ◽  
Gamma Ray Log

AbstractThe lacustrine Itapema Formation in the Santos Basin locally comprises 102 m thick clinoforms identified seismically and corroborated by several well penetrations. Individual clinoforms, as proven by well penetrations, are composed of 102 m thick successions of basinward-dipping molluscan grainstones and rudstones. Manual dip picking of borehole images shows upward-increasing dips consistent with seismic geometries and a predominance of longshore sediment transport. Clinoforms are bound at their top and base by strata with significantly lower dips recognizable on both seismic and borehole images. Elevated gamma-ray log responses together with sidewall core samples indicate that these intervals correspond to more argillaceous facies which are interpreted as lake flooding events. While the existence of bona fide clinoforms is demonstrated by a range of subsurface data, their precise origin remains enigmatic. The majority of the bivalve genera that make up the grain-supported carbonates appear to be infaunal or semi-infaunal. As such the clinoforms represent large bars produced through the re-working of bivalves from lower-energy depositional environments by shore-parallel currents.

Stern Flap for Resistance Reduction of Planing Hull Craft: A Case Study with a Fast Crew Boat Model

2012 ◽  
Author(s):  
Omar Yaakob ◽  
Suhaili Shamsuddin ◽  
Kho King Koh
Keyword(s):  
Reduction Rate ◽  
Cost Effective ◽  
Systematic Investigation ◽  
Percent Reduction ◽  
Geometrical Characteristics ◽  
Resistance Reduction ◽  
Cost Effective Method ◽  
Zero Degree ◽  
Resistance Performance

Kajian terhadap pelbagai cara mengurangkan rintangan bot peronda telah dilakukan oleh ramai penyelidik. Kaedah yang dikaji termasuk penggunaan kepak buritan, baji buritan dan suntikan gelembung mikro. Walau bagaimanapun, disebabkan oleh sifatnya yang mudah dan praktikal, kepak buritan didapati amat berpotensi. Kertas kerja ini membentangkan kajian terhadap kesan kepak buritan terhadap prestasi rintangan bot kelasi berbentuk planing. Ujian model dijalankan bagi membuktikan keberkesanan kepak bagi mengurangkan rintangan. Lima kepak berlainan telah digunakan dalam rangka kajian sistematik bagi menentukan ciri geometrik optimum kepak buritan. Hasil ujian model menunjukkan empat kepak menambah rintangan kapal manakala kepak kelima pada sudut sifar mengurangkan rintangan sehingga 7.2 peratus pada 23 knots dan pengurangan purata sekitar 4.5 peratus. Pada 23 knots, pengurangan 8.2 peratus kuasa berkesan diperolehi. Kata kunci: Reka bentuk bot peronda, ujian model, pesawat laju The study on various methods of reducing the resistance of patrol craft have been carried out by many researchers. These methods included the application of stern flaps, stern wedges, and microbubble injection. However, due to its simplicity and practicality, stern flap is the most promising and cost effective method. The effect of a stern flap on the resistance performance of the planing hull crew boat is presented. Model tests were conducted to prove the effectiveness of the stern flap on reducing planing hull craft resistance. Five different stern flap designs were tested as part of systematic investigation to determine the optimum geometrical characteristics of the stern flap. Results of model resistance experiments showed that four of the flaps tested showed an increase in resistance while the flap at zero degree angle reduced the total resistance by 7.2 percent at 23 knots, and an average reduction rate of 4.5 percent. At 23 knots, an 8.2 percent reduction in effective power was predicted. Key words: Patrol boats design, model testing, fast craft

scholarly journals Spectral gamma ray logging: A cost-effective method for uranium exploration

2018 ◽  
Vol 41 (1) ◽  
pp. 42
Author(s):  
G Jegannathan ◽  
V Veluswamy ◽  
BRam Mohan Reddy ◽  
PravinKumar Sharma
Keyword(s):  
Gamma Ray ◽  
Cost Effective ◽  
Cost Effective Method ◽  
Uranium Exploration

scholarly journals The colour analysis method applied to homogeneous rocks

Geologos ◽  
2015 ◽  
Vol 21 (4) ◽  
pp. 233-239
Author(s):  
Amadé Halász ◽  
Ákos Halmai
Keyword(s):  
Radioactive Waste ◽  
Rock Type ◽  
Cost Effective ◽  
Analysis Method ◽  
The Core ◽  
Cost Effective Method ◽  
Natural Gamma ◽  
Computer Aided ◽  
High Level

Abstract Computer-aided colour analysis can facilitate cyclostratigraphic studies. Here we report on a case study involving the development of a digital colour analysis method for examination of the Boda Claystone Formation which is the most suitable in Hungary for the disposal of high-level radioactive waste. Rock type colours are reddish brown or brownish red, or any shade between brown and red. The method presented here could be used to differentiate similar colours and to identify gradual transitions between these; the latter are of great importance in a cyclostratigraphic analysis of the succession. Geophysical well-logging has demonstrated the existence of characteristic cyclic units, as detected by colour and natural gamma. Based on our research, colour, natural gamma and lithology correlate well. For core Ib-4, these features reveal the presence of orderly cycles with thicknesses of roughly 0.64 to 13 metres. Once the core has been scanned, this is a time- and cost-effective method.

scholarly journals Quantification of Kaolinite and Halloysite Using Machine Learning from FTIR, XRF, and Brightness Data

Minerals ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1350
Author(s):  
Pieter I. Du Plessis ◽  
Michael F. Gazley ◽  
Stephanie L. Tay ◽  
Eliza F. Trunfull ◽  
Manuel Knorsch ◽  
...  
Keyword(s):  
Cost Effective ◽  
X Ray Diffraction ◽  
Yilgarn Craton ◽  
Weathering Profile ◽  
X Ray ◽  
Clay Deposits ◽  
Cost Effective Method ◽  
Cost Effective Alternative ◽  
Quantified Analysis

Quantification of halloysite and kaolinite in clay deposits from X-ray diffraction (XRD) commonly requires extensive sample preparation to differentiate the two phyllosilicates. When assessing hundreds of samples for mineral resource estimations, XRD analyses may become unfeasible due to time and expense. Fourier transform infrared (FTIR) analysis is a fast and cost-effective method to discriminate between kaolinite and halloysite; however, few efforts have been made to use this technique for quantified analysis of these minerals. In this study, we trained machine- and deep-learning models on XRD data to predict the abundance of kaolinite and halloysite from FTIR, chemical composition, and brightness data. The case study is from the Cloud Nine kaolinite–halloysite deposit, Noombenberry Project, Western Australia. The residual clay deposit is hosted in the saprolitic and transition zone of the weathering profile above the basement granite on the southwestern portion of the Archean Yilgarn Craton. Compared with XRD quantification, the predicted models have an R2 of 0.97 for kaolinite and 0.96 for halloysite, demonstrating an excellent fit. Based on these results, we demonstrate that our methodology provides a cost-effective alternative to XRD to quantify kaolinite and halloysite abundances.

scholarly journals Identification of Geo – Hazard Using Pore Pressure Analysis in ‘MAC’ Field, Niger Delta

2021 ◽  
Keyword(s):  
Pore Pressure ◽  
Gamma Ray ◽  
Pressure Data ◽  
Abnormal Pressure ◽  
Pore Pressure Prediction ◽  
Wireline Logs ◽  
Formation Pore Pressure ◽  
Resistivity Log ◽  
Gamma Ray Log ◽  
Pressure Analysis

Identification of geo-hazard zones using pore pressure analysis in ‘MAC’ field was carried out in this research. Suite of wireline logs from four wells and RFT pressure data from two wells were utilized. Lithologic identification was done using gamma ray log. Resistivity log was used to delineate hydrocarbon and non-hydrocarbon formations. Well log correlation helps to see the lateral continuity of the sands. Pore pressure prediction was done using integrated approaches. The general lithology identified is alternation of sand and shale units. The stratigraphy is typical of Agbada Formation. Three reservoirs delineated were laterally correlated. Crossplot of Vp against density (Rho) colour coded with depth revealed that disequilibrium compaction is the main overpressure generating mechanism in the field. Prediction of overpressure by normal compaction trend was generated and plot of interval transit time against depth show that there is normal compaction from 250m to about 1700 m on MAC-01, but at a depth of about 1800m, there was abnormal pressure build up that shows the onset of overpressure. A relatively normal compaction was observed on MAC-02 until a depth of about 2100m where overpressure was suspected. The prediction of formation pore pressure using Eaton’s and Bower’s method to determine the better of the two methods to adopt for pore pressure prediction shows that the pore pressure prediction using Eaton’s method gave a better result similar to the acquired pressure in the field. Hence Eaton’s method appears to be better suited for formation pore pressure estimation in ‘MAC’ field. The validation of the pore pressure analysis results with available acquired pressure data affirmed the confidence in the interpreted results for this study.

scholarly journals A cost-effective method to monitor vegetation changes in steppes ecosystems: A case study on remote sensing of fire and infrastructure effects in eastern Mongolia

2021 ◽  
Vol 132 ◽  
pp. 108331
Author(s):  
Batnyambuu Dashpurev ◽  
Karsten Wesche ◽  
Yun Jäschke ◽  
Khurelpurev Oyundelger ◽  
Thanh Noi Phan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Cost Effective ◽  
Vegetation Changes ◽  
Cost Effective Method ◽  
Eastern Mongolia

SUSTAINABLE IMPACT OF BUILDING ENERGY RETROFIT MEASURES

2017 ◽  
Vol 12 (3) ◽  
pp. 69-84 ◽  
Author(s):  
Amirhosein Jafari ◽  
Vanessa Valentin
Keyword(s):  
Social Impact ◽  
Cost Effective ◽  
Building Energy ◽  
Economic Benefits ◽  
Environmental Benefits ◽  
Energy Retrofit ◽  
Cost Effective Method ◽  
Impact Index ◽  
The Impact

Energy retrofitting is argued to be the most feasible and cost-effective method for improving existing buildings' energy efficiency. As a sustainable development, building energy retrofits require the consideration and integration of all three sustainability dimensions: environmental, economic and social. The objective of this study is to estimate and compare the sustainable impact of building energy retrofits to determine the maximum sustainable benefit when implementing different energy-related measures. The proposed analysis consists of integrating three approaches for evaluating these benefits. Economic benefits are measured by estimating the payback period of energy-related measures, environmental benefits are measured by estimating the CO2 equivalent saving per year due to the implementation of energy-related measures, and social benefits are measured by defining a “social impact index” that establishes the impact of energy-related measures on buildings' users. A case study is used to demonstrate the framework for four potential scenarios. The results show that for the case study, energy-related “controlling” and “upgrading mechanical system” measures have the highest sustainable impact among the identified energy retrofitting measures.

MACHINE LEARNING FOR PRODUCTIVITY PREDICTION IN HETEROGENEOUS CARBONATE GAS RESERVOIRS, CENTRAL SICHUAN BASIN, CHINA

2021 ◽  
Author(s):  
Zuoan Zhao ◽  
◽  
Dali Wang ◽  
Keyword(s):  
Machine Learning ◽  
Gamma Ray ◽  
Pore Space ◽  
Gas Production ◽  
Carbonate Reservoir ◽  
Production Rates ◽  
Gas Reservoirs ◽  
Data Set ◽  
Productivity Prediction ◽  
Gamma Ray Log

An approach of machine learning was used to evaluate and predict the production of the heterogeneous carbonate gas reservoirs in the horizontal development wells of the late Precambrian Dengying Formation. The present data set of machine learning consists of gamma ray log, laterolog, high-resolution electrical image logs, and production rate data. The previous data set acquired the conventional openhole logs, including gamma ray log, neutron-density log, sonic log, laterolog, and dipole acoustic log. The challenge in the previous data set was that the training process for machine learning was not convergent. It was most likely that the conventional log responses did not fully correspond to the productivity of the heterogenous carbonate gas reservoirs. Forty-one wells associated with the present data set were used to set up the training sample data set for the machine learning to the productivity prediction of the carbonate gas reservoirs. The data set construction includes log depth shift, calibrated image log creation, classification of reservoir types from core and carbonate reservoir heterogeneity variables extraction from image logs. Core observation and core laboratory analysis indicate that the pore space of the carbonate gas reservoirs mainly consists of vugs, caves, and fractures. However, the vugs and caves are selectively developed and randomly distributed both laterally and vertically. This represents a complex heterogeneous carbonate reservoir in which the vugs and caves are key contributor to the total pore space of the carbonate gas reservoir. The attributes of the vugs and caves can be extracted from the electrical image logs, including connectedness, surface proportion, size, and thickness of vug, and cave zones. Six horizontal development wells were used to validate the machine learning approach. The predicted gas production rates in the four wells separately were 700,000 m3/d, 2,000,000 m3/d, 800,000 m3/d, 300,000 m3/d, 1,100,000 m3/d and 1,180,000 m3/d, and the respective actual gas production rates are 1,019,790 m3/d, 1,820,000 m3/d, 800,000 m3/d, 396,000 m3/d , 1,700,000 m3/d, and 1,411,900 m3/d. The machine learning workflow and approach provided satisfactory results in the six horizontal wells. Subsequently, the electrical image logs have run in the standard logging program in the more than 50 horizontal development wells.

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