scholarly journals Studi Literatur Pendugaan Nilai Konduktivitas Hidraulik Dengan Menggunakan Data Uji Hidraulik Lapangan Dan Data Loging Geoteknik

2017 ◽  
Author(s):  
Tedy Agung Cahyadi ◽  
Irwan Iskandar ◽  
Sudarto Notosiswoyo ◽  
Lilik Eko Widodo

Konduktivitas hidraulik merupakan parameter yang sangat penting dalam pemodelan aliran airtanah. Parameter tersebut dapat diambil melalui pengujian packer test dan slug test . Mahalnya operasional pelaksanaan pengujian tersebut, memberikan dampak minimnya data kondutivitas hidraulik di lapangan. Konduktivitas hidraulik pada batuan yang terkekarkan memiliki kompleksitas (derajad heterogenitas dan anisotropi) yang lebih tinggi dibandingkan dengan konduktivitas hidraulik pada batuan sedimen. Untuk mengatasi minimnya data konduktivitas hidraulik, dalam studi literature ini akan dilakukan cara prediksi nilai konduktivitas hidraulik dengan menggunakan pendekatan metode HC-System. HC-System merupakan metode empirik yang melibatkan data-data geoteknik menduga nilai konduktivitas hidraulik di daerah yang tidak ada data pengukuran (terbatas pada titik pengukuran geoteknik). Data geoteknik tersebut terdiri dari Rock Quality Designation (RQD), Lithology Permeability Index (LPI), Depth Index (DI), and Gouge Content Index

2017 ◽  
Author(s):  
Lilik Eko Widodo ◽  
Tedy Agung Cahyadi ◽  
Sudarto Notosiswoyo ◽  
Eman Widijanto

Highly fractured rocks at Grasberg Mining in PT Freeport Indonesia (PTFI) lead to fractured groundwater flow media. Hydraulic conductivity of fractured rock has more complexity than that of porous rocks media. In this study, hydraulic conductivity (K) has been estimated according to HC-System based on Rock Quality Designation (RQD), Lithology Permeability Index (LPI), Depth Index (DI) and Gouge Content Designation (GCD). Numerical model of HC-System at Grasberg Mining in general can be expressed by the equation K = 2 x 10-6 x HC0.5571. The RQD data can be grouped into three ranges, i.e. first group that dominates over 80 % of the RQD data with K ranging between 1.9x10-8 – 2.3x10-7 m/s, second group that is within 40 – 80% of the RQD data with K falling between 2x10-8 – 7.2x10-7 m/s, and third group that takes part less than 40 % of RQD data with K ranging between 2.1x10-8 – 1.9x10-6 m/s. Based on the lithology, the hydraulic conductivity of rocks can be assinged as follows: igneous rock with K ranging 6.8x10-8 – 1.9x10-7 m/s, and sedimentary rock with K ranging 2.2x10-8 – 1.9x10-6 m/s. HC-System demonstrates good interpretation of hydraulic conductivity by means of clustering method, which uses geological and geotechnical data for hydrogeological characterization


2021 ◽  
Author(s):  
Said Beshry Mohamed ◽  
Sherif Ali ◽  
Mahmoud Fawzy Fahmy ◽  
Fawaz Al-Saqran

Abstract The Middle Marrat reservoir of Jurassic age is a tight carbonate reservoir with vertical and horizontal heterogeneous properties. The variation in lithology, vertical and horizontal facies distribution lead to complicated reservoir characterization which lead to unexpected production behavior between wells in the same reservoir. Marrat reservoir characterization by conventional logging tools is a challenging task because of its low clay content and high-resistivity responses. The low clay content in Marrat reservoirs gives low gamma ray counts, which makes reservoir layer identification difficult. Additionally, high resistivity responses in the pay zones, coupled with the tight layering make production sweet spot identification challenging. To overcome these challenges, integration of data from advanced logging tools like Sidewall Magnetic Resonance (SMR), Geochemical Spectroscopy Tool (GST) and Electrical Borehole Image (EBI) supplied a definitive reservoir characterization and fluid typing of this Tight Jurassic Carbonate (Marrat formation). The Sidewall Magnetic resonance (SMR) tool multi wait time enabled T2 polarization to differentiate between moveable water and hydrocarbons. After acquisition, the standard deliverables were porosity, the effective porosity ratio, and the permeability index to evaluate the rock qualities. Porosity was divided into clay-bound water (CBW), bulk-volume irreducible (BVI) and bulk-volume moveable (BVM). Rock quality was interpreted and classified based on effective porosity and permeability index ratios. The ratio where a steeper gradient was interpreted as high flow zones, a gentle gradient as low flow zones, and a flat gradient was considered as tight baffle zones. SMR logging proved to be essential for the proper reservoir characterization and to support critical decisions on well completion design. Fundamental rock quality and permeability profile were supplied by SMR. Oil saturation was identified by applying 2D-NMR methods, T1/T2 vs. T2 and Diffusion vs. T2 maps in a challenging oil-based mud environment. The Electrical Borehole imaging (EBI) was used to identify fracture types and establish fracture density. Additionally, the impact of fractures to enhance porosity and permeability was possible. The Geochemical Spectroscopy Tool (GST) for the precise determination of formation chemistry, mineralogy, and lithology, as well as the identification of total organic carbon (TOC). The integration of the EBI, GST and SMR datasets provided sweet spots identification and perforation interval selection candidates, which the producer used to bring wells onto production.


2019 ◽  
Vol 53 (3) ◽  
pp. 1485-1494 ◽  
Author(s):  
Jun Zheng ◽  
Xiaohong Wang ◽  
Qing Lü ◽  
Jianfeng Liu ◽  
Jichao Guo ◽  
...  

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