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INDONESIA
JOURNAL OF EARTH ENERGY ENGINEERING
Published by Universitas Islam Riau
ISSN : -     EISSN : 25409352     DOI : -
Core Subject : Science, Engineering,
Earth & Planetary Sciences Energy Engineering Materials Science & Nanotechnology
Journal of Earth Energy Engineering (eISSN 2540-9352) is a Bi-annual, open access, multi-disciplinary journal in earth science, energy, and engineering research issued by Department of Petroleum Engineering, Universitas Islam Riau. The journal is peer reviewed by experts in the scientific and engineering areas and also index in Directory of Research Journals Indexing (DRJI) and CrossRef Member.
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "Vol. 11 No. 2 (2022)" : 5 Documents clear
Analyze of Water Injection Performance Surveillance in “ATHENA” Field Andi Dewi; Firdaus; Deny Fatryanto
Journal of Earth Energy Engineering Vol. 11 No. 2 (2022)
Publisher : Universitas Islam Riau (UIR) Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jeee.2022.6356

Abstract

To measure the success of waterflood activities, we need evaluation and analysis. To support evaluation and analysis need to be done assessment of well connectivity to the response of injection wells, performance wells with Hall-plot and Voidage Replacement Ratio, and calculate water breakthrough time with method Buckley-Leverret whether according to the actual field. To examine these required supporting data such as field history, production and injection history, fluid level measurement data. The results of the study showed the well ATH-43 less response (poor response) and the well ATH-37 and ATH-33 gave good response (good response) and gain oil obtained by 8,196 barrels. The hall-plot evaluation showed that the well ATH-04 had no formation/normal damage, and the results of the VRR showed the VRR < 1. The results of the calculation of water breakthrough time calculations with actual show the well experiencing breakthrough earlier than the calculation. (Premature breakthrough).
Investigation of Horizontal Well for Cyclic Steam-Solvent Stimulation to Escalate Heavy Oil Production Ahmad Muraji Suranto; Allen Haryanto Lukmana; Ristiyan Ragil Putradianto; M Rizqi Asy'ari
Journal of Earth Energy Engineering Vol. 11 No. 2 (2022)
Publisher : Universitas Islam Riau (UIR) Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jeee.2022.8130

Abstract

Indonesia's oil reserves that have been exploited on a large scale are light oil because the recovery technique is much easier than the heavy oil. Generally, heavy oil has a high viscosity compared to light oil. In most cases, to reduce high oil viscosity (greater than 50 cp) using steam injection. Cyclic steam stimulation (CSS) is one of processes that commercially developed by numerous oil company to producing of heavy oil reservoir. The CSS can apply in vertical well or horizontal well. The research of CSS in horizontal well is still limited reported in the literature. On the other hand, the horizontal well has drainage area more wide compared with vertical well. In this study, solvent addition in cyclic steam stimulation will be tested with reservoir simulation. The steam was injected on the well, after that soaking time and the last was producing of liquid fluid reservoir. As the result, the oil production increases 3 times higher compared to without solvent. Furthermore, cumulative steam oil ratio (CSOR) and cumulative energy oil ratio (CEOS) decrease about 50% and 16%, respectively. In here, effect of solvent added in the steam, the steam distribution and drainage area wider.
Predicting Rate of Penetration and optimization Weight on bit using Artificial Neural Networks Tien Hung Nguyen
Journal of Earth Energy Engineering Vol. 11 No. 2 (2022)
Publisher : Universitas Islam Riau (UIR) Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jeee.2022.8170

Abstract

Obtaining the maximum Rate of Penetration (ROP) by optimization drilling parameters is the aim of every drilling engineer. This is because it could save time, reduce cost and minimize drilling problems. However, ROP depends on a lot of parameters which lead to difficulties in its prediction. Therefore, it is necessary and important to investigate a solution predicting ROP with high accuracy to determine the suitable drilling parameters. In this study, a new approach using Artificial Neural Network (ANN) has been proposed to predict ROP from real – time drilling data of several wells in Nam Rong - Doi Moi field with more than 900 datasets included important parameters such as the weight on bit (WOB), weight of mud (MW), rotary speed (RPM), standpipe pressure (SPP), flow rate (FR), torque (TQ). In the process of training the network, algorithms and the number of neurons in the hidden layer were varied to find the optimal model. The ANN model shows high accuracy when compared to actual ROP, therefore it can be recommended as an effective and suitable method to predict the ROP of other wells in the research area. Besides, base on the proposed ANN model, authors carried out experiments and determind the optimal weight on bit value for the drilling interval from 1800 to 2300 m of wells in Nam Rong Doi Moi field
Eco-Friendly Bridging Material: Experimental Characterization of Eggshells as an Affordable Natural Waste Non-Damaging Lost Circulation Material to Reduce Drilling Fluid Cost in Reservoir Drill-In-Fluid System Muhammad Rizqi Al Asy'ari; M Naufal Afifabyan; Riska Karimah
Journal of Earth Energy Engineering Vol. 11 No. 2 (2022)
Publisher : Universitas Islam Riau (UIR) Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jeee.2022.9158

Abstract

Lost circulation nowadays became one of the major problems in many drilling operations worldwide. This problem is complicated for it can significantly cause non-productive time during drilling operations. This research aims to study an eggshells as a LCM and to provide further insight about the reliability and cost analysis of eggshells as a potential drilling fluid additive. Moreover, the research successfully identified the usage of an abundant natural waste, i.e. eggshells, as an environmentally friendly fluid additive. This research also investigated the technical feasibility of the eggshells and also its economics impact on drilling operations. In addition, it is found that the eggshells can also act as a non-damaging LCM for production zone that is more affordable as compared to other natural waste loss circulation material and current commercially chemical. Series of laboratory tests were conducted such as mud balance for the density test, rheological test using viscometer Fann Vg, filtration loss test with filter press, and also alkalinity (pH) test. An excellent result from filtration loss test i.e. decreased fluid losses and showed great improvement almost same as commercially CaCO3 result in the filter cake thickness. The research proves great potential of the utilization of eggshells as a multi-purpose additive in a drilling fluid. Economic analysis also suggests that it can possibly be implemented and to be further developed for a large-scale field operations. Finally, it is found that using eggshells as LCM can reduce the cost up to 72.2 % cheaper than commercial CaCO3. It is also safe for drilling in the production zone (pay-zone) because of its solubility on acid that it can disappear during the acidizing job. If this paper can be implemented on a wide-range scale it will be very beneficial to reduce other commercial additives usage without losing its reliability.
Stuck Pipe Detection in Geothermal Operation with Support Vector Machine Sarwono Sarwono; Lukas; Maria Angela Kartawidjaja; Raka Sudira Wardana
Journal of Earth Energy Engineering Vol. 11 No. 2 (2022)
Publisher : Universitas Islam Riau (UIR) Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jeee.2022.9258

Abstract

One of the biggest problems during drilling operation is a stuck pipe in which the drill string would stick or freeze in the well. This challenge leads to a significant amount of remedial costs and time. Many researchers have investigated different factors regarding the stuck pipe. These factors include poor hole cleaning, improper mud design, key seating, balling up of bit, accumulation of cutting and caving, poor bottom hole assembly configuration, and differential pressure. Since geothermal drilling targets lost circulation zones at reservoir depth, the chance of getting stuck pipe events becomes higher. Many publications reported that lost circulation events that lead to stuck pipe events have become the top non-productive time (NPT) contributor to costs in many geothermal drilling projects. The consequences of a stuck pipe are very costly, that include lost time when releasing the pipe, time, and cost of fishing out the parted Bottom Hole Assembly (BHA), and efforts to abandon the tool(s) in the hole. Despite many observations that have been done to develop a system in avoiding stuck pipe incidents in oil and gas drilling operations using artificial intelligence (AI), few works have been developed for geothermal drilling operations. In this research, we propose a method to build an early warning system model for stuck pipe conditions based on a Support Vector Machine. Based on the experiment result Support Vector Machine Algorithm showed good performance with 89% accuracy and 81% recall for limited training dataset.

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