Idle Wells Revival Guidance to Optimize Remaining Gas in Shallow zone of Tunu field, Mahakam: Taking Advantage from Reservoir Re-Equilibrium

2020 ◽  
Author(s):  
A. S. Ashfahani
Keyword(s):  
Best Practice ◽  
Static Condition ◽  
Automatic Monitoring ◽  
Global Strategy ◽  
Candidate Selection ◽  
Driving Mechanism ◽  
Gas Field ◽  
Shallow Zone ◽  
Production Target ◽  
Field Production

Shallow Zone reservoir of Tunu Field (TSZ) which was initially identified as drilling hazards, has now been extensively developed since 2009 with more than 600 Bscf of cumulative gas. The zone consists of widespread and scattered gas-bearing sand reservoirs, with strong aquifer drive mechanism. Today, more than 280 development wells have been drilled, and as the field is aging up, there are more than 62% wells have been died or idle. As an impact from driving mechanism, most of idle wells are related to water influx from reservoir to wellbore. These wells have been studied and revival program is performed by considering the strong aquifer support and reservoir re-equilibrium process in the reservoir. Based on trial phase that have been conducted, global strategy to revive the dead well have been developed, in order to optimize remaining reserves and also to support field production target. To implement this initiative, several supporting items were prepared: well candidate selection workflow, static condition requirement by dynamic well simulation, automatic monitoring tool for well candidate selection based on static condition requirement, campaign categories, job preparation (i.e. dedicated deltaic swamp testing barge), and regular monitoring & evaluation. Continuous implementation from this initiative has given additional production gain and recovered volume significantly to support field production target. Guidance from this best practice could give an initiative idea for other gas field with typical characteristics for optimizing each standard cubic feet of gas volume from existing idle wells.

DEEPWATER GAS FIELD PRODUCTION FROM SUBSEA WELLS INTO COMPRESSED NATURAL GAS CARRIERS THROUGH A HYBRID RISER TOWER

2005 ◽  
Vol 45 (1) ◽  
pp. 45
Author(s):  
J-F. Saint-Marcoux ◽  
C. White ◽  
G.O. Hovde
Keyword(s):  
Natural Gas ◽  
Eddy Currents ◽  
Gas Production ◽  
Lessons Learned ◽  
Concept Design ◽  
Vertical Load ◽  
Gas Field ◽  
Compressed Natural Gas ◽  
Field Development ◽  
Field Production

This paper addresses the feasibility of developing an ultra-deepwater gas field by producing directly from subsea wells into Compressed Natural Gas (CNG) Carrier ships. Production interruptions will be avoided as two Gas Production Storage Shuttle (GPSS) vessels storing CNG switch out roles between producing/storing via one of two Submerged Turret Production (STP) buoys and transport CNG to a remote offloading buoy. This paper considers the challenges associated with a CNG solution for an ultra-deepwater field development and the specific issues related to the risers. A Hybrid Riser Tower (HRT) concept design incorporating the lessons learned from the Girassol experience allows minimisation of the vertical load on the STP buoys. The production switchover system from one GPSS to the other is located at the top of the HRT. High-pressure flexible flowlines with buoyancy connect the flow path at the top of HRT to both STP buoys. System fabrication and installation issues, as well as specific met ocean conditions of the GOM, such as eddy currents, have been addressed. The HRT concept can be also used for tiebacks to floating LNG plants.

scholarly journals Security standard compliance and continuous verification for Industrial Internet of Things

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772092273 ◽  
Author(s):  
Ani Bicaku ◽  
Markus Tauber ◽  
Jerker Delsing
Keyword(s):  
Internet Of Things ◽  
Best Practice ◽  
Automatic Monitoring ◽  
Industrial Internet Of Things ◽  
Industrial Systems ◽  
Best Practice Guidelines ◽  
Industrial Internet ◽  
Security Standard ◽  
Compliance Verification ◽  
Security Compliance

Due to globalization and digitalization of industrial systems, standard compliance is gaining more attention. In order to stay competitive and remain in business, different sectors within industry are required to comply with multiple regulations. Compliance aims to fulfill regulations by including all measures imposed by laws and standards. Every device, application, or service implements several technologies at many levels, and standards support interoperability across them. They help to create global markets for industries and enable networked development in order to be successful and sustainable. This work highlights the importance of standard compliance and continuous verification in industrial Internet of Things and implements an automatic monitoring and standard compliance verification framework. In this work, we focus on security, safety, and organizational aspects of industrial Internet of Things. We identify a number of standards and best practice guidelines, which are used to extract security, safety, and organizational measurable indicator points. In addition, a metric model is provided that forms the basis for the necessary information needed for compliance verification, including requirements, standards, and metrics. Also, we present the prototype of the monitoring and standard compliance verification framework used to show the security compliance of an industrial Internet of Things use case.

scholarly journals Technological progress and development directions of PetroChina overseas oil and gas field production

2020 ◽  
Vol 47 (1) ◽  
pp. 124-133 ◽  
Author(s):  
Longxin MU ◽  
Yaqiang CHEN ◽  
Anzhu XU ◽  
Ruifeng WANG
Keyword(s):  
Technological Progress ◽  
Oil And Gas ◽  
Gas Field ◽  
Oil And Gas Field ◽  
Field Production

best practice well candidate selection for workover

2018 ◽  
Author(s):  
Kelik Rudi Suharya
Keyword(s):  
Best Practice ◽  
Candidate Selection ◽  
Selection For

Machine Learning Technology to Improve Precision and Accelerate Screening Shallow Gas Potentials in Tunu Shallow Gas Zone, PT Pertamina Hulu Mahakam

2021 ◽  
Author(s):  
R. Herbet
Keyword(s):  
Machine Learning ◽  
Learning Technology ◽  
Gas Reservoirs ◽  
Shallow Gas ◽  
Gas Field ◽  
East Kalimantan ◽  
Main Challenge ◽  
Shallow Zone ◽  
Learning Probability ◽  
Mahakam Delta

Tunu is a giant gas field located in the present-day Mahakam Delta, East Kalimantan, Indonesia. Tunu gas produced from Tunu Main Zone (TMZ), between 2500-4500 m TVDSS and Tunu Shallow Zone (TSZ) located on depth 600 - 1500 m TVDSS. Gas reservoirs are scattered along the Tunu Field and corresponds with fluio-deltaic series. Main lithologies are shale, sand, and coal layers. Shallow gas trapping system is a combination of stratigraphic features, and geological structures. The TSZ development relies heavily on the use seismic to assess and identify gas sand reservoirs as drilling targets. The main challenge for conventional use of seismic is differentiating the gas sands from the coal layers. Gas sands are identified by an established seismic workflow that comprises of four different analysis on pre-stack and angle stacks, CDP gathers, amplitude versus angle(AVA), and inversion/litho-seismic cube. This workflow has a high success rate in identifying gas, but requires a lot of time to assess the prospect. The challenge is to assess more than 20,000 shallow objects in TSZ, it is important to have a faster and more efficient workflow to speed up the development phase. The aim of this study is to evaluate the robustness of machine learning to quantify seismic objects/geobodies to be gas reservoirs. We tested various machine learning methods to fit learn geological Tunu characteristic to the seismic data. The training result shows that a gas sand geobody can be predicted using combination of AVA gather, sub-stacks and seismic attributes with model precision of 80%. Two blind wells tests showed precision more than 95% while other final set tests are under evaluated. Detectability here is the ability of machine learning to predicted the actual gas reservoir as compared to the number of gas reservoirs found in that particular wells test. Outcome from this study is expected to accelerate gas assessment workflow in the near future using the machine learning probability cube, with more optimized and quantitative workflow by showing its predictive value in each anomaly.

An Automatic Gas-Flow Control System Adaptable to Gas Field Production

1964 ◽  
Vol 16 (03) ◽  
pp. 253-258
Author(s):  
J.C. Anderson ◽  
L.M. McMillon
Keyword(s):  
Control System ◽  
Flow Control ◽  
Gas Flow ◽  
Gas Field ◽  
Flow Control System ◽  
Field Production

scholarly journals Application of MES System in Offshore Oil and Gas Field Production Management

2019 ◽  
Vol 1 (2) ◽  
pp. 47-54
Author(s):  
Yong Chen ◽  
Weihua Lan ◽  
Chong Wang
Keyword(s):  
Production Management ◽  
Oil And Gas ◽  
Gas Field ◽  
Oil And Gas Field ◽  
Mes System ◽  
Offshore Oil And Gas ◽  
Offshore Oil ◽  
Field Production

Unlocking Surface Constraints for High Temperature Gas Field: Production Network Compositional Variation Analysis for Wet Gas Meter PVT Calibration Approach

2021 ◽  
Author(s):  
Shaturrvetan Karpaya ◽  
Sulaiman Sidek ◽  
Dani Angga Ab Ghani ◽  
Hazrina Ab Rahman ◽  
Aivin Yong ◽  
...  
Keyword(s):  
High Temperature ◽  
Gas Condensate ◽  
Production Network ◽  
Total Field ◽  
Production Rates ◽  
Gas Field ◽  
Wet Gas ◽  
Tracer Dilution ◽  
Gas Ratio ◽  
Field Production

Abstract Installation of Wet Gas Metering System (WGMS) on a platform for the purposes of real-time measurement of liquid and gas production rates as well as performance monitoring as part of reservoir and production optimization management are quite common nowadays in Malaysia. Nonetheless, understanding of wells production deliverability invariably measured using these Wet Gas Meter (WGM) which provides the notion of production rates contributed by the wells are paramount important, eventually the produced fluids will be processed by various surface equipment at the central processing platform before being transport to onshore facilities. However, the traditional WGM are known to operate within ±10% accuracy, whereby the confidence level on measurement of the produced fluids can be improved either by updating with accurate PVT flash table or combination of results from performing tracer dilution technique for data verification. Sarawak Gas Field contains a number of gas fields offshore East Malaysia, predominantly are carbonate type formation, where one (1) of the field operated by PETRONAS Carigali Sdn.Bhd.(PCSB) is a high temperature accumulation at which temperature at the Gas Water Contact (GWC) approximately 185°C and full wellstream Flowing Tubing Head Temperature (FTHT) records at 157°C. Cumulative field production of five (5) wells readings from WGM had shown 9.1% differences as compared to the export meter gas readings. As part of a strategy to provide maximum operational flexibility, improvement on accuracy of the WGM is required given that the wells have higher Technical Potential (TP) but are limited by threshold of the multi-stage surface processing capacity. This also impacts commerciality of the field to regaining the cost of capital investment and generate additional revenue especially when there is a surge in network gas demand, as the field unable to swiftly ramp-up its production to fulfill higher gas demand considering the reported production figures from cumulative WGM surpassing the surface equipment Safe Operating Envelope (SOE). Our approach begins with mass balance check at the WGMS and export meter including the fuel, flare and Produced Water Discharge (PWD) to check mass conservation by phases because regardless different type of phases change occurs at topside the total mass should be conserved (i.e. for total phases of gas, condensate and water) provided that precise measurement by the metering equipment. Tracer dilution measurement of gas, condensate and water flowrates were used to verify the latest calibrated Water Gas Ratio (WGR) and Condensate Gas Ratio (CGR) readings input into the WGM. Consequently, PVT separator samples were also taken via mini-separator for compositional analysis (both gas and condensate) and for mathematical recombination at the multi-rates CGR readings to generate a representative PVT compositional table. Simultaneously, process model simulation run was conducted using full wellstream PVT input to validate total field production at the export point. This paper presents practical approach to balance the account, to ensure the SOE at topside as well as to improve the PVT composition at the WGM for high temperature field that emphasizes on understanding of compositional variations across production network causing significant differences in total field production between WGM and the allocation meter.

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