A New Solution to an Old Problem: Tractored CT Conveyed Real-Time Water Injection Profiling in Ultra Deep Wells

2013 ◽  
Author(s):  
James Arukhe ◽  
Saleh Al Ghamdi ◽  
Mubarak Dhufairi ◽  
Laurie Duthie ◽  
Karam Yateem ◽  
...  
Keyword(s):  
Real Time ◽  
Water Injection ◽  
Deep Wells

A New Solution to an Old Problem: Tractored CT Conveyed Real-Time Water Injection Profiling in Ultra Deep Wells

2013 ◽  
Author(s):  
James Arukhe ◽  
Saleh Al Ghamdi ◽  
Mubarak Dhufairi ◽  
Laurie Duthie ◽  
Karam Yateem ◽  
...  
Keyword(s):  
Real Time ◽  
Water Injection ◽  
Deep Wells

Maximizing Drilling Performance with Real-Time Drilling Vibration Mitigation in the Deep Wells

2016 ◽  
Author(s):  
M. Cui ◽  
G. H. Wang ◽  
H. Y. Ge ◽  
X. Z. Chen ◽  
H. W. Guo
Keyword(s):  
Real Time ◽  
Vibration Mitigation ◽  
Drilling Performance ◽  
Deep Wells

Real-Time Integrated LWD Formation Evaluation to Maximize Injectivity

2021 ◽  
Author(s):  
Idabagusgede Hermawanmanuab ◽  
Rayan Ghanim ◽  
Enrico Ferreira ◽  
Mohamed Gouda
Keyword(s):  
Real Time ◽  
Water Injection ◽  
Holistic Approach ◽  
Geological Structure ◽  
Target Zone ◽  
Horizontal Section ◽  
Well Placement ◽  
Formation Evaluation ◽  
Real Time Analysis ◽  
Resistivity Inversion

Abstract The main objective was to drill a power water horizontal injector within the sweet spot of a thin fractured and heterogeneous reservoir to achieve pressure stabilization in this producing field and an optimized sweep at the bottom of reservoir to maximize and prolong production. A traditional triple-combo logging while drilling (LWD) portfolio cannot fulfill these challenging reservoir navigation and formation evaluation (FE) objectives simultaneously because of the limited number of measurements. Hence, a more holistic approach is required to optimize the well placement via the integration of real-time LWD FE measurements to maximize the injectivity. An integrated LWD assembly was utilized and offset well FE data were studied to select the best zone for well placement to provide the best injectivity and production of the remaining oil towards the base of the reservoir. Extensive pre-well modeling was performed, based on offset well data with multiple scenarios reviewed to cover all eventualities. Another challenge was to place the wellbore in a relatively low resistive zone (water wet) in contrast to normal development wells where the wellbore is navigated in high resistive hydrocarbon bearing zones, so conventional distance to bed boundary mapping methodology was not applicable. To overcome this challenge; advanced Multi Component (MC) While Drilling resistivity inversion was proposed in conjunction with deep azimuthal resistivity technology. The benefit of this technique is in providing the resistivity of each layer within the depth of detection along with thickness and dip of each layer. Resistivity inversion results were correlated with nuclear magnetic resonance (NMR) porosity and volumetric data to identify the best zone for well placement. As MC inversion was able to map multiple layers within ~7 ft radius depth of detection, changing thicknesses and dip of each layer; the geosteering team was able to make proactive recommendations based on the inversion results. These proactive trajectory adjustments resulted in maintaining the wellbore within a thin target zone (1-3 ft in thickness) also confirmed by NMR and Formation Testing Service (FTS) in real-time, achieving excellent net-to-gross, which otherwise would not have been possible. The hexa-combo LWD assembly supported optimum well placement and provided valuable information about the geological structure through the analysis of high-resolution electrical images identifying the structural events which cause compartmentalization, confirmed by FTS results. This integrated LWD approach enabled proactive well trajectory adjustments to maintain the wellbore within the optimum porous, permeable and fractured target zone. This integrated methodology improved the contact within the water-injection target of the horizontal section, in a challenging thin reservoir and achieved 97.5 % exposure. Using an integrated LWD hexa-combo BHA and full real-time analysis the objective was achieved in one run with zero Non-Productive Time (NPT) and without any real-time or memory data quality issues.

Real-Time Water Injection Monitoring with Distributed Fiber Optics Using Physics-Informed Machine Learning

2021 ◽  
Author(s):  
Teymur Sadigov ◽  
Cagri Cerrahoglu ◽  
James Ramsay ◽  
Laurence Burchell ◽  
Sean Cavalero ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Resolution ◽  
Real Time ◽  
Fiber Optics ◽  
Water Injection ◽  
The Real ◽  
Start Up ◽  
Naturally Fractured ◽  
Monitoring Application ◽  
Time Injection

Abstract This paper introduces a novel technique that allows real-time injection monitoring with distributed fiber optics using physics-informed machine learning methods and presents results from Clair Ridge asset where a cloud-based, real-time application is deployed. Clair Ridge is a structural high comprising of naturally fractured Devonian to Carboniferous continental sandstones, with a significantly naturally fractured ridge area. The fractured nature of the reservoir lends itself to permanent deployment of Distributed Fiber Optic Sensing (DFOS) to enable real-time injection monitoring to maximise recovery from the field. In addition to their default limitations, such as providing a snapshot measurement and disturbing the natural well flow with up and down flowing passes, wireline-conveyed production logs (PL) are also unable to provide a high-resolution profile of the water injection along the reservoir due to the completion type. DFOS offers unique surveillance capability when permanently installed along the reservoir interface and continuously providing injection profiles with full visibility along the reservoir section without the need for an intervention. The real-time injection monitoring application uses both distributed acoustic and temperature sensing (DAS & DTS) and is based on physics-informed machine learning models. It is now running and available to all asset users on the cloud. So far, the application has generated high-resolution injection profiles over a dozen multi-rate injection periods automatically and the results are cross-checked against the profiles from the warmback analyses that were also generated automatically as part of the same application. The real-time monitoring insights have been effectively applied to provide significant business value using the capability for start-up optimization to manage and improve injection conformance, monitor fractured formations and caprock monitoring.

Recent Patents on Adjoint Method-based Real-time Dynamic Water Injection Optimization

2013 ◽  
Vol 6 (2) ◽  
pp. 145-152
Author(s):  
Pang Jin ◽  
Lei Guanglun ◽  
Liu Hong ◽  
Zhang Xu ◽  
Li Honglian
Keyword(s):  
Real Time ◽  
Adjoint Method ◽  
Water Injection ◽  
Time Dynamic

ADAM: An Accident Diagnostic, Analysis and Management System — Applications to Severe Accident Simulation and Management

2002 ◽  
Author(s):  
M. J. Zavisca ◽  
M. Khatib-Rahbar ◽  
H. Esmaili ◽  
R. Schulz
Keyword(s):  
Real Time ◽  
Water Injection ◽  
Management Training ◽  
Computer Applications ◽  
Severe Accident ◽  
Diagnostic Analysis ◽  
Gas Generation ◽  
Accident Management ◽  
Accident Simulation ◽  
On Line

The Accident Diagnostic, Analysis and Management (ADAM) computer code has been developed as a tool for on-line applications to accident diagnostics, simulation, management and training. ADAM’s severe accident simulation capabilities incorporate a balance of mechanistic, phenomenologically based models with simple parametric approaches for elements including (but not limited to) thermal hydraulics; heat transfer; fuel heatup, meltdown, and relocation; fission product release and transport; combustible gas generation and combustion; and core-concrete interaction. The overall model is defined by a relatively coarse spatial nodalization of the reactor coolant and containment systems and is advanced explicitly in time. The result is to enable much faster than real time (i.e., 100 to 1000 times faster than real time on a personal computer) applications to on-line investigations and/or accident management training. Other features of the simulation module include provision for activation of water injection, including the Engineered Safety Features, as well as other mechanisms for the assessment of accident management and recovery strategies and the evaluation of PSA success criteria. The accident diagnostics module of ADAM uses on-line access to selected plant parameters (as measured by plant sensors) to compute the thermodynamic state of the plant, and to predict various margins to safety (e.g., times to pressure vessel saturation and steam generator dryout). Rule-based logic is employed to classify the measured data as belonging to one of a number of likely scenarios based on symptoms, and a number of “alarms” are generated to signal the state of the reactor and containment. This paper will address the features and limitations of ADAM with particular focus on accident simulation and management.

Operator Develops Fully Smart Onshore Field

2021 ◽  
Vol 73 (05) ◽  
pp. 56-57
Author(s):  
Judy Feder
Keyword(s):  
Real Time ◽  
United Arab Emirates ◽  
Oil And Gas ◽  
Water Injection ◽  
Health And Safety ◽  
Oil And Gas Industry ◽  
Oil Fields ◽  
Abu Dhabi ◽  
Time Data ◽  
Gas Industry

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 203461, “Digitalization in the Oil and Gas Industry—A Case Study of a Fully Smart Field in the United Arab Emirates,” by Muhammad Arif and Abdulla Mohammed Al Senani, ADNOC, prepared for the 2020 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, held virtually from 9–12 November. The paper has not been peer reviewed. One of the first oil fields in the UAE to be fully operated remotely is in the southeast region, 250 km from Abu Dhabi. The complete paper discusses the development and commissioning of the field, which is the first smart field for ADNOC Onshore. The designed and applied technology facilitated unmanned operation of the field from downhole to export. Introduction Oilfield digitalization encompasses gathering real-time and non-real-time data from wells, flow lines, manifolds, stations, and water injection facilities; analysis of the data using algorithms, flowcharts, plots, and reports; and user access to this data on user-friendly screens. This allows engineers to focus on interpretation of data vs. searching, organizing, and formatting the data. In the bigger picture, the data collected will lead to conclusions and set bases for important decisions for similar projects in the future, enabling a lesson-learning approach to design new oil fields. The accumulated theoretical and practical research results of smart-field implementation require analysis and synthesis to maintain perspective of the entire project. Both were applied in the Mender field, which is the subject of the complete paper. Problem Statement The Mender parent field has been producing since 2013 with minimal digitalization for wellheads. Wells are not fit-ted with remote sensors, and operators have been visiting the wells to collect data using analog gauges. Collected data are stored in computers or as hard copies. Some critical data is lost, which affects decision-making. The new Mender field is 50 km from the parent field and is in a sensitive area close to international borders. The field area is a wildlife reserve for various endangered animals. The nature of operations is highly critical because of concentrations of hydrogen sulfide (H2S) that could jeopardize employees’ health and safety.

Process Design of Cyclic Water Flooding by Real-Time Monitoring

2018 ◽  
Vol 140 (11) ◽  
Author(s):  
Kobra Pourabdollah
Keyword(s):  
Real Time ◽  
Production Rate ◽  
Process Design ◽  
Water Injection ◽  
Oil Production ◽  
Oil Field ◽  
Water Flooding ◽  
Injection System ◽  
Real Time Monitoring ◽  
Naturally Fractured

The gradual decline in the oil production rate of water flooded reservoirs leads to decrease in the profit of water flooding system. Although cyclic water injection (CWI) was introduced to reduce the descending trend of oil production in water flooded reservoirs, it must be optimized based upon the process parameters. The objective of this study is to develop all process design criteria based upon the real-time monitoring of CWI process in a naturally fractured reservoir having five producing wells and five injector wells completed in an Arab carbonated formation containing light crude oil (API = 42 deg). For this aim, a small pilot oil field was selected with water injection facilities and naturally producing oil wells and all data were collected from the field tests. During a five years' field test, the primary observations at the onset of shutdown periods of the water injection system revealed a repeatable significant enhancement in oil production rate by a factor of plus 5% leading us to assess the application of CWI. This paper represents the significant parameters of pressure and productivity affected during CWI in naturally fractured carbonate reservoirs based upon a dual porosity generalized compositional model. The results hopefully introduce other oil producer companies to the potential of using CWI to increase oil production in conventional water injection systems. The results also outline situations where such applications would be desirable.

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