Bringing Flexibility and Automation to Well Testing Operations Through Wireless Telemetry - Case Study

Abstract Dynamic reservoir data are a key driver for operators to meet the forecasted production investments of their fields. However, many challenges during well testing, such as reduced exploration and capex budgets, complex geologic structures, and inclement weather conditions that reduce the well testing time window can prevent them from gathering critical reservoir characterization data needed to make more informed field development planning decisions. To overcome these challenges, a live, downhole reservoir testing platform enabled the most representative reservoir information in real time and connected more zones of interest in a single run for appraisal wells in the Sea of Okhotsk, Russia. This paper describes the test requirements, the prejob planning, and automated execution of wirelessly enabled operations that led to the successful completion of the well test campaign in very hostile conditions, a remote area, and restricted period. The use of a telemetry system to well testing in seven zones enabled real-time control of critical downhole equipment and acquired data at surface, which in turn was transmitted to the operator's office in town in real time. Various operation examples will be discussed to demonstrate how automated data acquisition and downhole operations control has been used to optimize operations by both the service company and the operator.

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Fully Automated and Wirelessly Enabled Drillstem Tests: Seven-Zones Campaign Case Study in Sakhalin

10.2118/204401-ms ◽

2021 ◽

Author(s):

Elias Temer ◽

Deiveindran Subramaniam

Keyword(s):

Data Acquisition ◽

Real Time ◽

Time Window ◽

Weather Conditions ◽

Testing Time ◽

Well Testing ◽

Well Test ◽

Time Data ◽

Operations Control ◽

Bad Weather

Abstract Well test is one of the crucial steps required to forecast production investments of their fields. However, the operators face many challenges such as reduced capex, exploration budgets, and bad weather conditions that limit the well testing time window. To overcome these challenges, an automated well testing platform enabled a real time monitoring and controlling more zones in a single run for appraisal wells in the Sea of Okhotsk, Russia. This article highlights the test objectives, the job planning, and automated execution of wirelessly enabled operations in very hostile conditions and limited time period. The use of a telemetry system to well test seven zones allowed real-time data acquisition, control of critical downhole equipment, data transmission to the operator's office in town. Various operational cases will be discussed to demonstrate how automated data acquisition and downhole operations control has optimized operations for both the service company and the operator.

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A Back Allocation Methodology to Estimate the Real-Time Flow and Assist Production Monitoring

10.2118/205916-ms ◽

2021 ◽

Author(s):

Gabriela Chaves ◽

Danielle Monteiro ◽

Virgilio José Martins Ferreira

Keyword(s):

Real Time ◽

Input Data ◽

Oil Field ◽

Well Testing ◽

Well Test ◽

Time Data ◽

Time Flow ◽

Well Model ◽

Operational Information ◽

The Individual

Abstract Commingle production nodes are standard practice in the industry to combine multiple segments into one. This practice is adopted at the subsurface or surface to reduce costs, elements (e.g. pipes), and space. However, it leads to one problem: determine the rates of the single elements. This problem is recurrently solved in the platform scenario using the back allocation approach, where the total platform flowrate is used to obtain the individual wells’ flowrates. The wells’ flowrates are crucial to monitor, manage and make operational decisions in order to optimize field production. This work combined outflow (well and flowline) simulation, reservoir inflow, algorithms, and an optimization problem to calculate the wells’ flowrates and give a status about the current well state. Wells stated as unsuited indicates either the input data, the well model, or the well is behaving not as expected. The well status is valuable operational information that can be interpreted, for instance, to indicate the need for a new well testing, or as reliability rate for simulations run. The well flowrates are calculated considering three scenarios the probable, minimum and maximum. Real-time data is used as input data and production well test is used to tune and update well model and parameters routinely. The methodology was applied using a representative offshore oil field with 14 producing wells for two-years production time. The back allocation methodology showed robustness in all cases, labeling the wells properly, calculating the flowrates, and honoring the platform flowrate.

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A Novel Well Test Data Analyzer and Process Optimizer Using Artificial Intelligence and Machine Learning Techniques

10.2118/206137-ms ◽

2021 ◽

Author(s):

Nagaraju Reddicharla ◽

Subba Ramarao Rachapudi ◽

Indra Utama ◽

Furqan Ahmed Khan ◽

Prabhker Reddy Vanam ◽

...

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Real Time ◽

Test Data ◽

Oil Field ◽

Well Testing ◽

Well Test ◽

Time Data ◽

Real Time Data ◽

Well Tests

Abstract Well testing is one of the vital process as part of reservoir performance monitoring. As field matures with increase in number of well stock, testing becomes tedious job in terms of resources (MPFM and test separators) and this affect the production quota delivery. In addition, the test data validation and approval follow a business process that needs up to 10 days before to accept or reject the well tests. The volume of well tests conducted were almost 10,000 and out of them around 10 To 15 % of tests were rejected statistically per year. The objective of the paper is to develop a methodology to reduce well test rejections and timely raising the flag for operator intervention to recommence the well test. This case study was applied in a mature field, which is producing for 40 years that has good volume of historical well test data is available. This paper discusses the development of a data driven Well test data analyzer and Optimizer supported by artificial intelligence (AI) for wells being tested using MPFM in two staged approach. The motivating idea is to ingest historical, real-time data, well model performance curve and prescribe the quality of the well test data to provide flag to operator on real time. The ML prediction results helps testing operations and can reduce the test acceptance turnaround timing drastically from 10 days to hours. In Second layer, an unsupervised model with historical data is helping to identify the parameters that affecting for rejection of the well test example duration of testing, choke size, GOR etc. The outcome from the modeling will be incorporated in updating the well test procedure and testing Philosophy. This approach is being under evaluation stage in one of the asset in ADNOC Onshore. The results are expected to be reducing the well test rejection by at least 5 % that further optimize the resources required and improve the back allocation process. Furthermore, real time flagging of the test Quality will help in reduction of validation cycle from 10 days hours to improve the well testing cycle process. This methodology improves integrated reservoir management compliance of well testing requirements in asset where resources are limited. This methodology is envisioned to be integrated with full field digital oil field Implementation. This is a novel approach to apply machine learning and artificial intelligence application to well testing. It maximizes the utilization of real-time data for creating advisory system that improve test data quality monitoring and timely decision-making to reduce the well test rejection.

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Energy optimization of the urban drainage system by integrated real-time control during wet and dry weather conditions

Urban Water Journal ◽

10.1080/1573062x.2018.1480726 ◽

2018 ◽

Vol 15 (4) ◽

pp. 362-370 ◽

Cited By ~ 5

Author(s):

Stefan Kroll ◽

Alessio Fenu ◽

Tom Wambecq ◽

Marjoleine Weemaes ◽

Jan Van Impe ◽

...

Keyword(s):

Real Time ◽

Energy Optimization ◽

Drainage System ◽

Weather Conditions ◽

Urban Drainage ◽

Real Time Control ◽

Urban Drainage System ◽

Time Control

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Pressure and pressure derivative analysis for non-newtonian pseudoplastic fluids in double-porosity formations

CT&F - Ciencia Tecnología y Futuro ◽

10.29047/01225383.238 ◽

2011 ◽

Vol 4 (3) ◽

pp. 47-60 ◽

Cited By ~ 4

Author(s):

Freddy-Humberto Escobar ◽

Angela-Patricia Zambrano ◽

Diana-Vanessa Giraldo ◽

José-Humberto Cantillo

Keyword(s):

Oil Recovery ◽

Reservoir Characterization ◽

Numerical Models ◽

Simulated Data ◽

Newtonian Fluids ◽

Well Testing ◽

Well Test ◽

Well Test Analysis ◽

Pressure Derivative ◽

Derivative Analysis

Non-Newtonian fluids are often used during various drilling, workover and enhanced oil recovery processes. Most of the fracturing fluids injected into reservoir-bearing formations possess non-Newtonian nature and these fluids are often approximated by Newtonian fluid flow models. In the field of well testing, several analytical and numerical models taking into account Bingham, pseudoplastic and dilatant non-Newtonian behavior have been introduced in the literature to study their transient nature in porous media for a better reservoir characterization. Most of them deal with fracture wells and homogeneous formations and well test interpretation is conducted via the straight-line conventional analysis or type-curve matching. Only a few studies consider the pressure derivative analysis. However, there exists a need of a more practical and accurate way of characterizing such systems. So far, it does not exist any methodology to characterize heterogeneous formation bearing non-Newtonian fluids through of well test analysis. In this study, an interpretation methodology using the pressure and pressure derivative log-log plot is presented for non-Newtonian fluids in naturally fractured formations, so the dimensionless fracture storativity ratio, ω, and interporosity flow parameter, λ, are obtained from characteristics points found on such plot. The developed equations and correlations are successfully verified by their application only to synthetic well test data since no actual field data are available. A good match is found between the results provided by the proposed technique and the values used to generate the simulated data.

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World's First Extension Pack with 7-in. Enhanced Single-Trip Multizone System: Success Case and Learning Points on the Installation and Treatment Design

10.2523/iptc-21783-ms ◽

2021 ◽

Author(s):

Sunanda Magna Bela ◽

Abdil Adzeem B Ahmad Mahdzan ◽

Noor Hidayah A Rashid ◽

Zairi A Kadir ◽

Azfar Israa Abu Bakar ◽

...

Keyword(s):

Reservoir Characterization ◽

Development Planning ◽

Development Project ◽

Lessons Learned ◽

High Rate ◽

Individual Treatment ◽

Flow Area ◽

Field Development ◽

Well Completion ◽

Gravel Pack

Abstract Gravel packing in a multilayer reservoir during an infill development project requires treating each zone individually, one after the other, based on reservoir characterization. This paper discusses the installation of an enhanced 7-in. multizone system to achieve both technical and operational efficiency, and the lessons learned that enabled placement of an optimized high-rate water pack (HRWP) in the two lower zones and an extension pack in the uppermost zone. This new approach helps make multizone cased-hole gravel-pack (CHGP) completions a more technically viable and cost-effective solution. Conventional CHGPs are limited to either stack-pack completions, which can incur high cost because of the considerable rig time required for multizone operations, or alternate-path single-trip multizone completions that treat all the target zones simultaneously, with one pumping operation. However, this method does not allow for individual treatment to suit reservoir characterization. The enhanced 7-in. multizone system can significantly reduce well completion costs and pinpoint the gravel placement technique for each zone, without pump-rate limitations caused by excessive friction in the long interval system, and without any fiuid-loss issues after installation because of the modular sliding side-door (SSD) screen design feature. A sump packer run on wireline acts as a bottom isolation packer and as a depth reference for subsequent tubing-conveyed perforating (TCP) and wellbore cleanup (WBCU) operations. All three zones were covered by 12-gauge wire-wrapped modular screens furnished with blank pipe, packer extension, and straddled by two multizone isolation packers between the zones, with a retrievable sealbore gravel-pack packer at the top. The entire assembly was run in a single trip, therefore rig time optimization was achieved. The two lower zones were treated with HRWPs, while the top zone was treated with an extension pack. During circulation testing on the lowermost zone, high pumping pressure was recorded, and after thorough observation of both pumping parameters and tool configuration, it was determined that the reduced inner diameter (ID) in the shifter might have been a causal factor, thereby restricting the flow area. This was later addressed with the implementation of a perforated pup joint placed above the MKP shifting tool. The well was completed within the planned budget and time and successfully put on sand-free production, exceeding the field development planning (FDP) target. The enhanced 7-in. multizone system enabled the project team to beat the previous worldwide track record, which was an HRWP treatment only. As a result of proper fluid selection and rigorous laboratory testing, linear gel was used to transport 3 ppa of slurry at 10 bbl/min, resulting in a world-first extension pack with a 317-lbm/ft packing factor.

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Advanced Gas While Drilling GWD Comparison with Pressure Volume Temperature PVT Analysis to Obtain Information About the Reservoir Fluid Composition, a Case Study from East Kuwait Jurassic Reservoir

10.2118/206296-ms ◽

2021 ◽

Author(s):

Mohammad J. Ahsan ◽

Shaikha Al-Turkey ◽

Nitin M. Rane ◽

Fatemah A. Snasiri ◽

Ahmed Moustafa ◽

...

Keyword(s):

Real Time ◽

Oil And Gas ◽

Compositional Analysis ◽

Fluid Composition ◽

Well Test ◽

Drilling Mud ◽

Strong Base ◽

Field Development ◽

Gas Drilling ◽

Reservoir Fluid

Abstract Objectives/Scope The acquisition of mud gas data for well control and gathering of geological information is a common practice in oil and gas drilling. However, these data are scarcely used for reservoir evaluation as they are presumably considered as unreliable and non-representative of the formation content. Recent development in gas extraction from drilling mud and analyzing equipment has greatly improved the data quality. Combined with proper analysis and interpretation, these new datasets give valuable information in real-time lithological changes, hydrocarbons content, water contacts and vertical changes in fluid over a pay interval. Methods, Procedures, Process Post completion, Mud logging data have been compared with PVT results and they have shown excellent correlation on the C1-C5 composition, confirming the consistency between gas readings and reservoir fluid composition. Having such information in real time has given the oil company the opportunity to optimize its operations regarding formation evaluation, e.g downhole sampling, wireline logging or testing programs. Formation fluid is usually obtained during well tests, either by running downhole tools into the well or by collecting the fluid at surface. Therefore, its composition remains unknown until the arrival of the PVT well test results. This case intends to use mud gas information collected while drilling to predict information about the reservoir fluid composition in near real time. To achieve this goal we compared mud gas data collected while drilling with reservoir fluid compositional results. Pressure volume temperature (PVT) analysis is the process of determining the fluid behaviors and properties of oil and gas samples from existing wells. Results, Observations, Conclusions The reason any oil and gas company decides to drill a well is to turn the project into an oil-producing asset. But the value of the oil extracted from a single well is not the same as the value of the oil produced from another. The makeup of the oil, which can be determined from the compositional analysis, is an important piece of the equation that determines how profitable the play will be. The compositional analysis will determine just how much of each type of petroleum product can be produced from a single barrel of oil from that wells. Novel/Additive information Formation samples were obtained from offset wells in the Marrat Formation. These datasets gave valuable indications on fluid properties and phase behavior in the reservoir and provided strong base for reservoir engineering analysis, simulation and surface facilities design. The comparison of the gas data to PVT results gives a good match for reservoir fluid finger print, early acquisition of this data will help for decision enhancement for field development.

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Control of a Prosthetic Arm Using fNIRS, a Neural-Machine Interface

10.5772/intechopen.93565 ◽

2020 ◽

Author(s):

Usama Ali Syed ◽

Zareena Kausar ◽

Neelum Yousaf Sattar

Keyword(s):

Real Time ◽

Near Infrared ◽

Time Window ◽

Time Signal ◽

Real Time Control ◽

Functional Near Infrared Spectroscopy ◽

Prosthetic Devices ◽

Linear Discriminant ◽

Time Control ◽

Artificial Neural Network Ann

Development in the field of bio-mechatronics has provided diverse ways to mimic and improve the function of human limbs. Without an elbow joint, the hand remains stiff because all the muscles tension passes through this joint. Advanced myoelectric prosthetic devices are limited due to the lack of appropriate signal sources on residual amputee muscles and insufficient real-time control. Neural-machine interfaces (NMI) are representing a recent approach to develop effective applications. In this research study, an NMI is designed that presents real-time signal processing for command generation. The human brain hemodynamic responses are, therefore, translated into control commands for people suffering from transhumeral amputation. A novel and first of its kind scheme is proposed which utilizes functional near-infrared spectroscopy (fNIRS) to generate the control commands for a three-degree-of-freedom (DOF) prosthetic arm. The time window for fNIRS signals was set to 1 second. The average accuracy was found to be 82% which is a state-of-the-art result for such a technique. The accuracy ranged from 65 to 85% subject-wise. The data were trained and tested on both artificial neural network (ANN) and linear discriminant analysis (LDA). Eight out of 10 motions were correctly predicted in real time by both classifiers.

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Insights into Khuff Oil Rim Development in Sultanate of Oman from Extensive Drilling and Well Testing Operations

10.2118/208139-ms ◽

2021 ◽

Author(s):

Tingting Zhang ◽

Arun Kumar ◽

Rashid Al Maskari ◽

Maryam Musalami ◽

Sumaiya Habsi

Keyword(s):

Management Plan ◽

Productivity Index ◽

Well Testing ◽

Flow Profile ◽

Well Test ◽

Sultanate Of Oman ◽

Full Field ◽

Associated Gas ◽

Field Development ◽

Rock Types

Abstract The Yibal Khuff project is a mixed oil-rims, associated gas, and non-associated gas development in highly fractured tight carbonate reservoirs. Rock types and fractures vary widely with significant contribution to flow. In the east segment of the field, 22 horizontal oil producers targeting K2 reservoir have been pre-drilled and tested extensively. The integration of well logs, borehole image data (BHI), well test data and production logs provide key insights into reservoir productivity and the development of a robust well and reservoir management plan, ready for start-up of the field in 2021. A log-based approach was used to classify the reservoir into three main rock types (RRT). Fractures were classified, and high impact fractures were identified. Reservoir flow profile based on noise and temperature logs was established and used in combination with fracture data and cement bond logs in understanding flow conformance and behind casing flow. A large variation in productivity index has been observed, from tight to highly productive wells. Different ways have been explored to establish the link between productivity index, fracture production, and matrix production by rock types. This is the first full field development in the Khuff formation in Sultanate of Oman. The results will benefit a wider audience. A holistic approach was taken to explore the link between well deliverability and nature of a complex geology. The outcome is a robust operating envelope and well, reservoir and facilities management (WRFM) plan, clearly driven by understanding of subsurface risk and opportunities.

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The Selection and Optimum Well Testing Practices to Achieve Zero Flaring & Venting in Malaysian Water for a Petronas Field Development

10.2118/207618-ms ◽

2021 ◽

Author(s):

Adhi Naharindra ◽

Zalina Ali ◽

Nik Fazril Ain Sapi’an ◽

Latief Riyanto ◽

Fuziana Tusimin ◽

...

Keyword(s):

Environmental Impact ◽

Oil And Gas ◽

Oil Field ◽

Testing System ◽

Well Testing ◽

Well Test ◽

Flow Lines ◽

Field Development ◽

Well Completion ◽

Production Facilities

Abstract Increased HSE concerns and global economic efficiency from well testing activities especially on its environmental impact have left several oil and gas industries’ facing critical challenges to develop and monetize oil reserves. Some of these challenges include handling well effluents from well test unloading operations after well completion with high contaminants such as H2S and CO2 which will exacerbate environmental impact to safety, pollution, and oil spill risks. In addition, mitigation to environmental impact will be constrained to limited deck space and topside loads for offshore wellhead facilities and eventually restricts the footprint of well test unloading equipment. The scope of the paper is to examine the evolution of well deliverability testing from conventional well test facilities’ flaring practices to contemporary smokeless and zero flaring operations applied in a giant sand stones oil field in Malaysian water, which is surrounded by a world class environmentally protected marine and coastal ecosystem. The zero-flaring approach allows a demonstration of the safety & emission reduction, cost saving, technical viability, and economic benefits over traditional flaring techniques for 20 to 30 well testing during the life of field. Previous wells clean up method require flaring of oil and gas before the production facilities and flow lines were operational.commissioned. The application of environment friendly well testing system using the completed flow lines and production facilities enable zero-flaring option to be technically and economically viable. Zero-flaring well testing system provides several attractive benefits, with potential reduction in flaring equivalent of ±1000 barrels of oil, pollution avoidance, 40 - 50% schedule reduction and over 40% reduction in total project costs for the field development..

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