The Liza Field: From Discovery to Development

2021 ◽  
Author(s):  
Nicholas Austin ◽  
Mita Das ◽  
Adedayo Oyerinde ◽  
Elizabeth Elkington
Keyword(s):  
Comprehensive Evaluation ◽  
Investment Decision ◽  
Phase 1 ◽  
Dynamic Performance ◽  
Full Range ◽  
Seismic Survey ◽  
Lower Probability ◽  
Calibration Data ◽  
Well Test ◽  
Field Development

Abstract In May 2015, Liza-1 encountered more than 90 m (295 ft) of high-quality oil-bearing Upper Cretaceous deepwater sandstones. Immediately, the >1 billion barrel Liza field began on its path from discovery to development. Following the Liza-1 discovery, ExxonMobil and the Stabroek Block co-venturers, Hess Guyana Exploration Limited and CNOOC Petroleum Guyana Limited, undertook a blockwide 3D seismic survey, the largest performed by ExxonMobil at that time, to better delineate the resource potential. Subsequent appraisal drilling built confidence in the performance and connectivity of the reservoir while providing calibration data to inform the development. The initial appraisal well was the "inverted-Y" Liza-2 drilled in early 2016, which comprised an original hole and a sidetrack. A comprehensive evaluation program was implemented with conventional coring of both the original hole and the sidetrack to provide reservoir calibration critical to field development. Furthermore, a production well test was performed on the Liza-2 sidetrack to build confidence in dynamic performance and connectivity assumptions. The Liza-3 appraisal was then drilled down dip of the Liza-1 and −2 to confirm static connectivity across the field. A scenario modeling and simulation approach was implemented at Liza to capture the full range of plausible realizations that could represent the field. The scenarios were measured against the incoming data (Liza-2 and Liza-3) when acquired, and scenarios with greater alignment to the data continued to be pursued while others were moved to a much lower probability of occurrence. This multi-scenario approach was utilized to develop an integrated reservoir model that allowed for depletion plan optimization across a range of subsurface scenarios within flow assurance constraints, ultimately supporting the final investment decision (FID) for the Liza Phase 1 project in 2017, just 25 months after the Liza-1 discovery. Following FID, advanced, proprietary Full Wavefield Inversion seismic reprocessing and high resolution 4D baseline seismic acquisition and processing have been utilized to enable continued optimization. The path from discovery to development culminated in December 2019 with the commencement of production from Liza Phase 1 less than 5 years after the first deepwater oil discovery in Guyana.

A fuzzy evaluation method of road vehicle automatic weighing instrument in dynamic force metrological performance

2020 ◽  
Vol 64 (1-4) ◽  
pp. 1365-1372
Author(s):  
Xiaohui Mao ◽  
Liping Fei ◽  
Xianping Shang ◽  
Jie Chen ◽  
Zhihao Zhao
Keyword(s):  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Dynamic Performance ◽  
Dynamic Force ◽  
Fuzzy Evaluation ◽  
Road Vehicle ◽  
Evaluation Standard ◽  
The Road ◽  
Metrological Performance

The measurement performance of road vehicle automatic weighing instrument installed on highways is directly related to the safety of roads and bridges. The fuzzy number indicates that the uncertain quantization problem has obvious advantages. By analyzing the factors affecting the metrological performance of the road vehicle automatic weighing instrument, combined with the fuzzy mathematics theory, the weight evaluation model of the dynamic performance evaluation of the road vehicle automatic weighing instrument is proposed. The factors of measurement performance are summarized and calculated, and the comprehensive evaluation standard of the metering performance of the weighing equipment is obtained, so as to realize the quantifiable analysis and evaluation of the metering performance of the dynamic road vehicle automatic weighing instrument in use, and provide data reference for adopting a more scientific measurement supervision method.

scholarly journals A Fully Automatic Calibration System for Hydrometers in NIM

MAPAN ◽  
2021 ◽  
Author(s):  
Jintao Wang ◽  
Xiang Liu ◽  
Wencai Shi ◽  
Changhong Xu
Keyword(s):  
Full Range ◽  
Density Measurement ◽  
Fused Silica ◽  
Automatic Calibration ◽  
Liquid Density ◽  
Calibration Data ◽  
Calibration System ◽  
Solid Density ◽  
Fully Automatic ◽  
Better Than

AbstractHydrometers are widely used in industry for liquid density measurement. It is important to achieve rapid and high accuracy calibration for hydrometers. Based on the Archimedes principle, a fully automatic hydrometer calibration system in NIM was designed using Cuckow’s method. The liquid density of n-tridecane (C13H28)is calibrated with 441 g high-purity fused silica ring as the solid density standard. The buoyancy of hydrometer is measured by static weighing system with resolution 0.01 mg. The alignment between liquid surface and hydrometer scale was achieved by the lifting platform with the positioning accuracy of 10 μm. According to the weighing value of hydrometer in air and liquid, the density correction value at different scales is calculated. Hydrometer covering a full range (650–1500) kg/m3can be calibrated without changing the liquid. Taking the calibration data of PTB as reference, the experimental data show that the measurement uncertainty of this system is better than 0.3 division (k = 2).

Time-Lapse Seismic for Reservoir Management: Case Studies From Offshore Niger Delta, Nigeria

2016 ◽  
Vol 19 (03) ◽  
pp. 391-402
Author(s):  
Sunday Amoyedo ◽  
Emmanuel Ekut ◽  
Rasaki Salami ◽  
Liliana Goncalves-Ferreira ◽  
Pascal Desegaulx
Keyword(s):  
Case Studies ◽  
Niger Delta ◽  
Reservoir Management ◽  
Time Lapse ◽  
Seismic Survey ◽  
Elastic Model ◽  
Field Development ◽  
4D Seismic ◽  
The Impact

Summary This paper presents case studies focused on the interpretation and integration of seismic reservoir monitoring from several fields in conventional offshore and deepwater Niger Delta. The fields are characterized by different geological settings and development-maturity stages. We show different applications varying from qualitative to quantitative use of time-lapse (4D) seismic information. In the first case study, which is in shallow water, the field has specific reservoir-development challenges, simple geology, and is in phased development. On this field, 4D seismic, which was acquired several years ago, is characterized by poor seismic repeatability. Nevertheless, we show that because of improvements from seismic reprocessing, 4D seismic makes qualitative contributions to the ongoing field development. In the second case study, the field is characterized by complex geological settings. The 4D seismic is affected by overburden with strong lateral variations in velocity and steeply dipping structure (up to 40°). Prestack-depth-imaging (PSDM) 4D seismic is used in a more-qualitative manner to monitor gas injection, validate the geologic/reservoir models, optimize infill injector placement, and consequently, enhance field-development economics. The third case study presents a deep offshore field characterized by a complex depositional system for some reservoirs. In this example, good 4D-seismic repeatability (sum of source- and receiver-placement differences between surveys, dS+dR) is achieved, leading to an increased quantitative use of 4D monitoring for the assessment of sand/sand communication, mapping of oil/water (OWC) front, pressure evolution, and dynamic calibration of petro-elastic model (PEM), and also as a seismic-based production-logging tool. In addition, 4D seismic is used to update seismic interpretation, provide a better understanding of internal architecture of the reservoirs units, and, thereby, yield a more-robust reservoir model. The 4D seismic in this field is a key tool for field-development optimization and reservoir management. The last case study illustrates the need for seismic-feasibility studies to detect 4D responses related to production. In addition to assessing the impact of the field environment on the 4D- seismic signal, these studies also help in choosing the optimum seismic-survey type, design, and acquisition parameters. These studies would possibly lead to the adoption of new technologies such as broad-band streamer or nodes acquisition in the near future.

All-Electric Intelligent Completion System: Evolution of Smart Completion

2021 ◽  
Author(s):  
Orient Balbir Samuel ◽  
Ashvin Avalani Chandrakant ◽  
Fairus Azwardy Salleh ◽  
Ahsan Jamil ◽  
Zulkifli Ibrahim ◽  
...  
Keyword(s):  
Phase 1 ◽  
Cost Optimization ◽  
Control Valve ◽  
Production Optimization ◽  
Economic Life ◽  
Control Line ◽  
Flow Control Valve ◽  
Efficient System ◽  
Associated Gas ◽  
Field Development

Abstract Field D is a mature offshore field located in East Malaysia. A geologically complex field having multiple-stacked reservoirs with lateral and vertical faulted compartments & uncertainty in reservoir connectivity posed a great challenge to improve recovery from the field. Severe pressure depletion below bubble point and unconstrained production from gas cap had contributed to premature shut-ins of more than 50% of strings. As of Dec 2019, the field has produced at a RF less than 20%. Initial wells design consisted of conventional dual strings & straddle packers with sliding sleeves (SSD). Field development team was challenged for a revamp on completion design to enhance economic life of the depleting field. In 2015, as part of Phase-1 development campaign, nine wells including four water injectors were completed initiating secondary recovery through water flood. An approach of Smart completion comprising of permanent downhole monitoring system (PDHMS) and hydraulic controlled downhole chokes or commonly known as flow control valve (FCV) was adopted in all the wells in order to optimize recovery from the field and step towards intervention-less solutions. Seeing the benefits of intelligent completion in Phase-1, Phase-2, drilled and completed in 2019 – 2020 has been equipped with new technology "All-electric Intelligent Completion System" in 4 out of 8 oil producers. The new design addresses the reservoir complexity, formation pressure and production challenges and substantial cost optimization, phasing out the load of high OPEX to CAPEX. Installation of "All-electric Intelligent Completion System" has proven to be an efficient system compared to hydraulic smart completions system. It requires 50% to 75% less installation time per zone and downhole FCV shifting time is less than five minutes compared to several hours full cycle for hydraulic system. The new system has capability to complete up to 27 zones per well with single cable. It gave more options and flexibility in order to selectively complete more zones compared to hydraulic FCVs which requires individual control line for each zone. Future behind casing opportunities (BCO) have been addressed upfront, saving millions of future investment on rig-less intervention. In addition to that, non-associated gas (NAG) zones have been completed to initiate in-situ gaslift as and when required avoiding the dependency on aging gaslift facility. The scope of the paper is to show case the well design evolution during Field D development and highlight on how smart completion has evolved from original dual completion to hydraulic smart and recently to electric smart system, how it has contributed to cost and production optimization during installation and production life and also support the gradual digitalization of the Field D. In the end it demonstrates the optimized completion design to enhance the overall economic life of the depleting field.

Ability of Vis-PIR spectroscopy to monitor changes in organic carbon of loamy soils at two depths

2021 ◽  
Author(s):  
Hayfa Zayani ◽  
Youssef Fouad ◽  
Didier Michot ◽  
Zeineb Kassouk ◽  
Zohra Lili-Chabaane ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Near Infrared ◽  
Full Range ◽  
Nir Spectroscopy ◽  
Soil Samples ◽  
Calibration Data ◽  
Least Squares Regression ◽  
Data Set ◽  
Soil Carbon Stocks ◽  
The Mean

<p>Visible-Near Infrared (Vis-NIR) spectroscopy has proven its efficiency in predicting several soil properties such as soil organic carbon (SOC) content. In this preliminary study, we explored the ability of Vis-NIR to assess the temporal evolution of SOC content. Soil samples were collected in a watershed (ORE AgrHys), located in Brittany (Western France). Two sampling campaigns were carried out 5 years apart: in 2013, 198 soil samples were collected respectively at two depths (0-15 and 15-25 cm) over an area of 1200 ha including different land use and land cover; in 2018, 111 sampling points out of 198 of 2013 were selected and soil samples were collected from the same two depths. Whole samples were analyzed for their SOC content and were scanned for their reflectance spectrum. Spectral information was acquired from samples sieved at 2 mm fraction and oven dried at 40°C, 24h prior to spectra acquisition, with a full range Vis-NIR spectroradiometer ASD Fieldspec®3. Data set of 2013 was used to calibrate the SOC content prediction model by the mean of Partial Least Squares Regression (PLSR). Data set of 2018 was therefore used as test set. Our results showed that the variation ∆SOC<sub>obs</sub><sub></sub>obtained from observed values in 2013 and 2018 (∆SOC<sub>obs</sub> = Observed SOC (2018) - Observed SOC (2013)) is ranging from 0.1 to 25.9 g/kg. Moreover, our results showed that the prediction performance of the calibrated model was improved by including 11 spectra of 2018 in the 2013 calibration data set (R²= 0.87, RMSE = 5.1 g/kg and RPD = 1.92). Furthermore, the comparison of predicted and observed ∆SOC between 2018 and 2013 showed that 69% of the variations were of the same sign, either positive or negative. For the remaining 31%, the variations were of opposite signs but concerned mainly samples for which ∆SOCobs is less than 1,5 g/kg. These results reveal that Vis-NIR spectroscopy was potentially appropriate to detect variations of SOC content and are encouraging to further explore Vis-NIR spectroscopy to detect changes in soil carbon stocks.</p>

Implications of accurate geomechanical modelling and systematic core testing for sanding evaluation and sand control decisions – a case study from Perth Basin

2020 ◽  
Vol 60 (1) ◽  
pp. 267
Author(s):  
Sadegh Asadi ◽  
Abbas Khaksar ◽  
Mark Fabian ◽  
Roger Xiang ◽  
David N. Dewhurst ◽  
...  
Keyword(s):  
Management Strategies ◽  
Mechanical Tests ◽  
Well Test ◽  
Sand Production ◽  
Gas Field ◽  
Stress Regime ◽  
Full Field ◽  
Field Development ◽  
Sand Control ◽  
Rock Mechanical Properties

Accurate knowledge of in-situ stresses and rock mechanical properties are required for a reliable sanding risk evaluation. This paper shows an example, from the Waitsia Gas Field in the northern Perth Basin, where a robust well centric geomechanical model is calibrated with field data and laboratory rock mechanical tests. The analysis revealed subtle variations from the regional stress regime for the target reservoir with significant implications for sanding tendency and sand management strategies. An initial evaluation using a non-calibrated stress model indicated low sanding risks under both initial and depleted pressure conditions. However, the revised sanding evaluation calibrated with well test observations indicated considerable sanding risk after 500 psi of pressure depletion. The sanding rate is expected to increase with further depletion, requiring well intervention for existing producers and active sand control for newly drilled wells that are cased and perforated. This analysis indicated negligible field life sanding risk for vertical and low-angle wells if completed open hole. The results are used for sand management in existing wells and completion decisions for future wells. A combination of passive surface handling and downhole sand control methods are considered on a well-by-well basis. Existing producers are currently monitored for sand production using acoustic detectors. For full field development, sand catchers will also be installed as required to ensure sand production is quantified and managed.

Optimizing Well Locations in Green Fields Using Fast Marching Method: Optimize Well Locations for Millions of Cells Using Hundreds of Scenarios and Realizations With High Accuracy in Seconds

2019 ◽  
Author(s):  
Abdulaziz S. Al-Qasim ◽  
Mohan Kelkar
Keyword(s):  
Production Rate ◽  
Reservoir Simulation ◽  
Efficient Production ◽  
Fast Marching Method ◽  
Well Test ◽  
Fast Marching ◽  
Well Test Analysis ◽  
Test Analysis ◽  
Field Development ◽  
Marching Method

Abstract To perform an optimization study for a green field (newly discovered field), one must collect the information from different parts of the field and integrate these data as accurately as possible in order to construct the reservoir image. Once the image, or alternate images, are constructed, reservoir simulation allows prediction of dynamic performance of the reservoir. As field development progresses, more information becomes available, enabling us to continually update and, if needed, correct the reservoir description. The simulator can then be used to perform a variety of exercises or scenarios, with the goal of optimizing field development and operation strategies. We are often confronted with important questions related to the most efficient well spacing and location, the optimum number of wells needed, the size of the production facility needed, the optimum production strategies, the location of the external boundaries, the intrinsic reservoir properties, the predominant recovery mechanism, the best time and location to employ infill drilling and the best time and type of the improved recovery technique we should implement. These are some of the critical questions we may need to answer. A reservoir simulation study is the only practical means by which we can design and run tests to address these questions in sufficient detail. From this perspective, reservoir simulation is a powerful screening tool. The magnitude, time and complexity of a reservoir simulation problem depends in part on the available computational environment. For instance, simple material balance calculations are now routinely performed on desktop personal computers, while running a field-scale three-dimensional simulator may call for the use of a supercomputer and may take many days to finish. We must also take into account the storage requirements and limitations, CPU time demand and the general architecture of the machine. The problem arises when there is a large amount of data available with a study objective that requires running several scenarios incorporating millions of grid cells. This will limit the applicability of reservoir simulation as it will be computationally very inefficient. For example, determining the optimum well locations in a field that will result in the most efficient production rate scenario requires a large number of simulation runs which can make it very inefficient. This is because one will have to consider multiple well scenarios in multiple realizations. The main purpose of this paper is to use a novel methodology known as the Fast Marching Method (FMM) to find the optimum well locations in a green oil field that will result in the most efficient production rate scenario. The concept of radius of investigation is fundamental to well test analysis. The current well test analysis relies on analytical solutions based on homogeneous or layered reservoirs. The FMM will enable us to calculate the radius of investigation or pressure front as a function of time without running any simulation and with a high degree of accuracy. The calculations can be done in a matter of seconds for multi-millions of cells.

Development and validation of behavioral biases scale: a SEM approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ritika ◽  
Nawal Kishor
Keyword(s):  
Decision Making ◽  
Investment Decision ◽  
Phase 1 ◽  
Secondary Data ◽  
Higher Order ◽  
Second Order ◽  
Individual Investors ◽  
Content Type ◽  
Behavioral Biases ◽  
Investment Decision Making

PurposeThis paper attempts to identify the biases in decision-making of individual investors. The paper aims to develop and validate a higher-order behavioral biases scale.Design/methodology/approachScale development is done by identifying the relevant items of the scale through existing literature and then, adding new items for some biases. In phase 1, using a structured questionnaire, data was collected from 274 investors who invest in financial markets. The major dimensions of the scale have been pruned by using exploratory factor analysis administered on data collected in phase 1. Higher-order CFA is used to analyze the data and to validate the scale on another set of data (collected in phase 2) containing 576 investors.FindingsThe study reveals that the scale for measuring behavioral biases has many dimensions. It has two second-order factors and 13 zero-order constructs. Two second-order constructs have been modeled on the basis of cause of errors in investment decision-making, that is, biases caused due to cognition, biases caused due to emotions.Originality/valueBehavioral biases are yet to receive a due attention, especially, in the Indian context. The present research is focusing on providing an empirically tested scale to test the behavioral biases. Some of the biases, which have been analyzed using secondary data in previous studies, have been tested with the help of statements in this study.

Successful production application of 3‐D amplitude variation with offset: The lessons learned

Geophysics ◽  
2002 ◽  
Vol 67 (2) ◽  
pp. 379-390 ◽  
Author(s):  
William L. Soroka ◽  
Thomas J. Fitch ◽  
Kirk H. Van Sickle ◽  
Philip D. North
Keyword(s):  
Gas Production ◽  
Lessons Learned ◽  
Seismic Survey ◽  
Total Production ◽  
Old Field ◽  
Amplitude Variation ◽  
Initial Flow ◽  
Amplitude Variation With Offset ◽  
Field Development ◽  
Infill Drilling

Amplitude variation with offset (AVO) analysis was successfully performed on a 3‐D prestack seismic volume. Important conclusions were that AVO results could improve field development and production, that 3‐D AVO results were more useful than 2‐D AVO results, and that reliable AVO results could be generated on land. The AVO results were used to help develop an infill drilling program to increase production. AVO information lowered the risk of finding hydrocarbons by helping to identify seismic events that had a higher probability of being gas‐saturated sands. The 3‐D seismic survey covered known gas zones and potential new reserves. The AVO calibration work showed that positive AVO gas responses (classes 2 and 3) were observed for 90% of the zones associated with known production. One 15‐ft‐thick gas reservoir below seismic resolution did not give a positive AVO anomaly. A well drilled to an untested zone displaying a positive AVO anomaly encountered commercial quantities of gas. Production from this new zone at the initial flow rate increased the total production rate in this 25‐year‐old field by >50%. The AVO method was shown to be applicable onshore and to provide useful results in more consolidated geologic environments with classes 2 and 3 AVO responses. For the successful use of AVO, greater effort and extra care in acquisition and processing were needed than in a normal seismic program.

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