bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Artificial Neural Network Control Model for Predicting the Pressure Distribution in a Complex Commingled Well
Authors: Ikezue E. N. , Onukwuli O. D. 
Published: July 2014

Abstract
Artificial neural network are closely modeled on biological processes for data processing, specifically the nervous system and its basic unit the neuron. The neuron receives multiple signals from other neuron through its dendrites each signal multiplied by a weighting function (Coefficient). These signals are added in the cell body or soma and when each component signal reaches a threshold value, a signal known as action potential is sent out through the axon which is the neurons output channel. Data obtained from a case study well were modeled and analyzed for predicting the pressure profile. The result showed that the pressure profile increased from 0.00 psia/cp and had an asymptotic limit at 220000 psia/cp at 400 psia-pressure and for temperature 100°F respectively. Then it increased from 0.01 psia/cp to 0.18 psia/cp (specific gravity 1.2) at a temperature of 100°F, the result was compared with those of Earlougher [3] and found to be valid for (1) radial flow (2) isotropic and homogeneous medium (3) general gas law applies. The case study well-opukusi 8 (escravos swamp field) south east Nigeria was monitored for 36 days period when it was shut-in for the pressure to build up and attain steady state to enable the prediction of productivity index which has the value of 0.60 which is indicative of a declining productivity.
Effect of Uncertainty in PVT Properties on CO2 EOR
Authors: Stanley Buduka 
Published: July 2014

Abstract
The aim of this study is to determine the impact of uncertainty in PVT properties on enhance oil recovery using CO2 Injection. A homogeneous 3D model using Eclipse 300 a compositional simulator was constructed with eleven components of hydrocarbon constituents present. The Peng –Robinson Equation of state (EOS) was used to characterize the fluids and the sensitivity study. The sensitivities were performed on the Binary interaction Coefficient, Fluid composition, miscibility, Temperature and Pressure of the reservoir system.
The studies show that Fluid composition has a significant impact on the reservoir recovery factor .The miscibility effect sensitivity also shows that the recovery improves as the process becomes more miscible, while the sensitivity on the Binary interaction coefficient has no effect on the recovery factor of the reservoir ,also reservoir fluid composition with heavier hydrocarbons is unsuitable for CO2 enhanced oil recovery due to low API gravity.
A 2D model sensitivity carried out on the temperature and pressure show that an increase in temperature gives an increase in the recovery based on the model, while a decrease in the reservoir pressure also has a significant increase in the reservoir recovery. The model result was linked to an economic model to determine the impact of uncertainty in PVT properties on the CO2 EOR to take economic decision based on economic indices such as NPV and IRR.
Guidelines for Uncertainty Assessment using Reservoir Simulation Models for Green- and Brown-field Situations
Authors: Ambastha Anil K. 
Published: July 2014

Abstract
Uncertainty assessment using reservoir simulation models for green- and brown-field situations has become a common practice. While capturing uncertainties in forecasts is required in all situations, developing multiple history-matched models is also an important goal for brownfield situations. Objective of this study is to provide systematic and practical guidelines for uncertainty assessment work using reservoir simulation models.
This paper discusses steps involved in any uncertainty assessment including selection of uncertain parameters and their ranges, practical experimental design methods, appropriate response or tracking functions (or variables), and data analysis techniques. Roles of lessons learnt from a base-case history-match exercise for a brownfield situation as well as earth modeling/petroleum engineering knowledge in setting up appropriate parameters and ranges are emphasized. Guidelines are provided to judge "quality of history match" based on prudent interpretation of response or tracking functions/variables. A Monte Carlo simulation-based methodology to develop multiple history-matched models for brownfield situations is presented in detail including practical tips on problem setup and analysis of results. Unique nature of uncertainties related to forecasting situations is discussed with an emphasis on a need to engage all operational and facilities personnel to develop adequate forecast problem description and economic success metrics. Guidelines presented in this paper are illustrated using a case study example. Practical tips presented in this paper would be of use to all reservoir simulation engineers carrying out uncertainty assessments.
Comparative Analysis of Permanent Downhole Gauges and their Applications
Authors: Enyekwe A. E. , Ajienka J. A. 
Published: July 2014

Abstract
Permanent Downhole Gauges (PDGs) are important accessories to run in with the completions of a well and are particularly crucial in offshore locations and deviated wells where intervention is uneconomical and risky. This paper performs a comparative analysis of the different technologies used in the design of PDGs. It outlines specific use and advantages of each of the sensor types used in PDGs. From the comparative analysis, optical sensors are the most versatile in terms of ability to measure a broad range of parameters and can survive harsh conditions of pressure and temperature. They are relatively expensive. Piezoelectric sensors such as Quartz or Sapphire crystals are also very robust but are limited to a range of temperatures and pressures. Silicon-on-insulator sensors are most useful in wells with artificial lift systems (ESP or Gas lift) as they can determine the efficiency of the artificial lift system. They are also limited by operational temperatures and pressures. Capillary tube pressure gauges are rugged and well suited for extreme conditions of temperature and pressure but cannot measure a wide range of parameters. Two quick-look flowcharts for selection of PDGs were developed and presented in this work as helpful output. One is based on well properties while the other is based on field properties. Economic implications are considered in both. A quick cross-reference of the two flowcharts can help investors in their selection of a PDG.
Practical Application of Multi Rate Deconvolution
Authors: Obeahon P. P. , Sedgwick A. , Okereke O. 
Published: July 2014

Abstract
Deconvolution is not a new interpretation method or a replacement of conventional methods in the analysis of well test data. It is rather a process that is used to convert variable rate pressure data into constant rate pressure data thereby providing more pressure data for the determination of an interpretation model. The usage of this robust method is not widespread among Reservoir Engineers resulting into missed opportunities or benefits in its application.
To stimulate more widespread usage, this paper presents the results of three case studies demonstrating how deconvolution can aid in reservoir characterization. The success of applying this technique depends a lot on the quality of the test data and on the deconvolution algorithm applied. This was applied to reservoirs with single well.
The first case study involves a retrograde gas condensate reservoir Z100 in the Niger Delta, Here deconvolution was used to predict initial reservoir pressure (Pi) from Multi rate test (MRT) data and validate boundary response obtained from single pressure build up (PBU) analysis. The second case study involves a wet gas reservoir Z200 in the same field as the Z100. Prior to drilling, it was estimated from analogue data that the proposed well would recover 154Bscf. Following completion of the well an MRT was conducted. Numerically matching the deconvolved response of all available flow periods showed that the well will drain 148Bscf. This shows an acceptable 0.4% deviation. The third case study involves an oil field N100 in the North Sea. Here, deconvolving 8 years of production showed that connected Stock Tank Oil Initially-In Place (STOIIP) had increased due to dynamic fault seal failure. The origin of the fault seal failure as well as Pi was estimated. The result is consistent with the 2005 4D seismic interpretation acquired in this field.
These three case studies demonstrate that deconvolution can aid in Pi estimation, better estimation reserve evaluation, dynamic fault seal analysis, and potentially reduce the level of uncertainty and non-uniqueness of PTA. A procedure on how to use deconvolution in reserve estimation is also presented. It is hoped that this paper having highlighted the merits of deconvolution will encourage reservoir engineers to use this technique more confidently.
Managing Waterflood in Deepwater Soft Rock: The Bonga Experience to Date
Authors: Olatunbosun Olugbenga 
Published: July 2014

Abstract
The Bonga field came on stream in November 2005 with 16 predrilled wells (9 producers and 7 water injectors). The field is characterised by unconsolidated rock but with permeabilities in the multi darcy range. The reservoirs are undersaturated and contain light crudes in the 28-35 deg API range. The field contains STOIIP of over 4 billion barrels across 6 reservoirs and it is developed by waterflood. The reservoir characteristics have culminated in high injection and production rates per well with injection rates above 60 kbpd and production rates above 50 kbpd achieved for some wells.
Plateau field production and injection was achieved soon after start up with production and injection at or near nameplate capacities of 225 kbopd and 300kbwpd respectively. This continued until H1 2008 when injectivity decline set in. As water breakthrough had already occurred, the reduced deliverability of the water injectors further compromised the voidage replacement capacity of the system. Net result was that the field fell off plateau but production was soon restored to near plateau level. Since then, production has been off plateau intermittently with the integrated team taking action to ameliorate the situation and to bring the field back to near plateau level of some 200 kbopd. The key issues/challenges that have resulted in production decline include: injector impairment, inadequate topsides injection capacity, injection well failures, baffles mitigating injector-producer connectivity, producer impairment, ScSSV failures, injector longevity, injection water quality, produced water handling, premature water breakthrough.
Cross discipline corrective and innovative measures have been taken to address the above challenges and maximise value from this field. The measures cut across subsurface, wells, topsides, subsea and production operations disciplines and include: Backflush/refrac, acid stimulation, increased injection capacity, improved injection water quality, fracture mode injection only, drilling of horizontal wells as preferred option for injectors, breaking down of connectivity baffles by sustained high rate water injection etc. This paper captures the key learnings from the Bonga experience and the corrective measures applied. The field overview and performance history of the field are illustrated in figs 1&2.
Synthesis and Applications of Nanomaterials in Enhanced Oil Recovery
Authors: Odedele Engr T. 
Published: July 2014

Abstract
Given the large amount of by-passed oil and gas and low oil recovery factors in many reservoirs coupled with global energy demand projected to rise as high as almost 60%in the next 30 years particularly in Africa, it is quite evident that convectional petroleum engineering techniques are not adequate and efficient for reservoir characterization and production optimization. This challenging trend may be met only by revolutionary breakthroughs in energy science and technology. The industry thus requires stunning discoveries in underlying core science and engineering which can only be accomplished through integration and global approach. Breakthroughs in nanotechnology open up the possibility of enhancing and optimizing oil and gas production beyond the current available technology by introducing innovative concepts that are more efficient and environmentally friendly. The term “nanotechnology” covers processes associated with the creation and utilization of structures in the 1.0 nanometer (nm) to 100 nm range. Nanofabrication involves engineering at the atomic length scale. It no doubt, offers substantial economic and societal benefits than any technology and holds the promise of both incremental improvements of existing products and the potential for revolutionary changes that could transform entire industries. Nanotechnology is characterized to be a multidisciplinary field, making it inherently innovative and more precise than other technologies. In this paper, the greatest potential for innovative solutions in enhanced oil recovery (particularly water flooding) through the investigation and synthesis of water-based nano-particle will be discussed.
Integrated Multidisciplinary Pore Pressure Prediction Leads to Accurate Casing Design: A Case Study
Authors: Effiowan Akiba Eyo , Umahi Otuka , Richard Ebisike , Tunde Alabi , Lamens Jo , Oyibo Alphonsus 
Published: July 2014

Abstract
The well design of LT- 4 and LT- 5 wells in the Niger delta is evidence that application of current 3-D seismic technology, accurate modelling and RFT data with inclusion of offset well information lead to improved pore pressure and fracture gradient predictions.
The LT field had no cores, no PVT samples, nor production history. Seismic modelling by geologists and geophysicists observed a pressure trend above hydrostatic from 10, 600ftTVDSS which corresponds to the 17.4MFS. Pressure data (RFT) from offset wells and other drilling performance data (FIT, mud weight, kick pressure) from wells drilled in the wider area were used to constrain the pressure prediction. Two distinct pressure ramps were observed from the plot, coinciding with the base of the 17.4MFS and 19.4MFS respectively (fig. 2.1) which illustrates the geological control on overpressures. The kill mud weight data indicated from offset wells in which kicks occurred provided information on overpressures in the 8 ½” hole sections. The pore pressure evaluation over pressures in the deepest zones would not have been predicted based only on either the other pressure data (RFT) available or on the seismic velocity data.
Sensitivity analysis of the pore pressure prediction with inclusion of the well kick data for the well planning and design provided a more robust basis for design resulting in selection of an appropriate intermediate casing weight and grade.
This paper presents a case study of the LT- 4 and LT-5 wells showing how an effective casing design which depends on an accurate pore pressure prediction can be achieved through integration of seismic calibration and offset well information.
A Robust Way of Managing Water and Gas Encroachment Modeling Issues in a Matured Reservoir with Dip Complexity
Authors: Suleiman Ahmed , Peter Joseph 
Published: July 2014

Abstract
Robust re-development and management of brown field depends on having an integrated reservoir model that can reliably replicate performance history, and predict future performance in form of acceptable and consistent production forecasts that can be validated with other methods. This often involves integration of all geosciences and petroleum engineering data in a relatively fine simulation model which, although captures the heterogeneities in the reservoir to some more detailed level, usually takes up so much CPU space and long model's runtime. Typically, a shorter runtime can be achieved by building a coarser static model, and/or upscaling finer static model that will lead to the loss of some of the reservoir's pecularities. Such coarser models are normally impacted by many shortcomings, most important of which is numerical dispersion that result in spurious gas cusping or water encroachment/coning issues. These problems are more critical in reservoirs with high dipping structure or in model with some random skewed or dipping cells. This paper demonstrates a robust methodology of managing these issues of long run time and not compromising on quality of result.
This case study was on a 67 ft oil-rim reservoir (20km × 8km) with huge overlying gas cap and long production history in the Niger Delta. The wells in this reservoir are characterized by some water coning and gas cusping problems.
In order to achieve shorter models runtimes while still preserving key reservoir details, a relatively coarse static model was constructed based on consistent geological concepts incorporating all relevant geosciences and Petroleum Engineering data. Preliminary attempts made towards using the coarse model to achieve acceptable history match failed, largely due to numerical dispersion issues arising from high dipping model cells around areas with slight increase in structural dip. The model was subsequently updated by "refinement" of the high dipping cells at the free water level interface only. The updated model, whilst still fast, achieved acceptable history match within the defined uncertainty envelop, which could only have been achieved by a very fine model that will take order of magnitude time to run.
Based on the model derived using this approach, more than 12 hours of model runtime was saved, the existing well behaviours were better replicated and few new drilling opportunities were identified. The use of this robust approach results in a better understanding of the subsurface and delivers new opportunities which will ultimately enable more optimal (faster decision making) management/development of the field.
Development of a Self Configuring Mesh Network Architecture for Digital Oilfield Implementation
Authors: Idachaba Francis Enejo 
Published: July 2014

Abstract
The Mesh network architecture provides a robust architecture for ad-hoc wireless communication networks utilizing low power transceiver for short hop links. The key advantages of this architecture include the ability of the network to configure itself and setup a transmission path between the different nodes. The requirement for all the nodes in the mesh network to be ON makes it unattractive for digital oilfield (DOF) implementations in both onshore and offshore Oil and Gas production installations due to the drain on the power supply. The self-configuring mesh network topology proposed in this work extends the coverage of the wireless sensor networks deployed in DOF implementations by maximizing the advantages of the mesh network and the power saving configurations of the star topology currently used in DOF implementations. It utilizes a set of algorithms which enables the Remote Terminal Units (RTU) to go into sleep mode without impacting on the real-time communication advantage of the mesh network. These algorithms enable the system to setup neighborhood cells comprising of RTUs within its coverage and identify multiple transmission paths in the event of a failure of the main link. This architecture allows more RTUs to communicate with the gateway using short hops thereby increasing data reliability. The short transmit distance extends the battery life and maximizes the gateway license as more RTUs can be linked to access the same gateway. The synchronization algorithm also enables longer battery life for the RTUs by ensuring that the RTUs operate in the sleep mode. The topology will increase the data reliability and reduce both the OPEX and CAPEX required for setting up the communication links in DOF implementations in both onshore and offshore installations.
Industry-Academia Collaborations. The Shell Sabbatical Model
Authors: Idachaba Francis Enejo 
Published: July 2014

Abstract
The quality of graduates produced by any institution is assessed by the ability of those graduates to add value to the business of their employers. Research has shown that the factors with the greatest impact on the quality of the graduates include the quality of the curriculum, the delivery method, the quality of the lecturers and the motivation of the students. The shell sabbatical model takes University lecturers with relevant proposals and integrates them into the company for a period of One year giving them the opportunity of participating fully in the company operations. This provides them with an opportunity to learn the culture of the industry and understand the skill requirement of the industry while contributing to the company business. It also provides these lecturers with an insight into the needs of the industry thus shaping their research directions. This model impacts on the quality of the lecturer, the curriculum and the teaching method by providing the lecturer with access to the latest technology in the industry, enabling the lecturer to identify relevant modifications that should be made to the curriculum of his courses and changing his teaching methods as he is now able to teach with practical examples and real life illustrations and scenarios. This also results in an increased motivation as they are taught with real life scenarios and examples. This paper reviews the Shell sabbatical model and presents some results on its impact on the University lecturer, the industry, the student and the Nigerian educational system.
Modelling a Complex Niger Delta Reservoir for Secondary Recovery: The Use of Assisted History Matching for Improved Uncertainty Management
Authors: Mijinyawa A. 
Published: July 2014

Abstract
The model maturation method proposed by Joosten et al (Joosten et al, 2011) was applied to a large, complex and mature Niger Delta reservoir system aimed at obtaining a range of acceptable history-matches as basis for evaluating the feasibility of water injection. The method involved forcing gridblock level changes in reservoir properties to obtain model matches for observed field performance. These changes were then used as feedback to improve/update the geo-thinking (understanding of the subsurface).
Of the various model maturation components/types in use, a combination of Experimental Design (ED) with the Adjoint methods of assisted history matching was employed. The first stage involved the assessment of the initial uncertainty space using ED techniques. This resulted in the identification of the most significant uncertainty parameters with respect to key history-match criteria and led to a reduction in the size of the uncertainty parameter space. This reduced (more manageable) space formed the input into the Adjoint process which essentially involved the (automated) identification of the location and extent of changes in gridblock permeability required to improve the model response vis-à-vis production performance.
Despite previous examples of the successful application of this approach to integrated reservoir modelling (Joosten et al, 2011), results in this case showed that it was not entirely possible to fully account for all the forced permeability changes from both a subsurface and surface perspective. A number of reasons were identified for this outcome. Chief amongst these is the lack of a full understanding of the dynamic behaviour of the (complex) faulting in the field. In the end, a compromise position was adopted where the extent and location of changes in gridblock permeability was restricted based on observed well log information. This position was adjudged to still give acceptable history-match results that could reasonably be used to underpin the water flood project.