bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reuse of Produced Water by Membranes for Enhanced Oil Recovery
Authors: Nair Remya Ravindran , Protasova Evgenia , Bilstad Torleiv , Strand Skule 
Published: September 2016

Abstract
Produced water (PW) management and reuse of PW has economic and environmental benefits compared to PW discharge. This research focuses on membrane separation efficiencies in adjusting the ionic composition of de-oiled PW and evaluating the possibility for smart water production from PW for enhanced oil recovery. Key characteristics of smart water for carbonate reservoir is increased concentration of divalent ions and depletion of monovalent ions.
Dual media is used for oil removal from PW. De-oiled PW is feed for Nanofiltration (NF) membranes for separation of barium and calcium ions. Combination of NF retentate with seawater (SW) as feed and NF permeate from PW is also considered. PW permeate is mixed with SW spiked with determining multivalent ions, sulfate or phosphate, which alter wettability of oil reservoirs.
Currently, smart water is produced by adding chemicals to fresh water or low total dissolved solids (TDS) water produced by reverse osmosis (RO) or flash distillation. Using de-oiled PW as feed to NF will reduce power consumption, footprint and chemicals. PW can be reinjected into reservoirs after removing scale-causing ions. By injecting low barium and calcium PW brines, the frequency of scale squeezes will decrease. Membrane performance is evaluated for flux and separation efficiencies of calcium and barium. Barium concentrations in synthetic PW is increased 20 times the original concentration in Tor Field in North Sea, for evaluating NF separation efficiency. Negligible amount of barium is present in NF permeate at pressures of 8-12 bars resulting in a permeate flow rate of 200 L/h for a membrane area of 2.6 m2.
Increased sulfate concentration in smart water enhances recovery by 40 % of original oil in place. However, BaSO4 scalingcan be initiated even with negligible barium concentration if high sulfate level is present in the injected brine. The novelty of this research resides in the use of non-precipitating phosphate replacing sulfate for smart water production, simultaneously decreasing barium concentration and scaling potential of PW. However, precipitation of calcium occurred in presence of high concentration of phosphate. Power consumed by NF membranes for smart water production is calculated at 0.37 kWh/m3.
Increase Efficiency of Smart Field Integrated Operations Through Service Level Management
Authors: Reddicharla Nagaraju , Bangari Praveen , Konkati Sarath 
Published: September 2016

Abstract
The current trend of low oil and gas prices demands operators to improve operational effectiveness and optimize production at different process cycles range from days to months to years. Smart field integrated operations plays a major role and provides more rigorous, effective and consistent surveillance to help reduce deferment, accelerate decision making and enhance production system performance. This paper talks about how the efficiency of smart field operations can be improved by enabling service level management for the data, processes and IT applications.
In general smart field operations are often failed due to lack of knowledge to turn the data into meaningful information especially in the case of real time surveillance activities for a given business critical challenge to make an operational advise & decision and the complete sense of asset awareness translating into asset optimization. Smart fields is not just about improved automation.
The first step in this new approach is to create a service catalog (such as Water injection surveillance, ESP & Gas-lift surveillance, well & facility reviews…etc.) for identified business challenges (High GOR, High water cut, process debottle-necking…etc.) in the asset where the smart field integrated operations can provide solutions. After the business process is identified for a given service, the second step is to augment the processes with the depth of service requirements and define the service execution workflow by enabling smart field integrated operations in it. The third step is to define the staffing or resource model to deliver the service in the asset. The existing resources in the asset can also carry out certain jobs in the service execution. The fourth step is to derive the tangible and intangible value generated from the service delivered and aligned to organizational KPIs. The fifth and final step is to capture the knowledge generated from the services for the future use.
The real time data availability at the right time with the given frequencies, business process performance at the agreed service levels in the service execution workflow and the availability of IT applications play a major role to achieve the success. However this can only be efficiently monitored with the agreed service levels defined into it and tracked for continuous improvement. The assets teams can meet on a scheduled basis and review the performance of services delivered and measure efficiency of smart field integrated operations.
This helps to eliminate waste and improve productivity and use the asset resources efficiently with the help of smart field integrated operations. This paper illustrates the detailed approach, application of services levels in the processes, examples and the benefits.
Oil Viscosity Estimation from NMR Logs for In-Situ Heavy Oil Characterization
Authors: Hursan Gabor , Seifert Douglas J. , Lyngra Stig , Palmer Richard G. 
Published: September 2016

Abstract
This publication presents the calibration of a downhole nuclear magnetic resonance (NMR) log-based oil viscosity correlation with laboratory live oil viscosity measurements. The laboratory data set was acquired from formation tester sampling (FTS) including 37 pressurized single-phase oil samples taken from 11 wells. The FTS oil viscosity range was 1-1,400 centiPoise (cP).
In two Saudi Arabian carbonate fields, the moveable hydrocarbons consists of crude with in-situ oil viscosities of ~1-3 cP. Thick tar mats are located below the oil columns, separating the moveable hydrocarbons from the aquifers. For pressure support, horizontal water injectors are drilled into the heavy oil transition zones, located between the moveable oil and the tar, utilizing real-time logging while drilling (LWD) NMR data and formation tester mobility data for well placement. For optimum water injector placement, accurate NMR log-based determination of the reservoir oil viscosity is critical. The NMR logs are processed using an integrated petrophysical model that subdivides the oil volume into light, medium and heavy components. The in-situ viscosities are calibrated to the relative percentage of heavy-medium components to the total oil volume.
Despite the large geographic distance between the 11 sampled wells, the presented results reveal a remarkable consistency between the in-situ oil viscosity data from the FTS laboratory analyses and the NMR log responses. In this particular case, the well results suggest that one viscosity relationship is adequate for describing a large geographical area containing multiple medium and heavy oil reservoirs. The results indicate the logarithm of viscosity to be a clear function of the heavy-medium oil volume percentage. Two distinct linear segments are sufficient to cover the full 1-1,400 cP oil viscosity range. One of these segment describes the mobile oil column with low heavy-medium oil volume percentage and oil sample viscosity of less than 3 cP. The other segment defines the oil/tar transition zone where the presence of asphaltene aggregate structures leads to a very rapid increase of oil viscosity versus depth covering the range 3-1,400 cP. The robustness of the method is demonstrated by the low statistical uncertainties for the entire viscosity range, when comparing the predicted NMR oil viscosity correlation results with the laboratory results, from the 37 physical oil samples.
The new NMR empirical oil viscosity correlation was built on a previously published methodology, but the existing correlation did not do a particularly good job for the lower oil viscosity range (&lt;10 cP) and for the very heavy oils. The purpose of this new publication is to present a new empirical NMR viscosity correlation with much wider validity range.
Uncertainty Quantification for History Matching Problems With Multiple Best Matches Using a Distributed Gauss-Newton Method
Authors: Gao Guohua , Vink Jeroen C. , Chen Chaohui , Tarrahi Mohammadali , El Khamra Yaakoub 
Published: September 2016

Abstract
It is crucially important for decision making and an extremely challenging task to properly quantify uncertainty of model parameters and production forecasts after conditioning to production data. A novel approach is proposed to generate approximate conditional realizations using the distributed Gauss-Newton (DGN) method together with a multiple local Gaussian approximation technique. Results are compared with those obtained from other approaches such as Randomized Maximum Likelihood (RML), Ensemble-Kalman-Filter (EnKF), and Markov-Chain-Monte-Carlo (MCMC) simulation.
The DGN method is developed to find multiple local minima of the objective function in parallel, by collecting and sharing information from dispersed regions in parameter space dynamically. Around each local minimum, the estimated Hessian obtained from the Gauss-Newton approximation along with the prior inverse covariance matrix is used as a local approximation of the posterior inverse covariance matrix. The posterior joint PDF can then be approximated as a weighted linear superposition of multiple local Gaussian distributions, which can be sampled very efficiently without having to resort to expensive MCMC methods.
The proposed approach is first validated using a nonlinear history matching toy problem with multiple modes. In terms of efficiency, the new approach can significantly reduce the computational cost and accelerate the uncertainty quantification process, when compared to the traditional RML method or traditional MCMC approaches. In terms of accuracy, uncertainty characteristics obtained from the proposed approach are comparable to those generated from the MCMC simulation, and they are much better than those obtained from EnKF or RML. The approach is then also applied to a real field history matching problem, where the dynamic system of multi-phase flow in the reservoir exhibits very strong nonlinear behavior, and the objective function has multiple local minima. Uncertainty ranges of production forecasts for the real field case are quantified by generating an ensemble of conditional realizations. The production forecasts for all conditional realizations are consistent with the production data observed after the history matching period, which further validates the applicability of the proposed method to real field problems.
Its high efficiency makes the new approach practical for large-scale problems, for which methods based on Design of Experiment break down. Furthermore, as was argued by Vink, Gao, and Chen (2016), inevitable under-modeling reduces the urgency of using very accurate methods to quantify uncertainty, and using a multi-Gaussian approximation of the posterior should be more than sufficient. The proposed approach has been implemented in our next generation reservoir simulation and history matching system called PetroSigns.
A New Automated Algorithm for Designing the Optimal Single-Well-Chemical-Tracer SWCT Tests At Various Reservoir Conditions
Authors: Khaledialidusti Rasoul , Kleppe Jon 
Published: September 2016

Abstract
Single-well-chemical-tracer (SWCT) is the most commonly used field method to determine oil or water saturation in one-spot pilot. The SWCT method overcomes the limitations of the well-to-well tracer method, being long measuring time and excessive tracer dispersion. However, other limitations are encountered such as the shorter investigation region and the effect of the product acid due to the hydrolysis reaction on the reliability of the saturation measurement. The latter one is still considered to be a controversial issue.
Saturation measurements from large investigation regions are more reliable because of larger measured volume and longer distance away from the wellbore damage and capillary desaturated zone. However, some criteria prevent the test from reaching the desired investigation region and may thus cause deviations in the test results from the ideal test. These criteria are the higher fraction of hydrolyzed ester and the detection limit of ester, hydrolysis reaction during injection and production times, and fluid drift and tracer dispersion during shut-in time. The main objective of this research is to develop an automated algorithm to design the optimal SWCT test including the larger investigation region and more ideal tracer profile according to the reservoir conditions.
The devised algorithm has been programmed based on the six different stages. In the first four stages, all test design parameters in different investigation regions and retardation factors are calculated. The test design parameters are sizing the test volume, test timing (i.e., injection, shut-in, and production), tracer concentration during the test, and the mean residence volume. In the fifth stage, all criteria are taken into consideration to find the optimal test design. After that, the achieved parameters are applied in the simulation stage (sixth stage) of the workflow. The objective of the final stage is the investigation of the effect of the following items on the tracer result in order to develop more ideal (i.e., Gaussian) tracer profiles: 1) ester bank and concentration, 2) ester properties, 3) shut-in time and adapting the conventional rule to the reservoir conditions.
To evaluate the workflow methodology, two different field test cases with different reservoir conditions are employed in order to reflect the influence of different stages of the algorithm. After the numerical interpretation of these two tests, the algorithm is performed to design the optimal test with all criteria taken into account. The results show that the proficiency of the algorithm could be noticeable in the design of an optimal test with larger investigation region yielding more Gaussian-like profiles by the means of modifying the conventional rule of the shut-in time and selecting an optimal ester bank and concentration fitting to the reservoir conditions.
Maximizing Well Uptime Through Effective Well Operations And Integrity In South Iraq
Authors: Kumar Randhir , Hindawi Kareem , Awobadejo Mayowa , Alharthy Said , Al Jumah Ali 
Published: September 2016

Abstract
Achieving high production system availability of any asset is one of the most important target thereby creating a stable plateau production and continuous hydrocarbon supply to customers. This ambition can be reality with comprehensive planning & execution, and certain due considerations that enable integration across all the asset's divisions and units. The authors through this this paper deliberate on the most critical factors that can improve the uptime remarkably which contributed to the success story of the Shell operated asset in Iraq in achieving high uptime percentage of 99% in 2015. These factors are described in a level of detail in this paper.
Shell Operational Excellence Blades is a set of documents, containing rules and minimum requirements of operations in all the sub divisions of the asset, they show clear examples of best in class practices and the ways to implement them. These are followed by all the assets operated by Shell to ensure integration across the board and proper management of the asset, ultimately resulting in good outcomes.
Effective well operations describe the process for safely and efficiently operating wells within the integrity envelope to produce at their optimum. It is a key part of the operating integrity work stream and ensures wells are operated within Shell's Asset Integrity - Process Safety Management Standards (AI-PSM). It involves knowing and understanding the well operating limits, continuously monitoring and controlling the wells within these boundaries. Optimizing production through maximizing uptime is administered through a systematic daily well surveillance and optimization process, ensuring standards and processes are adhered to.
Production system optimization can be described as the loop of identifying a bottle neck, then removing it, allowing for increased production rates, which serves as a key point in realizing high uptime for any producing asset. Integrated planning on the other hand, supplemented by proactive surveillance, is another critical item that needs care and attention throughout the year. Surveillance is recommended to always by "proactive" and not "reactive," to prevent any possible system down time or irreversible damage.
All the assets are operated by people, and hence people integration comes forward as the glue that brings everything together and removes artificial boundaries, facilitating work delivery and improving the outcomes. Hence, implementing a collaborative working environment is highly encouraged.
Impact of Local Stress Heterogeneity on Fracture Initiation in Unconventional Reservoirs: A Case Study from Saudi Arabia
Authors: Oparin Maksim , Sadykov Almaz , Khan Safdar , Tineo Roberto 
Published: September 2016

Abstract
Drilling horizontal wells with subsequent multi-stage hydraulic fracturing have become essential for economic production of oil and gas from unconventional resource plays. The selection of appropriate intervals for perforation clusters (in cased holes) is one of the keys for a successful fracturing job in horizontal wells. An inappropriate interval may lead to extremely high breakdown pressures, or even an inability to breakdown, which can prevent that part of the well from contributing to the production.
Wellbore staging where perforation intervals are selected is based on minimum horizontal stress along the lateral has proven to be effective and has increased production contribution of each stage. We found this approach can be effective only in normal stress regime. In other stress regimes, e.g., strike-slip and reverse stress regimes, breakdown pressures were discovered to be higher in intervals of lower horizontal stress, contrary to what we typically see in normal stress regime.
This study adds practical soundness to theoretical methodologies of fracture breakdown pressure prediction, and improves the completion design to meet the expected fracturing pressure in the tectonically stressed environment of unconventional gas wells in Saudi Arabia.
To design completions that can withstand breakdown pressures in various stress regimes, hoop stress and the resultant fracture breakdown pressure must be taken into account. This study reviews the process of openhole image log analysis, selection of the uniaxial compressive strength (UCS) correlation, estimation of maximum horizontal stress and obtaining hoop stress. It collects and analyzes fracture breakdown pressures observed in unconventional gas wells. Various geomechanical aspects that influence breakdown pressure are investigated and compared with the actual breakdown pressures observed.
Towards a Robust Estimation of Permeability by Integrating Logging Data from Nuclear Magnetic Resonance, Acoustic, and Formation Tester
Authors: Thern Holger , Hinze Iris , Mohnke Oliver , Salazar Jesus , Kriegshaeuser Berthold 
Published: September 2016

Abstract
Permeability is critical for determining the producibility of hydrocarbon reservoirs. Permeability, however, cannot be measured directly by logging tools, but rather needs to be deduced from available logging data. We present a method to derive a continuous permeability profile from nuclear magnetic resonance (NMR) and acoustic (AC) logging data by incorporating formation tester (FT) mobility. The underlying theory and workflow are described and field data examples that validate the approach are discussed.
NMR permeability models combine porosity and an average pore size estimated from relaxation time measurements. Stoneley waves from acoustic logging deliver a permeability log by capturing the fluid particle motion between the borehole and the near borehole formation. Formation tester tools measure multiple formation properties including mobility, which is converted to permeability by multiplication with fluid viscosity. While NMR and AC data deliver a continuous, but uncalibrated permeability profile, FT mobilities are only taken at discrete depths with potentially large spacing.
We have developed a robust workflow to generate a continuous and calibrated permeability log from NMR and acoustic data, by incorporating formation tester mobilities. The workflow can incorporate wireline and logging while drilling (LWD) data and can be applied to clastics and carbonate reservoirs. In particular, carbonates can exhibit complex pore geometries due to diagenetic alteration that can make permeability assessment difficult. Permeability in clastic formations, on the other hand, can be affected by the presence of clays or by cementation. We have observed that incorporating formation tester data can contribute significantly to deliver a calibrated, continuous permeability profile from NMR and Stoneley waves.
We demonstrate the efficiency of our methodology by applying it to three field data examples from offshore carbonate formations. These examples demonstrate the value of integrating formation test mobility with NMR and, if available, acoustic permeability, to improve the petrophysical characterization of reservoirs. Advantages and limitations of the combination of all three measurement types are illustrated, and applications, such as the identification of pore geometry effects, are discussed.
The Importance of Implementing Petropysically Meaningful 3D Anisotropic Velocity Models to Improve the Interpretative Value of Microseismic Data
Authors: Taylor Scott , King Jeremy , Schaeffer Ben , McGreaham Lucas , Ghuneim Khaled , Hibbitts Todd 
Published: September 2016

Summary
The issue of how much seismic rock properties change during a frac is not well understood. For years, most downhole microseismic monitoring operators have changed their velocity models for each stage. With advances in velocity analysis technology, this practice is under increasing scrutiny. The authors present a study of a West Texas microseismic dataset, in which varying levels of anisotropy are measured through tomography. Results demonstrate that higher orders of anisotropy have not only increased accuracy and aided in the development of a geologically relevant velocity volume, but also enhanced the interpretative value of the microseismic data. The 3D time-invariant model demonstrates more viable event locations and agreement with sonic log and borehole seismic (VSP) data. Furthermore, meaningful rock property estimates can be extracted from perforation data which not only adds credibility to the time invariant modelling approach but also adds significant information value."
The authors seek to extract more value from microseismic in order to make this measurement viable both in the current price environment and across a broader spectrum of wells. This is the first in a series of papers that will walk through the premise, basic steps and benefits to honoring an increasingly more sophisticated level of physics when building velocity models.