bluuebunny/crossref_metadata_2025_split huggingface dataset:
Temperature Transient Analysis of Slightly Compressible, Single-Phase Reservoirs
Authors: Onur Mustafa , Çinar Murat 
Published: April 2016

Abstract
This paper presents new semilog-straight line and temperature-derivative methods (similar to pressure-derivative method commonly used in pressure transient analysis) for interpreting and analyzing temperature transient data from constant-rate drawdown and buildup tests conducted in infinite-acting reservoirs containing slightly compressible fluid of constant compressibility and viscosity. The procedures are based on the analytical solutions accounting for Joule-Thomson (J-T) heating/cooling, adiabatic fluid expansion, conduction and convection effects. The development of the analytical solutions is based on the fact that the effects of temperature changes on pressure transient data can be neglected so that the pressure diffusivity and thermal energy balance equations can be decoupled. The analytical solutions are verified by and are found in excellent agreement with the solutions of a commercial non-isothermal reservoir simulator. It is shown that drawdown and buildup sandface temperature data may exhibit three infinite-acting radial flow (IARF) periods (represented by semilog equations); one at early times reflecting the adiabatic expansion/compression effects, second at intermediate times reflecting the J-T expansion in the skin zone if skin exists, and the third one at late times reflecting J-T expansion effects in the nonskin zone. Performing semilog analyses based on these IARF regimes gives estimates of permeability of skin and nonskin zones as well as radius of the skin zone assuming that the J-T coefficient of the fluid and viscosity is known. Parameters such as skin zone permeability and radius are not readily accessible from conventional pressure transient analysis from which only the skin factor and non-skin zone permeability can be obtained. The applicability of the proposed analysis procedure is demonstrated by considering synthetic and field test data. The results indicate that the analysis procedure provides reliable estimates of skin zone and non-skin zone permeabilities and skin zone radius from drawdown or buildup temperature data jointly with pressure data.
Utilization of Time-Lapse Seismic Data to Semi Quantify Residual Oil Saturation by Karhunen-Loeve Transform and Neural Artificial Network during CSS
Authors: Yang Sheng , Ji Dongqi , Gui Zhixian , Chen Zhangxin , Zhong Liguo 
Published: April 2016

Abstract
Due to the nature of Cyclic steam stimulation (CSS), a steam chamber generated by CSS is not as consistent and detectable as SAGD's (steam assisted gravity drainage) one, which makes it challenging to predict the residual oil distribution and steam-unswept zones. Time-lapse seismic are a valuable and important method to monitor steam injection and soaking. During CSS process, rock-fluid densities and velocities are changed significantly during steam injection and oil production. These changes make time-lapse seismic monitoring feasible. The previous approaches were mainly about fluid contact determination, steam chamber supervision and field history matching. In this study, a new method using time-lapse seismic attribute differences is developed to semi quantify residual oil saturation and determine steam-unswept zones during thermal recovery.
Twenty seismic attributes derived from time-lapse seismic data, which can sensitively reflect oil saturation changing, are selected as basic seismic attributes to quantify fluid saturation changes. The relationship between fluid properties and seismic attributes is complex and ambiguous. Only one seismic attribute difference between base data and monitored data is insufficient to reflect reservoir properties changes during thermal recovery process. In order to improve the accuracy of prediction, combinations of multiple seismic attributes differences are used to reflect rock-fluid properties changes such as oil saturation changes. The Karhunen-Loeve Transform is applied to squeeze twenty attributes into four new attributes by eliminating attributes correlation. Based on generated seismic attributes, the artificial neural network is implemented to illustrate the oil saturations changes, which is also constrained by the measured fluid reservoir data.
Four attribute differences are tested to demonstrate the oil saturation changes. The best result only can partially match field production data. However, the residual oil saturation distribution generated by the proposed method can match the majority features of the field production data. This approach provides a reliable and valuable way to help operators monitor a CSS process and design infill well drilling.
Experimental Validation of a Pore-Scale Derived Dimensionless Capillary Pressure Function for Imbibition Under Mixed-Wet Conditions
Authors: Zhou Y. , Helland J. O. , Hatzignatiou D. G. , Ahsan R. , Hiorth A. 
Published: April 2016

Abstract
In this work, we validate experimentally a dimensionless capillary pressure function for imbibition at mixed-wet conditionsthat we developed recently based on pore-scale modeling in rock images. The difference to Leverett's traditional J-function is that our dimensionless function accounts for wettability and initial water saturation after primary drainage through area-averaged, effective contact angles that depend on the wetting property and distribution of oil- and water-wet grain surfaces. We hypothesized that describing these effective contact angles as a function of Amott wettability index relates the pore- and core-scale wettability, and that pore-scale imbibition simulations can provide these relations for specific rocks. In the present work, we adopt the dimensionless function to scale imbibition capillary pressure data measured on mixed-wet sandstone and chalk cores. The measured data practically collapse to a unique curve when subjected to the dimensionless capillary pressure function. For each rock material, we employ the average, dimensionless curve to reproduce the measured capillary pressure curves and obtain excellent agreement. We also demonstrate two approaches to generate different capillary pressure curves at other mixed-wettability states than that available from the data used to generate the dimensionless curve. The first approach changes the shape of the spontaneous- and forced-imbibition segments of the capillary pressure curve while the saturation at zero capillary pressure is constant. The second approach shifts the vertical level of the entire capillary pressure curve, such that the Amott wetting index (and the saturation at zero capillary pressure) changes accordingly. Thus, integrating these two approaches with the dimensionless function yields increased flexibility to account for different mixed-wettability states. The validated dimensionless function scales mixed-wet capillary pressure curves from core samples accurately, which demonstrates its applicability to describe variations of wettability and permeability with capillary pressure in reservoir simulation models. This allows for improved utilization of core experiments in predicting reservoir performance. Reservoir simulation models can also employ the dimensionless function together with existing capillary pressure correlations.
Field Development Process Revealing Uncertainty Assessment Pitfalls
Authors: Morosov André Luís , Schiozer Denis José 
Published: April 2016

Abstract
The amount of information available for field development planning is limited, forcing the Production Strategy to be designed under great amounts of uncertainty. During its implementation, new information allows the adaptation of the strategy for economic gain. This work reproduces the field development process under geological uncertainty in case study UNISIM-I-D (benchmark case based on Namorado Field in Brazil). The main objectives are to evaluate the process and observe the evolution of risk curves, all in a controlled environment with real field features.
The methodology generates new geostatistical images based on new well logs, assimilates production data using an ensemble-based method and re-optimizes the production strategy using a hybrid algorithm. The field development is carried out by repeatedly applying this framework under human supervision. Each step is customized using algorithms to simplify the implementation and to reduce computational effort, making this methodology more appealing for practical use. New data are collected from a high-resolution reference model that does not belong to the ensemble of models. The process starts with a production strategy, previously optimized under the uncertainties of the case study, which yields the real economic outcome within the original uncertain range.
Results show high quality history matching that excessively reduced the risk range and the variability of the updated model sets. Optimizations on the production strategy, based on the updated ensembles, consistently increased the expected monetary value of the project without guaranteeing an increment in the real NPV. Applying the methodology repeatedly throughout the field development increased the EMV by 29% (from 1.532 to 1.975 billion USD) while the real NPV decreased 2% (from 1.346 to 1.319 billion USD), falling out of the expected range and revealing that the model sets did not fully represent the real field. The lack of good representation is aggravated by heterogeneities inherent to the unknown reservoir, which are difficult to identify using only well logs and production data.
The results from the application of a closed-loop reservoir development process in a controlled environment warn against similar hidden mechanisms happening on a real field development under similar circumstances. They reveal intrinsic pitfalls in reservoir modeling that may contribute to production forecast problems and call for a reflection on how reservoir uncertainty assessment is performed. We prove that large sets of models do not guarantee coverage of geologic uncertainties as the field development process naturally changes the risk curves.
Determining the Zeta Potential of Intact Shales via Electrophoresis
Authors: Hoxha B. B. , Sullivan G. , van Oort E. , Daigle H. , Schindler C. 
Published: April 2016

Abstract
The wettability of rocks is of fundamental importance to the understanding of fluid transport within hydrocarbon reservoirs. Wettability is intimately tied to the zeta potential, which is determined by the electrostatic forces among the rock's mineral constituents. Extensive prior research has been conducted into the relationship between wettability and surface forces of shale samples that have been ground up and/or otherwise been altered. However, very little attention has been given to measuring the zeta potential of the surface of unbroken, intact shale samples.
A new technique is explored in this paper that investigates the zeta potential of the actual surface of shale samples in one intact piece. The surface zeta potential of shales was found to be strongly determined by the mineral composition and the cation exchange capacity (CEC) of the shale. Shales containing higher amounts of silicates (e.g. quartz, feldspar, and clays such as Illite and Smectite) tended to be water-wet and exhibit higher negative zeta potential values. Shales that contained higher amounts of carbonates (dolomite, aragonite, calcite, etc.) were more oil-wet with zeta potential values that were less negative or slightly positive. Measurements were also performed on Berea and Boise sandstone in order to compare organic vs. inorganic samples. Results for common shales showed Mancos and Marcellus to be intermediate-wet, Oxford and Eagleford to be moderately oil-wet, and Arne to be highly water-wet. Additionally, the zeta potential was also studied in various ionic and nano-particle solutions.
Scalability and Performance Efficiency of History Matching Workflows using MCMC and Adjoint Techniques Applied to the Norne North Sea Reservoir Case Study
Authors: Schulze-Riegert Ralf , Nwakile Michael , Skripkin Sergey , Willen Yannick 
Published: April 2016

Abstract
An increasing number of field development projects include rigorous uncertainty quantification workflows based on parameterized subsurface uncertainties. Reservoir model calibration workflows for reservoir simulation models including historical production data, also called history matching, deliver non-unique solutions and remain technically challenging. In addition, the validation process of the reservoir simulation model often introduces a break of the conceptual connection to the geological model. This raises questions on how to quantify the deviation between the calibrated simulation model and the original geological model.
Workflow designs for history matching require scalable and efficient optimization techniques to address project needs. Derivative-free techniques like Markov Chain Monte Carlo (MCMC) are used for optimization and uncertainty quantification. Adjoint techniques derive analytical sensitivities directly from the flow equations. For history matching those sensitivities are efficiently used for property updates on grid block level. Both techniques have different characteristics and support alternative history matching strategies like global vs. local, stochastic vs. deterministic.
In this work both techniques will be applied in an integrated workflow design to the Norne field. The Norne field is a North Sea oil-and-gas reservoir with approximately 30 wells, with one third being used for WAG injection for pressure support. Field data was previously released by Statoil and made available for a public benchmark study (NTNU Norway) testing history matching techniques including production and time-lapsed seismic data.
We focus on well production data for history matching. MCMC is used for global parameter updates and uncertainty quantification in a Bayesian context. An implementation of an adjoint technique is applied for analytical sensitivity calculations and local parameter adjustments of rock properties. History matching results are presented for field wide and well-by-well production data. Consistency checks between updated and original geological model are presented for rock property distribution maps. Geostatistical measures including spatial correlations are used to quantify deviations between updated and original geological model. In conclusion scalability and performance efficiency of the practical workflow implementation is discussed with a perspective of a consistent feedback loop from history matching to geological modeling.
Multi-Scale Integration of 4D Seismic and Simulation Data to Improve Saturation Estimations
Authors: Correia Gil Gomes , Davolio Alessandra , Schiozer Denis José 
Published: April 2016

Abstract
Some difficulties are frequently associated with the integration of seismic and flow simulation datasets, especially related with the low vertical resolution of the seismic data and the uncertain estimations in the areas between the wells. One challenge is then the integration of both datasets in different scales, in order to take advantage of their characteristics. The present study proposes a redistribution of the reservoir saturation estimated with 4D seismic inversion methods, combining the information provided by the flow simulation in order to improve the quality of the estimations and their resolution.
The methodology comprehends a saturation redistribution algorithm that is applied to each reservoir block combining the information of two saturation maps: one derived from the 4D seismic data and the other estimated by the flow simulator. The final saturation estimation follows the vertical distribution given by the simulation data but keep the average behavior observed in the 4D seismic. In order to have a better control of the results, the methodology is applied to a synthetic dataset that includes a reservoir model with different grid resolutions: geomodel, simulation model and seismic model.
Two different case studies present the main results of the proposed methodology to improve the saturation predictions. The first case study represents an ideal solution being assumed that the base model (simulation model) is very similar to the reference model (geomodel that represents the true answer), remaining a few differences due to the different scales. In the second case study, the base model is selected between multiple realizations during the uncertainty reduction process. The results shows that is possible to improve the resolution of the saturation variation maps computed from 4D seismic data allowing the identification of new fine scale heterogeneities and providing better estimations of the saturation changes due to production. This methodology can also give additional clues in future history matching procedures through the identification of critical regions. With the continuous calibration of the models during a history matching process the results obtained with the redistribution method tend to improve, approaching the results obtained in the first case study.
The proposed redistribution method combines the best characteristics of the seismic and simulation data. It includes the higher sensibility of the seismic data to identify the areal distribution of the main anomalies and inserts the higher sensibility of the simulation data regarding the identification of vertical water flow trends due to gravitational effects. Thus, the procedure introduces, in the maps provided by 4D seismic, new information regarding the injection/production patterns that become more and more reliable as we approach the wells.
New Approaches of Using Fluid Level Data for Production Optimization and Reservoir Engineering Applications
Authors: Burgstaller C. 
Published: April 2016

Abstract
A new technology for fully automated fluid level measurements was developed during the past seven years. The paper describes the technical features of the new device and summarizes via case studies new approaches of using fluid level data for optimizing artificial lift systems and for reservoir engineering applications (well testing).
The unique feature of this system is its fully automated and purely electronic functioning. The measuring device is mounted on the casing outlet and, contrary to conventional devices, works without the need of a gas gun. It has a sampling rate of one measurement per minute. The measured fluid level data is transmitted from each wellsite to the operations center via standard communication systems. The fluid level data can be used as an input signal to a VSD (Variable Speed Drive) controller for automatic pump regulation, thereby enabling operators to run downhole pumps in a safer and more efficient way. The new device has successfully been used to avoid pump-off conditions and the resulting serious equipment damage of artificial lift systems. Due to the availability of online fluid level data, downhole pumps (ESPs and Sucker Rod Pumps) could be operated safely at more aggressive production rates.
The device can also be used to control a VSD to keep the fluid level in a well at a specific depth to avoid downhole flow conditions below the bubble point pressure in oil wells. This application has been used on several oil production wells to avoid the generation of free gas within the reservoir, which would decrease the relative oil permeability and could also have a negative impact on the ultimate recovery of a reservoir.
Furthermore, a transient multi-phase flow model has been developed which has successfully been applied to derive bottomhole flowing and build-up pressure for production performance monitoring and well testing applications from the continuously available fluid level data. Comparisons with pressure data from downhole gauges show a very good agreement.
The new approach of obtaining bottomhole flowing and build-up pressure data from continuous fluid level measurements has proven to be a valuable method to optimize operations of artificially lifted wells and to obtain valuable data for reservoir monitoring in a cost-effective way.
DAS/DTS/DSS/DPS/DxS - Do We Measure What Adds Value?
Authors: Gohari Kousha , Jutila Heikki , Kshirsagar Atul , Chattopadhyay Arijit , Mascagnini Carlos , Gryaznov Andrey , Kidd Peter , Zarei Faraj 
Published: April 2016

Abstract
Inwell measurement of rates and ratios do not allow operators to proactively control flow into the well. For intelligent fields there is a growing need for tools that enable engineers to ‘see’ further into the reservoir in order to adjust and/or change the flow control strategy as required. From a reservoir management perspective the most value can be achieved when implementing intelligent flow control systems coupled with surveillance tools. Hence, this study presents a way of defining a fit for purpose surveillance strategy that can be coupled with active flow control systems that facilitates the optimisation of the recovery efficiency.
A dynamic simulator was used to analyse and determine a monitoring strategy that provides the most cost effective method of understanding various phenomena occurring within the reservoir, such as water/gas encroachment. The intention of the study was to determine if the data set currently obtained is sufficient enough to provide a deep understanding of the reservoir. The dynamic simulator modelled the temperature, saturation and pressure changes and the post-processer was used to derive corresponding changes in resistivity and acoustic properties. The change in temperature was important to model in order to study the parameter for its surveillance value as well as to capture thermal effects on reservoir fluid properties and geomechanical properties. The electro-magnetic and acoustic properties were calculated using a well-known formulae; resistivity was derived by inverting the Archie equation.
Results from the study were used to specify what the surveillance tools should measure and what detection distance would allow operators to proactively adjust the flow control devices/valves in order to maximise the value of the development. Sensitivity and optimisation analysis was conducted to obtain the distance of investigation required by the surveillance. The study demonstrated that a simple 1-way coupling gives representative estimations of electro-magnetic and acoustic properties over field production time. This will be able to assist in determining which methods of surveillance can be used over the life of the field assisting in recommending a suitable data acquisition strategy to extract maximum value from the tools available; DAS/DTS/DSS/DPS/DxS, EM, seismic and other methods.
Simple 1-way coupling is often enough to estimate the change with suitable accuracy to assess feasibility of various surveillance techniques. DAS could have an application in continuous cross-well tomography to follow the flood front; this subject is to be studied further.