bluuebunny/crossref_metadata_2025_split huggingface dataset:
Methodology to Assimilate Multi-Objective Data Probabilistically Applied to an Offshore Field in the Campos Basin, Brazil
Authors: Gomes Carlos Eduardo , Maschio Celio , Paes Vinicius Costa , Correia Manuel Gomes , Câmara Paulo Sérgio , Santos Antonio Alberto , Schiozer Denis José , Silva Marcia Ida , Dos Santos Marcos Sebastião , Anyzewski Alessandra Silva 
Published: April 2018

Abstract
This work applies a new methodology to assimilate multi-objective data (production, injection and, pressure of all wells) based on five of the twelve steps described by Schiozer et al. (2015) using reservoir simulation and uncertainty reduction for a brown offshore field in the Campos Basin, Brazil. We use probabilistic techniques to assimilate all data simultaneously, improving the performance of the process. The 12-step methodology by Schiozer et al. is based on a closed-loop reservoir development and management process. Steps 1 and 2 construct the model under uncertainties and select the numerical model. Steps 3 to 5 assimilate history data in an iterative process proposed by Maschio and Schiozer (2016). At each iteration, a set of best-matched models is selected to update the probability distributions of the reservoir properties (parameters) based on a correlation matrix. Steps 6 to 12, comprising the decision analysis, were not included in this work. The results reflect a practical application of the methodology, considering a real reservoir with two zones and complex behavior that was captured during reservoir characterization using an uncertainty reduction algorithm. The reservoir was characterized through the probabilistic combination of uncertain variables, based on well logs and seismic data. The probabilistic characterization highlighted the geological variability under uncertainty. A set of three hundred geological realizations with associated porosity, net-to-gross ratio, and permeability distributions was generated for further combination with uncertain dynamic parameters. The method DLHG (Discretized Latin Hypercube combined with Geostatistics) was used during the entire process to build approximately 1000 uncertain scenarios allowing the review of reservoir parameters in any iteration. The data assimilation process was used to update the probability density function for each parameter according to the data match indicators. We significantly reduced the uncertainty and improved production forecast reliability. This paper integrated different areas including reservoir characterization, reservoir simulation and history matching with the associated uncertainty reduction. The methodology was successfully applied in a practical case with several uncertainties, indicating good potential for application in other fields. The matching quality was better than in previous approaches.
Model Selection for Error Generalization in History Matching
Authors: Nezhad Karim Nobakht Behzad , Christie Mike , Demyanov Vasily 
Published: April 2018

Abstract
In order to better understand reservoir behavior, reservoir engineers make sure that the model fits the data appropriately. The question of how well a model fits the data is described by a match quality function carrying assumptions about data. From a statistical perspective, improper assumptions about the underlying model may lead to misleading belief about the future response of reservoir models. For instance, a simple linear regression model may have a fair fit to available data, yet fail to predict well. On the contrary, a model may perfectly match the data but make poor prediction (i.e. overfitting). In both cases, the regression model mean response will be far from the true response of the reservoir variables and will cause poor decision making. Therefore, a suitable model has to provide balance between the goodness of the fitted model and the model complexity.
In the model selection problem, realistic assumptions concerning the details of model specification are the key elements in learning from data. With regard to conventional history match scheme, the data fitting is usually performed by linear least-squares regression model (LSQ) which makes simple, yet often unrealistic, assumptions about the discrepancy between the model output and the measured values. The linear LSQ model ignores any likely correlation structure in discrepancy, changes in mean and pattern similarities reflecting on poor prediction.
In this work, we interpret the model selection problem in data-driven settings that enables us to first interpolate the error in history period, and second propagate it towards unseen data (i.e. error generalization). The error models constructed by inferring parameters of selected models can predict the response variable (e.g. oil rate) at any point in input space (e.g. time) with corresponding generalization uncertainty. These models are inferred through training/validation data set and further compared in terms of average generalization error on test set.
Our results demonstrate how incorporating different correlation structures of errors improves predictive performance of the model for the deterministic aspect of the reservoir modelling. In addition, our findings based on different inference of selected error models highlight an enormous failure in prediction by improper models.
Study of the Feasibility of the Carbon Dioxide Injection in a North Sea Petroleum Reservoir
Authors: Al-Masri Wael , Papaspyrou Christos , Shapiro Alexander , Suicmez Vural 
Published: April 2018

Abstract
Carbon dioxide injection has recently been considered as a promising method for enhanced oil recovery. The supercritical carbon dioxide is often miscible or nearly miscible with the oil under reservoir conditions, which facilitates high recovery. Underground injection of carbon dioxide is also of a significant ecological advantage, and utilization of CO2 results in a noticeable reduction of the taxation of the petroleum companies. On the other hand, application of carbon dioxide under conditions of the North Sea petroleum reservoirs for enhanced oil recovery (EOR) is hindered by multiple practical problems: availability of the CO2 sources, logistics of the delivery offshore, corrosion resistivity of the installations, and other. Previous studies of CO2 EOR for the reservoirs of the North Sea region, including core-flooding experiments and reservoir simulations, indicate that the deployment of CO2-EOR can significantly enhance the recovery of hydrocarbons. However, CO2 must be generated from anthropogenic sources, which affects the feasibility of the projects.
The current study evaluates the potential of a CO2-EOR project under the conditions of a specific petroleum reservoir of the Danish sector North Sea. Geological characteristics of the reservoir and the detailed oil properties lie in the ground of the study. The minimum miscibility pressures between CO2 and the reservoir oil are evaluated with the help of the in-house software (SPECS 5.70) and the commercial reservoir simulator (ECLIPSE 300). The results are verified in the slimtube simulations. The effect of the different oil characterizations and its lumping into the different numbers of components is investigated. The oil is found to be miscible with the carbon dioxide under reservoir conditions.
Several injection scenarios have been tested on the 2-D and 3-D reservoir models. Waterflooding was compared to injection of carbon dioxide, as well as water-alternate gas injection. An optimal scenario with regard to water-gas ratio under WAG was selected for further studies.
Finally, a cash flow model by Monte Carlo simulations and a sensitivity analysis on the impact of oil and CO2 price and discount rate, certify the feasibility and attractiveness of a CO2-EOR project in the West Flank of the Dan field.
Combining Multiple Fracturing Diagnostic Tests is an Effective Substitute for Production Logs in Unconventional Horizontal Wells
Authors: Crawford Elspeth 
Published: April 2018

Abstract
Utilizing fracture diagnostic tests during each stage in a horizontal — the Pump-In Leakoff Factor (PILF), the Instantaneous Shut In Pressure (ISIP) leakoff calcutaions, and the change (delta) of both in a pre-proppant step down test, and a post fracture step down test — a correlation of "effective stimulation" and "effective production" can be achieved. PILF is intended to be used as a relative indicator of the stage's capacity to dissipate hydraulic fracturing energy. It can also be used to visualize the connectivity and size of a fracture network. A general leakoff trend that can also be used to evaluate the fracture's ability to support the connected flow — i.e., the general concept of "propped." Taking these calculations results, and comparing them with a production log, an idea of applying the calculations to simulate production response, without having to run secondary production logs is proposed. When the deltas and the spread over the lateral are overlaid, and compare to the production log, the best deltas correspond to the best response on the log. This was done for multiple wells, and five have been pulled to review in this paper. This paper will describe the process, and results, with the end goal of having an effective substitute to calculate the contributions of a stage without running a production log.
Molar Distributions of Equilibrium Systems
Authors: Alqahtani Fahd Mohamad , Whitson Curtis Hays 
Published: April 2018

Abstract
This paper deals with the observation that in most equilibrium systems of petroleum mixtures, the molar distribution shape of heavier fractions such as C7+ are very similar. This observation is verified for a wide range of equilibrium pressure-temperature conditions for a wide range of petroleum reservoir mixtures. The states of equilibrium studied include saturation pressure, two-phase flash within the phase envelope, and isothermal systems under the influence of gravitational segregation. The gamma distribution model is used to quantify molar distribution. The gamma distribution parameter a defines the distribution shape which provides a quantitative measure of similarity between equilibrium phases.
The Hoffman, Crump and Hocott(1953) source of reservoir fluids for a saturated gas-oil system (containing only hydrocarbons) has been used in this study. The SRK EOS with zero binary interaction coefficients is used as the thermodynamic model to describe phase behavior of the Hoffman et al fluid system.
A number of applications are given related to the similarity of equilibrium phase molar distributions.
A Consistent Method to Build and Use a 3D Mechanical Earth Model
Authors: Cuesta Bertrand , Vorobiev Sergey 
Published: April 2018

Abstract
The document presents a consistent method to build 3D Mechanical Earth Models (3D MEM). It is based on a rock physics study to derive field specific correlations between mechanical properties and interpreted petrophysical quantities. The 3D MEMs built using this methodology yield robustness and consistency when matching to the measured minimum stress. They also display good predictive capabilities making them valuable for operational design.
This method consists of conducting a preliminary rock physics study in order to obtain correlations between the mechanical properties (elastic moduli and strength), of the various formations that are considered, and basic interpreted quantities which are readily available in most 3D geological models (porosity or mineralogy). The correlations are used to build a 3D MEM which is consistent with both the 3D geological model and the 1D geomechanical interpretation. It is also possible to extend the correlations by linking raw log data to rock mechanical properties.
The model was tested against field case study to verify its predictiveness. Minimum stresses calculated by the 3D MEM matched well to the measured values obtained from mini-frac tests performed at various locations. Ultimately it permits to better forecast the material properties (in 3D) as well as the effective stress tensor (in 4D). The 3D MEMs were used to evaluate the risks for infill drilling, and for completion purposes. Performing this type of preliminary rock physics study has a number of benefits. Firstly, to help identify which logging suite should be run to characterize the geomechanical properties of a given formation, and secondly it can be used to derive correlations between raw log data and geomechanical properties. These correlations can be applied during operations for real time decision making purposes when there is not yet a petrophysical interpretation available.
The novelty of the method introduced lies in the systematic and coherent integration of data to build a consistent geomechanical model (3D or 1D), that exhibits a robust predictive capability and shows the value of 3D MEM for the design of drilling and completion operations.
Offshore Exploratory Drilling Campaigns During Oil Price Downturns: Maximizing Value Creation from Flexibility
Authors: Cardenas Camilo , Bratvold Reidar , Jafarizadeh Babak 
Published: April 2018

Abstract
During oil price downturns, many operating companies reduce or eliminate large investments with long time horizons such as exploratory drilling campaigns. This reduction in investments induces rig and drilling services providers to decrease their bids to remain competitive. Consequently, the exploration expense is decreased, lessening the initial expenditure in the project. In this research, a valuation approach is implemented to study the impact of this investment reduction on the decision-making process for executing exploratory drilling campaigns during oil price downturns. It is shown that postponing exploration campaigns during oil downturns does not necessary maximize value creation.
Value creation from investment in oil price downturns results from the combination of uncertainty and flexibility. Value of flexibility (optionality), also referred to as Real Options value, can be estimated using a variety of methods. In this work, we use the versatile Least-Square Monte Carlo Method (LSM) approach developed by Longstaff and Schwartz (2001) to evaluate the waiting option for exploration drilling. Uncertainties in oil prices and drilling costs are included as they have the largest impact on the alternative chosen and the value achieved. We implement a two-factor stochastic oil price process developed by Schwartz and Smith (2000), as this model provides a good balance between realism and ease of communication. Uncertainty in the drilling costs is modeled as a Geometric Brownian Motion process. We also account for dependencies between oil price and costs by correlating the drilling cost with the previous period's oil prices.
We show that the real option methodology will identify the optimal time to start exploration drilling. We also demonstrate the effect of correlation between the drilling cost and the oil price on the optimal time to drill; which for this study is the year with lowest expected oil price. Furthermore, we analyze the sensitivity of project value with respect to the correlation factor and the parameters in the stochastic price model. This work demonstrates that including price-cost uncertainties and correlations leads to more realistic value estimates, resulting in investment decisions that maximize value.
This paper contributes to the practice of petroleum project analysis by showing the effect of correlations on the optimal time of drilling and the value of waiting options, demonstrating that it could be optimal to drill exploration wells during oil price downturns. The real option model developed in this paper is applicable to many types of exploration projects in the petroleum industry.
Performance Prediction for Dynamic Autonomous Flow Control Valves
Authors: Sørheim Ivar Leander , Askvik Stian Morken , Asheim Harald Arne 
Published: April 2018

Abstract
Flow forces controls this valve by moving a plate to adjust the opening. Viscous oil tends to open the valve, while less viscous water and gas make it choke. It also chokes at high flow rates. Such features are useful for inflow control along horizontal well. It may also have wider applications.
Pressure drops were measured across a test valve, for different flow rates and fluids. Measurements were compared to an analytic solution, relating performance to fluid properties, valve geometry and dimensions.
For water and oil, the measurements generally confirmed the analytic solution, but also revealed certain deviations. Measured performance with air showed phenomena not properly predicted by the analytic solution, which does not include compressibility
Published data for a commercial flow control valve of similar geometry indicate poorer performance than for the current experimental valve. Since the construction and dimension of the commercial valve are kept under cover, reasons becomes speculative
A New Approach to Polymer Flooding: Impact of the Early Polymer Injection and Wettability on Final Oil Recovery
Authors: Juarez-Morejon J. L. , Bertin H. , Omari A. , Hamon G. , Cottin C. , Morel D. , Romero C. , Bourdarot G. 
Published: April 2018

Abstract
An experimental study of polymer flooding is here presented focusing on the influence of initial core wettability and flood maturity (volume of water injected before polymer injection) on final oil recovery. Experiments were carried out using homogeneous Bentheimer sandstones of similar properties. The cores were oil flooded using mineral oil for water wet conditions, and with crude oil (after an ageing period) for intermediate wet conditions keeping constant in all experiments the viscosity ratio between oil and polymer solution. Polymer, which is a partially hydrolysed polyacrylamide (HPAM) was used at a concentration of 2500ppm in a moderate salinity brine. The polymer solution was injected in the core at different maturity times (0PV, Breakthrough, 1PV, 1.75PV, 2.5PV, 4PV and 6.5PV).
Coreflood results show that the maturity of polymer injection plays an important role on final oil recovery regardless wettability. The 0PV maturity (secondary polymer flooding) leads to the best sweep efficiency while final oil production decreases when the polymer flood maturity is high (late polymer injection after waterflooding). A difference of 15% in recovery is observed between secondary polymer flooding and late maturity (6.5 PV). Concerning the effect of wettability, the recovery factor obtained with water wet cores is always lower (from 10% to 20% depending on maturity) than the values obtained with intermediate wet cores, raising the importance of correctly restoring core wettability to obtain representative values of polymer incremental recovery. The influence of wettability can be explained by the oil phase distribution at the pore scale. Considering that the waterflooding period leads to different values of the oil saturation at which polymer flooding starts, we measured the core dispersivity using a tracer method at different states. The two-phase dispersivity decreases when water saturation increases which is favourable for polymer sweep.
This study shows that in addition to wettability, maturity of polymer flooding plays a dominant role in oil displacement efficiency. Final recovery is correlated to the dispersion value at which polymer flooding starts. The highest oil recovery is obtained when the polymer is injected early.
Economic Appraisal of Shale Gas Reservoirs
Authors: Kenomore Michael , Hassan Mohamed , Dhakal Hom , Shah Amjad 
Published: April 2018

Abstract
Natural gas produced from shale formations has increased rapidly in the past decade altering the oil and gas industry markets remarkably. The use of horizontal drilling and hydraulic fracturing has allowed previously unrecoverable shale gas to be extracted. Shale gas development is more expensive compared to conventional developments and as such, understanding the economic feasibility is of greater importance in successfully developing the resource. Using the estimated ultimate recoverable expressed in terms of P10, P50, and P90 from 2751 horizontal well production data (all starting production from 2008) from the Barnett shale, a discounted cash flow economic model (MS- Excel based) was used to quantify the effect of finding and development costs (F&DC) and gas prices on the economic viability of horizontal wells within four out of five basins (Strawn Basin, Ouachita Folded Belt, Forth-worth Syncline and Bendarch Basin) in the Barnett shale. The investment hurdle in the economic model was a rate of return of 20% and a payback period of 5 years or less. This paper helps determine the percentage of wells within basins in the Barnett shale that would be economically viable at various F&DC and gas prices subject to satisfying the prescribed investment hurdle.
Propagation to Reservoir Simulation of Uncertainty Associated with Three-Phase Relative Permeability Models with Hysteresis
Authors: Ranaee Ehsan , Inzoli Fabio , Riva Monica , Cominelli Alberto , Guadagnini Alberto 
Published: April 2018

Abstract
We study the way uncertainty associated with estimates of parameters of three-phase relative permeability models, including hysteresis, propagates to responses of reservoir simulations under Water Alternating Gas (WAG) conditions. We model three-phase relative permeabilities by: (i) joint calibration (on three-phase data) of a recent oil relative permeability model (Ranaee et al., 2015) and of the Larsen and Skauge (1998) gas relative permeability hysteretic model; and (ii) the common practice of relying on three-phase oil relative permeability models that are characterized solely on the basis of two-phase information (e.g., Stone, 1970 and Baker, 1988) in conjunction with the formulation of Larsen and Skauge (1998) for three-phase gas relative permeability. While model parameters associated with the former approach are linked to an estimation uncertainty, those of the models relying only on two-phase data are not. A numerical Monte Carlo (MC) framework is employed to estimate propagation to reservoir simulation outputs of uncertainty of parameters estimated through model calibration on three-phase data. Our findings suggest that evaluation of oil relative permeability through a saturation- weighted interpolation Baker model, even in combination with a three-phase gas relative permeability hysteresis model, yields the lowest values of field oil recovery. These are seen to lie outside uncertainty bounds evaluated via the above mentioned MC-based analysis. Relying on the Stone formulations together with the Larsen and Skauge (1998) gas relative permeability model yields (a) values of ultimate field oil recovery comprised within MC uncertainty bound and (b) values of field gas-oil ratio (GOR) which are smaller than those obtained through the Baker model in conjunction with the Larsen and Skauge (1998) formulation, both results falling markedly outside the MC-based confidence interval. Our results document the effect that propagation of uncertainties from calibrating three-phase relative permeability model parameters can have on field-scale simulation outputs, such as ultimate oil recovery and field GOR. They also serve as a baseline against which simulation results based on typical procedures to model three-phase relative permeabilities can be assessed.