bluuebunny/crossref_metadata_2025_split huggingface dataset:
Combining Geostatistics With Bayesian Updating to Continually Optimize Drilling Strategy in Shale Gas Plays
Authors: Willigers B. J. , Begg S. , Bratvold R. B. 
Published: June 2013

Abstract
We present a new methodology for improving the economic returns of shale gas plays. The development of an economically efficient drilling programme in such plays is a challenging task, requiring a large number of wells. Even after a relatively large number of wells have been drilled, the average well production and the variation of well performance (economics) remains highly uncertain. The ability to delineate a shale play with the fewest number of wells and to focus drilling in the most productive areas is an important driver of commercial success.
The importance of probabilistic modelling in managing uncertainty in shale gas plays has been explicitly emphasised in a number of studies. The objective of this study is to develop a practical valuation methodology that addresses these complexities and is dynamic, in the sense that the optimal drilling strategy can be continually updated as we learn the outcome of each well drilled.
Maximizing the returns from a shale gas play is essentially a problem of choosing well locations and numbers to optimize production volumes & rates. Drilling policies have to take account of a large number of already-drilled locations, possible new drilling locations, spatial dependencies between performance at those different (possible) well locations and the extent of uncertainty as to whether or not a well will be economic. These factors cause typical valuation methodologies to be impractical due to the "curse of dimensionality".
In this study an unconventional play is divided into cells. In each cell a fixed number of wells can be drilled. The chance of success (of a well having an NPV greater than zero) in any given cell is itself considered to be an uncertain variable. An initial probability distribution for the chance of success of each cell is derived from analogous plays plus any available information about the specific play.
The methodology proceeds as follows. First, as each new well (or group of new wells) is drilled, the outcome is used in combination with the prior probability distribution (using Bayes Theorem) to create an updated probability distribution for the chance of success of the relevant grid cell. Thus, our initial estimate can be continuously updated as we get more and more actual outcomes. Second, the influence of the new chance of success on the surrounding cells, due to spatial correlation, is updated using indicator kriging, a geostatistical technique.
The methodology proposed in this study informs the development of drilling policies for shale gas opportunities by using a probabilistic model that accounts for the uncertainty in the chance of success and its spatial dependency. The use of cells to represent a set of wells simplifies the analysis and greatly reduces the computing requirements. The methodology has been applied to a well set from the Barnett Shale, Texas, United States of America.
Sustainability versus Sustainable Development: The Case of Shale Gas
Authors: Shields Deborah , Verga Francesca , Blengini Gian Andrea 
Published: June 2013

Abstract
There is an ongoing dialogue in society about the place of energy resources in sustainability. One aspect of that discussion focuses on resource sustainability, the ability of governments and industry to ensure continued supply of needed resources. A related topic centers on the economic benefits and costs of fossil fuel production. Concerns about negative impacts on environmental social sustainability drive other parts of this conversation, and often lead to opposition to fossil fuel production and use. This paper uses the example of shale gas to argue that concentration on single sustainability aspects is inappropriate. Rather, development and production of these resources needs to be considered in the context of sustainable development, which necessitates integrating environmental and development strategies so as to satisfy current and future human needs. Integrated Sustainability Assessment (ISA) is proposed as a way to analyse the net contributions of a shale gas play to economic, environmental, social and resource sustainability. The latter topic is considered and variables that could be used in an ISA are proposed. Understanding, quantifying and communicating the nature and magnitude of the net contribution of shale gas to society will be a challenging, but essential, task in the process of responding to opposition in an open and constructive manner, one which ISAs can support.
How to integrate basin-scale information into reservoir models
Authors: Quinto Sacchi , di Torino Politecnico , Jan Weltje Gert 
Published: June 2013

Abstract
Objectives and scope of the Study In this paper a new approach is presented to consistently integrate basin-scale information into reservoir models. The impact of the quantitative integration of boundary conditions derived from basin-scale modeling on the facies distribution at the reservoir scale is evaluated. To this purpose, a new workflow was defined based on a geostatistical approach. The aim was that of integrating the typical dataset for reservoir geological modeling, comprising well and seismic data, with a potentially new kind of data obtained from 3-D process-based stratigraphic modeling and related to the distribution of the hydrocarbon bearing volumes. Quantitative coherence between the small scale reservoir volume and the large-scale geological setting defined by the basin model was imposed. Synthetic case studies were set up to verify the effectiveness of the method.
Applications The entire process was applied to a fluvio-deltaic environment to integrate the basin-derived information, such as (1) the overall reservoir/non reservoir volumes, (2) the 3D distribution of channelized volumes and (3) related flow directions, to the reservoir model. Eventually, the uncertainty reduction in the description of the final facies distribution at the reservoir scale was evaluated.
Results, Observations and Conclusions The developed approach proved very efficient to estimate the lithological fraction of the hydrocarbon bearing rocks (i.e. sands in a shaley/clayey environment). The lithological fraction is of crucial importance during the appraisal phase of a reservoir when relevant decisions have to be taken but few wells are drilled and, as a consequence, a limited amount of data is available to perform a reliable volumetric estimate. Furthermore, the prediction of the 3D facies architecture (such as the channel pattern in a fluvial depositional environment) can effectively assist in the well planning strategy. Besides, the overall uncertainty affecting a reservoir model can be assessed; this uncertainty is both a function of the initial environmental parameters for basin modeling and of the adopted methodological approach for basin-to-reservoir data integration. Therefore, an accurate inference of the basin parameters is needed to achieve a reliable prediction of both the channel location and the sand/shales volumes fractions.
Significance of subject matter Reservoir modeling can significantly benefit from the integration of quantitative basin-scale information. In particular, the numerical modeling of the stratigraphic sequence can be used to steer the reconstruction of the reservoir internal geometry and to reduce the uncertainty in the distribution of the hydrocarbon-bearing lithologies. Furthermore, this approach provides a rigorous assessment of the information content of all the available data and thus it might be very useful to guide further data acquisition campaigns.
Effect of DFN Upscaling on History Matching and Prediction of Naturally Fractured Reservoirs
Authors: Elfeel Mohamed Ahmed , Jamal Sarim , Enemanna Chukwuemeka , Arnold Dan , Geiger Sebastian 
Published: June 2013

Abstract
Naturally Fractured Reservoirs (NFR) hold a significant fraction of remaining petroleum reserves. Recovery factors from NFR are usually less than in conventional reservoirs due to associated high uncertainty throughout the characterisation and modelling phases. This particularly includes the modelling and upscaling of the fracture domain using Discrete Fracture Networks (DFN).
Computer assisted history matching and prediction is becoming increasingly popular as they help finding multiple history-matched models and probabilistic forecasts. Therefore, the associated uncertainty can now be quantified in a limited time frame. However, the results of a history match are known to depend on initial reservoir properties, including fracture permeability and matrix shape factors. Geological uncertainty in these two factors is exacerbated by the DFN upscaling errors.
We show how DFN modelling can be used to increase geological prior knowledge and hence produce more geologically consistent models. To highlight DFN upscaling errors, we use a realistic dataset from an onshore fractured reservoir to show how the DFN upscaling error could propagate through to the history matching phase. We compare history matching of three models with different DFN upscaling processes.
Results from state-of-the-art assisted history matching and prediction were found to depend on the static properties and particularly the computation of effective fracture permeability during DFN upscaling. This upscaling error alone leads to very different reservoir models, despite the best history matched models being of comparable quality. Hence, this leads to more uncertainty in reservoir production forecast. The identification of DFN upscaling errors is therefore crucial for better uncertainty quantification in reservoir simulation of NFR.
A Numerical Model for Multi-Mechanism Flow in Shale Gas Reservoirs with Application to Laboratory Scale Testing
Authors: Swami Vivek , Settari A. (Tony) , Javadpour Farzam 
Published: June 2013

Abstract
Shale is a complex unconventional reservoir having a variety of storage and flow mechanisms coupled together. Contrary to conventional reservoirs where gas is stored only in the pore space as free gas; current numerical simulators assume gas is stored as free and adsorbed phase in shale. Recent advancement of visualization and measurement techniques has enabled us to look at shale more closely. Shale has been found to contain a well-developed nanopore network in the organic matter or kerogen. Correspondingly we believe that gas is stored via four storage mechanisms: gas in natural fractures, free gas in matrix pores, adsorbed gas and gas dissolved in kerogen bulk in the shales.
In this work we formulate a flow model for shale gas reservoirs including the physics at nano scale. The model incorporates the gas stored in micro-fractures, gas stored in nanopores, gas adsorbed on the pore walls and gas dissolved in kerogen bulk. This complex quad porosity system has coupled equations between three interconnected systems; between matrix and fracture set, between matrix and adsorbed gas and between matrix and kerogen bulk. Sets of governing equations were derived for the coupled systems and numerically solved to find gas production as a function of time. The model was validated against laboratory observed data for a shale canister test from a Canadian shale gas field. This laboratory scale model can be suitably up-scaled for field scale simulation of shale reservoirs.
Well-head Pressure Transient Analysis
Authors: Spyrou Charidimos E. , Nurafza Peyman R. , Gringarten Alain C. 
Published: June 2013

Abstract
Pressure Transient Analysis (PTA) of bottom-hole pressure data (BHP) is a well-established method for estimating reservoir flow parameters and identify well behaviour. Unfortunately, permanent recording of bottom-hole data is not always operationally possible, for example in the case of high pressure and high temperature (HP/HT) reservoirs. On the other hand, most wells are equipped with gauges at the well head which record well head pressure data (WHP) continuously. This paper investigates the feasibility of using WHP data for identifying well test behaviour. The objective is to assess the ability to derive key well and reservoir parameters from WHP data in the absence of BHP data, focusing primarily on the estimation of permeability and skin.
Three different actual reservoir fluid and wellbore conditions were studied: a water injector with a single phase fluid in the wellbore and a reasonably constant fluid density; a dry gas well, also with single phase in the wellbore but changing fluid density; and a gas condensate well with multiphase flow and varying density in the wellbore. In each case, both WHP and BHP data were available. These WHP and BHP data were analysed separately with conventional PTA methods in order to compare resulting permeabilities and skin factors. WHP data were then converted to BHP data, using methods available in the literature in the water and dry gas cases, and two different approaches developed in this work for the gas condensate case.
In the case of the water injector, analysis of both the original WHP data and the converted BHP data provides a good estimate of permeability while overestimating the skin factor. A correction can be applied to the WHP derived skin, to match the BHP skin value.
In the dry gas and gas condensate cases, WHP analysis overestimates both permeability and skin factor. In the dry gas case, the WHP derived permeability and skin can be corrected to yield the BHP values, whereas PTA on the converted BHP data does provide the correct permeability. Finally, in the gas condensate case, it is possible to obtain the correct permeability from converted BHP in the absence of phase redistribution, whereas the skin factor remains overestimated.
Use of Well Indicators in the Production Strategy Optimization Process
Authors: Botechia V. E. , Gaspar A. T. , Schiozer D. J. 
Published: June 2013

Abstract
The selection of an adequate strategy for oil production is a complex process due to the several parameters that must be taken into account: type, number and position of wells, production and injection capacities of platforms, which must be defined and optimized in order to achieve an exploitation strategy which provides the best possible economic return. Most works presented production strategy optimization methodologies based on production or Net Present Value (NPV). In general, well information is not used in the optimization processes. However, information on well behavior and performance is very important to improve the production strategy and to make the process more robust.
The aim of this paper is to present a comparative analysis of the use of different indicators in order to assist the selection/optimization of a production strategy based on well information, using numerical simulation and economic analysis. Changes in the configurations of the production system can be made according to the behavior of the wells and evaluation of the indicators aiming to maximize the NPV of the field. The development of the equations of the well indicators is shown and the methodology is applied to two different geological models: an offshore sandstone reservoir, representing a gas solution drive model and a carbonate reservoir with typical characteristics of the pre-salt areas of Brazil.
A Novel Approach to a Quantitative Estimate of Permeability from Resistivity Log Measurements
Authors: Viberti Dario , Cossa Alessandro , Galli Maria Teresa , Pirrone Marco , Salina Borello Eloisa , Serazio Cristina 
Published: June 2013

Abstract

Description of the material
In this paper a novel methodology for the estimation of the formation permeability, based on the integration of resistivity modeling and near wellbore modeling, is presented. Results obtained from the application to a real case is shown and discussed.
The well log interpretation process provides a reliable estimation of the main petrophysical parameters such as porosity, fluid saturations and shale content, but the formation permeability is traditionally obtained through laboratory tests on plugs, at the scale of centimeters, and through well test interpretation, at the scale of tens or hundreds of meters.
However, log measurements, and in particular resistivity logs, are strongly affected by the presence of the near wellbore zone invaded by mud filtrate. In turn, the extension of the invaded zone depends on formation properties and, in particular, on permeability.
As a consequence, the resistivity measured by the tools (the apparent resistivity) has to be properly corrected through a resistivity modeling process to obtain the true formation resistivity and the geometry and resistivity of the invaded zone.
Resistivity profiles within the invaded zone are function of fluid properties, petrophysical properties and rock-fluid interaction properties. The novelty of the approach is to numerically simulate the mud invasion phenomenon and match the resistivity profile provided by resistivity modeling to estimate the formation permeability. In the proposed methodology the match of the resistivity profile is obtained by integrating the near wellbore simulator with an optimization algorithm.

Application
This novel approach was applied to a heterogeneous shaly-sand oil-bearing reservoir in the Norwegian offshore area. The analyzed sequence was characterized by a high degree of variations in the layers’ thickness, from meters down to below tools’ vertical resolution. A complete set of wireline logs were acquired in the considered well; several cores were cut and routine and special core analyses performed.

Results, Observations, and Conclusions
First, a conventional petrophysical characterization was achieved and the appropriate resistivity corrections were calculated. Then, the modeled resistivity was used as the input for the optimization algorithm so as to obtain a continuous quantitative estimation of permeability in the entire logged interval. The results were satisfactorily compared to core measurements: in both thick, conventional layers and thinner beds the match was very accurate.

Significance of subject matter
The new approach provided a robust permeability estimate also in un-cored intervals and, more generally, can be used to predict permeability in un-cored and un-tested wells.
Local History Matching Using 4D Seismic Data and Multiple Models Combination
Authors: Davolio Alessandra , Maschio Célio , Schiozer Denis José 
Published: June 2013

Abstract
Nowadays there are several methodologies to incorporate quantitatively 4D seismic data in the history matching of reservoir simulation models. Most of them add a map attribute derived from 4D seismic, which can be impedance maps, saturations etc., in the objective function of the optimization process. In these cases, the goal is to match the dynamic information provided by 4D seismic with simulation response in the whole reservoir area, or the whole area covered by seismic data. In this work, it is proposed a history matching methodology that uses 4D seismic information locally for each injector (and the associated producers) individually, trying to match the water front movement related to each injector with the observed dynamic changes. In order to guarantee consistency with geology, the matching is done by combining static properties that comes from different simulation models. These models are generated through a combination of the most important uncertain parameters in an uncertainty analysis procedure, geologically consistent, that should be run previously. Then, the matching procedure is based on the computation of the water saturation errors at some sub-regions defined around the injector for multiple scenarios; the error is computed between water saturation derived from 4D seismic and each model simulation result. The models which presented the smallest error for each sub-region are selected and a new simulation model is built by combining the static properties extracted from the selected models at each sub-region. Before calculating the saturation errors the volume of water computed from 4D seismic is calibrated to the volume of injected water providing a more robust calibration. The methodology was applied to a synthetic case where porosity and permeability were the main uncertainties updated by the methodology proposed. Since these properties were generated through geostatistic realizations, the adjusted model kept the geological features. The promising results observed in the synthetic case showed that the methodology can be a good alternative for history matching, since it is an easy to implement procedure and it does not require sophisticated optimization algorithms to incorporate 4D seismic into the process.
A Novel Approach to Modeling and Forecasting Frac Hits in Shale Gas Wells
Authors: Lawal Hamed , Jackson Greg , Abolo Nnamdi , Flores Cecilia 
Published: June 2013

Abstract
The ultra-tight nature of shale reservoirs has resulted in the maximization of the stimulated area within a section to increase production. As a result, some wells appear to interfere with one another during stimulation. This interference has been known to typically reduce (occasionally enhance) the performance of wells currently in production by altering the existing fracture network, or near well permeability, via the presence of multiple phases. This process is known as a "frac hit". Three different mechanisms are thought to be possible causes of the well-to-well interaction: depleted zones, changing stress fields, and high permeability lithofacies. Numerical and analytical modeling will be used to explore the impact of dynamic completion systems.
In this paper, modeling techniques are demonstrated to allow operators the ability to use rate transient analysis (RTA) tools to model frac hits. Examples from the Haynesville and Marcellus are examined. The examples were categorized based on the dominant flow regime, transient linear flow or depletion flow, and then the proper technique was employed. Unique characteristics with respect to reservoir phenomenon, i.e. depleted zone, changing stress fields, or high permeability lithofacies are also discussed.
These modeling procedures will enable operators to bound forecasts for wells that have been altered by the stimulation of a neighboring well. This means operators can still provide risked reserves based on numerical modeling and RTA software for wells that have endured a hit. In addition, the techniques will be applied to re-fracturing. Now operators have the ability to forecast re-fractured wells quantifying the NPV of a re-fracture. Lastly, the knowledge gained from the in-depth examination of the phenomenon and drive mechanisms behind the frac hit enables the avoidance of future occurrences of well damage.