The Experts below are selected from a list of 28935 Experts worldwide ranked by ideXlab platform
Shahab D Mohaghegh - One of the best experts on this subject based on the ideXlab platform.
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full field Reservoir Modeling of shale assets using advanced data driven analytics
Geoscience frontiers, 2016Co-Authors: Soodabeh Esmaili, Shahab D MohagheghAbstract:Abstract Hydrocarbon production from shale has attracted much attention in the recent years. When applied to this prolific and hydrocarbon rich resource plays, our understanding of the complexities of the flow mechanism (sorption process and flow behavior in complex fracture systems - induced or natural) leaves much to be desired. In this paper, we present and discuss a novel approach to Modeling, history matching of hydrocarbon production from a Marcellus shale asset in southwestern Pennsylvania using advanced data mining, pattern recognition and machine learning technologies. In this new approach instead of imposing our understanding of the flow mechanism, the impact of multi-stage hydraulic fractures, and the production process on the Reservoir model, we allow the production history, well log, completion and hydraulic fracturing data to guide our model and determine its behavior. The uniqueness of this technology is that it incorporates the so-called “hard data” directly into the Reservoir model, so that the model can be used to optimize the hydraulic fracture process. The “hard data” refers to field measurements during the hydraulic fracturing process such as fluid and proppant type and amount, injection pressure and rate as well as proppant concentration. This novel approach contrasts with the current industry focus on the use of “soft data” (non-measured, interpretive data such as frac length, width, height and conductivity) in the Reservoir models. The study focuses on a Marcellus shale asset that includes 135 wells with multiple pads, different landing targets, well length and Reservoir properties. The full field history matching process was successfully completed using this data driven approach thus capturing the production behavior with acceptable accuracy for individual wells and for the entire asset.
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Reservoir Modeling of shale formations
Journal of Natural Gas Science and Engineering, 2013Co-Authors: Shahab D MohagheghAbstract:Abstract Economic production from shale has been intimately tied to hydraulic fracturing since the first signs of success in Barnet Shale in the late 90s. The introduction of horizontal wells and multi-stage hydraulic fracturing was met by a huge move by operators toward developing shale formations that were mainly ignored in the past. Today using pad drilling, multiple horizontal wells share surface facilities and infrastructure, a development that minimizes the industry's environmental footprint. To understand production from shale Reservoirs one must understand the network of natural fractures in the shale and the role of hydraulically induced fractures and their interaction. Hydraulic fracturing has been around and been studied by engineers for decades. Analytical, numerical and data-driven models have been built to explain their behavior and contribution to flow. Contribution of natural fracture networks to storage and flow in carbonate (and some sandstone) Reservoirs had led to the development of techniques to study and model them. Since they are the predominant source of porosity and permeability in shale, more attention has been focused on their characteristics in the recent years. Studies of methane production from coal seams in the mid 80s provided insights on sorption as a storage mechanism and desorption and diffusion as a transport phenomenon in Reservoirs that came to be known as CBM (Coalbed Methane). Today, production from shale is mainly modeled based on lessons learned in the past several decades where all the above techniques are integrated to create the modern shale Reservoir models. The coupling of hydraulic fractures and natural fracture networks and their integration and interaction with the shale matrix remains the major challenge in Reservoir simulation and Modeling of shale formations. This article reviews the methods used by scientists and engineers in recent years to understand the complexities associated with production from shale. This will shed light on the commonly held belief amongst some of the best minds in Reservoir engineering (those that have been intimately involved in Modeling production from shale) that there is much to be learned about this complex resource and that our best days in understanding and Modeling how oil and gas are produced from shale are still ahead of us.
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top down intelligent Reservoir Modeling tdirm a new approach in Reservoir Modeling by integrating classic Reservoir engineering with artificial intelligence data mining techniques
2009Co-Authors: Shahab D MohagheghAbstract:SUMMARY Traditional Reservoir simulation and Modeling is a bottom-up approach. It starts with building a geological model of the Reservoir followed by adding engineering fluid flow principles to arrive at a dynamic Reservoir model. The dynamic Reservoir model is calibrated using the production history of multiple wells and the history matched model is used to strategize field development in order to improve recovery. Top-Down Intelligent Reservoir Modeling approaches the Reservoir simulation and Modeling from an opposite angle by attempting to build a realization of the Reservoir starting with well production behavior (history). The production history is augmented by core, log, well test and seismic data in order to increase the accuracy and fine tune the Top-Down model. The model is then calibrated (history matched) using the most recent wells as blind dataset. Although not intended as a substitute for the traditional Reservoir simulation of large, complex fields, this novel approach can be used as an alternative (at a fraction of the cost and time) to traditional Reservoir simulation in cases where performing traditional Modeling is cost (and manpower) prohibitive. In cases where a conventional model of a Reservoir already exists, Top-Down Intelligent Reservoir Modeling should be considered a complement to, rather than a competition for the traditional technique. It provides an independent look at the data coming from the Reservoir/wells for optimum development strategy and recovery enhancement. Top-Down Intelligent Reservoir Modeling is an elegant integration of state-of-the-art in Artificial Intelligence & Data Mining (AI&DM) with solid Reservoir engineering techniques and principles. It provides a unique perspective of the field and the Reservoir using actual measurements. It provides qualitatively accurate Reservoir characteristics that can play a key role in making important and strategic field development decisions. In this article, principles of TopDown Intelligent Reservoir Modeling are discussed along with an actual cases study. TRADITIONAL Reservoir SIMULATION & Modeling Reservoir simulation is the industry standard for Reservoir management. It is used in all phases of field development in the oil and gas industry. The routine of simulation studies calls for integration of static and dynamic measurements into the Reservoir model. Full field Reservoir simulation models have become the major source of information for analysis, prediction and decision making. Traditional Reservoir simulation and Modeling is a bottom-up approach that starts with building a geological (geo-cellular) model of the Reservoir. Using Modeling and geostatistical manipulation of the data the geo-cellular model is populated with the best available petrophysical and geophysical information at the time of development. Engineering fluid flow principles are then added and solved numerically so as to arrive at a dynamic Reservoir model. The dynamic Reservoir model is calibrated using the production history of multiple wells in a
N J Hardebol - One of the best experts on this subject based on the ideXlab platform.
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calibrating discrete fracture network models with a carbonate three dimensional outcrop fracture network implications for naturally fractured Reservoir Modeling
AAPG Bulletin, 2014Co-Authors: K Bisdom, B D M Gauthier, G Bertotti, N J HardebolAbstract:Modeling naturally fractured Reservoirs requires a detailed understanding of the three-dimensional (3D) fracture-network characteristics, whereas generally only one-dimensional (1D) data, often suffering from sampling artifacts, are available as inputs for Modeling. Additional fracture properties can be derived from outcrop analogs with the scanline method, but it does not capture their full two-dimensional (2D) characteristics. We propose an improved workflow based on a 2D field-digitizing tool for mapping and analyzing fracture parameters as well as relations to bedding. From fracture data collected along 11 vertical surface outcrops in a quarry in southeast France, we quantify uncertainties in Modeling fracture networks. The fracture-frequency distribution fits a Gaussian distribution that we use to evaluate the intrinsic fracture density variability within the quarry at different observation scales along well-analog scanlines. Excluding well length as a parameter, we find that 30 wells should be needed to fully (i.e., steady variance) capture the natural variability in fracture spacing. This illustrates the challenge in trying to predict fracture spacing in the subsurface from limited well data. Furthermore, for models with varying scanline orientations we find that Terzaghi-based spacing corrections fail when the required correction angle is more than 60°. We apply the 1D well analog data to calculate 3D fracture frequency using stereological relations and find that these relations only work for cases in which the orientation distribution is accurately described, as results greatly vary with small changes in the orientation distribution.
M A Atmanand - One of the best experts on this subject based on the ideXlab platform.
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assessment of methane gas production from indian gas hydrate petroleum systems
Applied Energy, 2016Co-Authors: N Vedachalam, S Ramesh, S Srinivasalu, G Rajendran, G A Ramadass, M A AtmanandAbstract:Abstract The effectiveness of the electro-thermal and depressurisation based techniques applied to three marine gas hydrate Reservoir settings of India is modeled and simulated using MATLAB and TOUGH + HYDRATE Reservoir Modeling software. The results indicate that the depressurisation technique (with an achievable Δ P of >90 bar) will be effective in dissociating gas hydrates up to 145 m from a well bore in the Krishna Godavari (KG) Reservoir. The technique when applied to the Andaman and Mahanadi Reservoirs is found to produce a maximum Δ P of 64 and 70 bar against the minimum required threshold of 134 and 152 bar, and hence, found to be less effective for hydrate dissociation. The in-situ electro-thermal technique will be effective in the KG and Andaman Reservoirs; and in the Mahanadi Reservoir, if the gas hydrate saturations are >17%. The depressurization technique when applied to a hypothetical sandy Reservoir in the KG basin shows that the spatial pressure drop is nearly double that in a clayey setting, which is conducive for hydrate dissociation.
Tracy Terrall - One of the best experts on this subject based on the ideXlab platform.
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fully coupled wellbore Reservoir Modeling of geothermal heat extraction using co2 as the working fluid
Geothermics, 2015Co-Authors: Barry Freifeld, Christine Doughty, Steven Zakem, Ming Sheu, Bruce Cutright, Tracy TerrallAbstract:Abstract We consider using CO 2 as an alternative to water as a working fluid to produce geothermal electricity through the application of a coupled Reservoir, wellbore, and surface power-plant model. Our approach has relaxed some of the simplifying assumptions others have made in previous work, through the application of a subsurface Reservoir model fully coupled with a detailed wellbore simulator. We also include a simplified representation of CO 2 turbomachinery for a surface plant optimized for direct use of supercritical CO 2 . The wellbore model includes heat transfer between the fluid in the well and the surrounding formation, in addition to frictional, inertial, and gravitational forces. Our results show that thermophysical operating conditions and the amount of power production are greatly influenced by wellbore flow processes and by wellbore/caprock heat transfer. We investigate competing effects that control development of a thermosiphon, which enables production of geothermal electricity without the need for a continuously operating external pump.
Christine Doughty - One of the best experts on this subject based on the ideXlab platform.
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carbon dioxide plume evolution following injection into a depleted natural gas Reservoir Modeling of conformance uncertainty reduction over time
2019Co-Authors: Christine Doughty, Curtis M OldenburgAbstract:Author(s): Doughty, Christine; Oldenburg, Curtis | Abstract: The uncertainty in the long-term fate of CO2 injected for geologic carbon sequestration (GCS) is a significant barrier to the adoption of GCS as a greenhouse gas emission mitigation approach for industry and regulatory agencies alike. Here we present a Modeling study that demonstrates that the uncertainty in forecasts of GCS site performance decreases over time as monitoring data are used to inform and update operational models. The approach we take is to consider a case study consisting of a depleted natural gas Reservoir that is used for GCS with CO2 injection occurring over 20 years, with a 50-year post-injection site care (PISC) period. We constructed a detailed model of the system and ran this model out to 200 years to generate the actual site data. A series of simpler operational models based on limited data and assumptions about how an actual operator would model such a site are then run and compared against the actual model output at various specific monitoring points after one year, two years, etc. The operational model is then updated and improved using the observations (synthetic data from the actual model) at the same time intervals. We found that both model parameter values and model features needed to be added over time to improve matches to the actual system. These kinds of model adjustments are expected to be a normal part of Reservoir engineering and site management at GCS sites. We found that the uncertainty in two key measures related to site performance at various locations decreases with time. This overall conclusion should help allay the concerns of industry and regulators about the uncertainty in GCS operations.
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fully coupled wellbore Reservoir Modeling of geothermal heat extraction using co2 as the working fluid
Geothermics, 2015Co-Authors: Barry Freifeld, Christine Doughty, Steven Zakem, Ming Sheu, Bruce Cutright, Tracy TerrallAbstract:Abstract We consider using CO 2 as an alternative to water as a working fluid to produce geothermal electricity through the application of a coupled Reservoir, wellbore, and surface power-plant model. Our approach has relaxed some of the simplifying assumptions others have made in previous work, through the application of a subsurface Reservoir model fully coupled with a detailed wellbore simulator. We also include a simplified representation of CO 2 turbomachinery for a surface plant optimized for direct use of supercritical CO 2 . The wellbore model includes heat transfer between the fluid in the well and the surrounding formation, in addition to frictional, inertial, and gravitational forces. Our results show that thermophysical operating conditions and the amount of power production are greatly influenced by wellbore flow processes and by wellbore/caprock heat transfer. We investigate competing effects that control development of a thermosiphon, which enables production of geothermal electricity without the need for a continuously operating external pump.
