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Collaborating Authors
January, 2017 up to December, 2017
What are the most significant challenges facing the E&P sector in Norway? The oil and gas industry has been through a couple of really challenging years with low oil and gas prices and low profitability. As the activity level is now starting to increase on the Norwegian Continental Shelf (NCS), we see pessimism turning into more optimism. I believe one of our most significant challenges right now is to avoid getting into an increasing cost spiral that we have experienced before. We need to continue the improvement journey most industry players have started and, in collaboration, develop lasting, sustainable efficiency improvements, focus on standardization and low-cost solutions, and develop and implement technology to improve efficiency.
- Europe > Norway > North Sea > Northern North Sea > North Viking Graben > PL 054 > Block 31/6 > Troll Field > Sognefjord Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > North Viking Graben > PL 054 > Block 31/6 > Troll Field > Heather Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > North Viking Graben > PL 054 > Block 31/6 > Troll Field > Fensfjord Formation (0.99)
- (9 more...)
Summary Wellbore tortuosity or spiraling can lead to the trapping of a cuttings bed in a trough of a tortuous hole, thereby leading to poor hole cleaning in extended-reach drilling. The objectives of this study included quantitatively evaluating the influences of wellbore tortuosity on hole cleaning and cuttings-transport behavior in extended-reach drilling. In addition, the study provided a recommendation of effective drilling practices. The study involved performing hole-cleaning-optimization studies for an extended-reach well with a long horizontal section aiming for maximum reservoir contact, by use of a transient cuttings-transport simulator. The planned trajectory of the well was assumed to have a certain degree of wellbore tortuosity in the horizontal section. The pump rate and bottoms-up circulation operation were optimized on the basis of parameter studies and additional transient simulations by considering the effects of penetration rate and variation in cuttings size. Simulation results indicated the formation of a considerably high cuttings bed, particularly in the downdip intervals (updip in mud-flow direction) at an insufficient pump rate; one-third to one-half of the drillpipe diameter could be potentially buried in a cuttings-deposit bed, and this can result in a packed-off hole or stuck pipe. A higher rate of penetration (ROP) can also cause insufficient hole cleaning. In this case, controlled drilling that maintains a reasonably low penetration rate may be effective. Furthermore, borehole breakout may enlarge hole diameter and generate large-sized cuttings. Both of these can have negative impacts on hole cleaning, and, thus, borehole stability and smooth wellbore-trajectory controls should be carefully considered. To clean these holes, frequent bottoms-up circulations were effective at each stand of drilling even if the optimization of other drilling parameters was limited. The findings also revealed that accumulated cuttings in a tortuous wellbore were trapped in the trough of the hole, and that the bed height of locally trapped cuttings in the downdip intervals could be much higher than that indicated by previous studies.
- Asia > Japan (0.69)
- Asia > Middle East (0.68)
- North America > United States > Texas (0.28)
- Asia > Middle East > Saudi Arabia > Eastern Province > Rub' al Khali Governorate > Rub' al Khali Basin > Shaybah Field (0.99)
- Asia > Middle East > UAE > Abu Dhabi > Arabian Gulf > Rub' al Khali Basin > Abu Dhabi Field (0.98)
A Novel Approach To Detect Interacting Behavior Between Hydraulic Fracture and Natural Fracture by Use of Semianalytical Pressure-Transient Model
Xiao, Cong (China University of Petroleum, Beijing) | Tian, Leng (China University of Petroleum, Beijing) | Zhang, Yayun (China University of Petroleum, Beijing) | Hou, Tengfei (China University of Petroleum, Beijing) | Yang, Yaokun (China University of Petroleum, Beijing) | Deng, Ya (China National Petroleum Corporation) | Wang, Yanchen (Shengli Oilfield Service Corporation) | Chen, Sheng (China National Petroleum Corporation)
Summary The detection of interacting behavior between the hydraulic fracture (HF) and the natural fracture (NF) is of significance to accurately and efficiently characterize an underground complex-fracture system induced by hydraulic-fracturing technology. This work develops a semianalytical pressure-transient model in the Laplace domain to detect interacting behavior between HF and NF depending on pressure-transient characteristics. Our results have shown that no matter what the flow state (compressible or incompressible flow) within a hydraulically induced fracture system, we can easily detect interacting behavior between HF and NF depending on whether the "dip" shape occurs at the formation radial-flow regime. Referring to sensitivity analysis, distance between NF and well, horizontal distance between NF and HF, and NF length are the three most sensitive factors to detect fracture-interacting behavior. Depending on interference analysis, although the pressure-transient characteristics of a pseudosteady-state dual-porosity model can interfere with our proposed methodology, the difference between our model and a pseudosteady-state dual-porosity system lies in whether the value of the horizontal line of dimensionless pressure derivative is equal to 0.5 at the formation radial-flow regime. Our work obtains some innovative insights into detecting fracture-interacting behavior, and the valuable results can provide significant guidance for refracturing operations and fracture detection in an underground fracture system. Introduction The seepage behavior in a naturally fractured reservoir (NFR) has been extensively investigated because of its importance in safe storage facilities for captured carbon dioxide and geothermal and petroleum resource recovery. For some special underground fracture systems, including tight reservoir and shale reservoir, because of extremely low permeability and porosity values, hydraulic-fracturing stimulation has become an integral technology for their effective development. Not only can hydraulic-fracturing technology create several high-conductivity HFs as flow paths, but can also activate and connect pre-existing NFs to form a spatially complex fracture network (Mayerhofer et al. 2006; Ozkan et al. 2011; Stalgorova and Mattar 2012, 2013; Clarkson 2013; Sierra and Mayerhofer 2014). It is universally acknowledged that the complexity of the resulting HF network is caused by the interacting behavior between HFs and NFs. Some of these studies concentrate on the mechanical interaction when HFs encounter pre-existing NFs, and corresponding criteria to predict whether HFs will propagate across a randomly frictional interface were developed. These criteria are derived from the linear-elastic fracture-mechanics solution for the stresses near the fracture tip, and the criteria were validated by laboratory experiments.
- Asia > China (0.95)
- North America > United States > Texas (0.68)
- Geology > Geological Subdiscipline > Geomechanics (0.46)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.34)
- North America > United States > Texas > Fort Worth Basin > Barnett Shale Formation (0.99)
- Asia > China > Shandong > North China Basin > Shengli Field (0.99)
Summary A new-generation compositional reservoir-flow-simulation model is presented for gas-bearing organic-rich source rocks, including convective/diffusive mass-balance equations for each hydrocarbon component in the organic (kerogen), inorganic, and fracture continua. The model accounts for the presence of dispersed kerogen with sorbed-gas corrected dynamic porosity. The Maxwell-Stefan theory is used to predict pressure-and composition-dependence of molecular diffusion in the formation. The equations are discretized and solved numerically by use of the control-volume finite-element method (CVFEM). The simulation is derived from a new multiscale conceptual flow model. We consider that kerogen is dispersed at a fine scale in the inorganic matrix and that it will be the discontinuous component of total porosity at the reservoir-simulation scale, which could be up to six orders of magnitude larger. A simple mass-balance equation is introduced to enable kerogen to transfer gas to the inorganic matrix that is collocated in the same gridblock. The convective/diffusive transport takes place between neighboring gridblocks only in the inorganic matrix. The simulation results show that the multiscale nature of the rock is important and should not be ignored because this could result in an overestimation of the contribution of the discontinuous kerogen. We also observe that although adsorbed fluid could contribute significantly to storage in the shale formation, its contribution to production could be severely limited by the lack of kerogen continuity at the reservoir scale and by a low degree of coupling between the organic and inorganic pores. The contribution of the Maxwell-Stefan diffusion to the overall transport in the shale formation increases as the inorganic matrix permeability is reduced because of pressure decline during production. Introduction Oil and gas production from organic-rich source rocks is characterized by a sharp decline. This decline is a manifestation of flowregime transition from an early time, when the production is mainly caused by flow in fractures, to a later period, when the matrix begins to contribute to the production. The extent of the early transient, which could be ephemeral, depends on the presence of fractures and on the physical qualities (conductivity, spatial distribution) of the fracture network. The later period, on the other hand, could take large production times and is characterized by a long tail in production-history plots. Its extent is controlled by the formation qualities.
- Research Report > New Finding (0.34)
- Research Report > Experimental Study (0.34)
- North America > United States > Texas > Fort Worth Basin > Barnett Shale Formation (0.99)
- North America > United States > Texas > West Gulf Coast Tertiary Basin > Eagle Ford Shale Formation (0.98)
- North America > United States > Texas > Sabinas - Rio Grande Basin > Eagle Ford Shale Formation (0.98)
- (2 more...)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale oil (1.00)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale gas (1.00)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Naturally-fractured reservoirs (1.00)
- (5 more...)
Summary Multiscale methods have been developed as a robust alternative to upscaling and to accelerate reservoir simulation. In their basic setup, multiscale methods use both a restriction operator to construct a reduced system of flow equations that can be solved on a coarser grid and a prolongation operator to map pressure unknowns from the coarse grid back to the original simulation grid. When combined with a local smoother, this gives an iterative solver that can efficiently compute approximate pressures to within a prescribed accuracy and still provide mass-conservative fluxes. We present an adaptive and flexible framework for combining multiple sets of such multiscale approximations. Each multiscale approximation can target a certain scale; geological features such as faults, fractures, facies, or other geobodies; or a particular computational challenge such as propagating displacement and chemical fronts, wells being turned on or off, and others. Multiscale methods that fit the framework are characterized by three features. First, the prolongation and restriction operators are constructed by use of a nonoverlapping partition of the fine grid. Second, the prolongation operator is composed of a set of basis functions, each of which has compact support within a support region that contains a coarse gridblock. Finally, the basis functions form a partition of unity. These assumptions are quite general and encompass almost all existing multiscale (finite-volume) methods that rely on localized basis functions. The novelty of our framework is that it enables multiple pairs of prolongation and restriction operatorsโcomputed on different coarse grids and possibly also by different basis-function formulationsโto be combined into one iterative procedure. Through a series of numerical examples consisting of both idealized geology and flow physics as well as a geological model of a real asset, we demonstrate that the new iterative framework increases the accuracy and efficiency of the multiscale technology by improving the rate at which one converges the fine-scale residuals toward machine precision. In particular, we demonstrate how it is possible to combine multiscale prolongation operators that have different spatial resolution and that each individual operator can be designed to target, among others, challenging grids, including faults, pinchouts, and inactive cells; high-contrast fluvial sands; fractured carbonate reservoirs; and complex wells.
- Geology > Structural Geology > Fault (0.67)
- Geology > Sedimentary Geology > Depositional Environment (0.48)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.46)
- Europe > United Kingdom > North Sea > Central North Sea > Ness Formation (0.99)
- Europe > Norway > North Sea > Tarbert Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 050 > Block 34/10 > Gullfaks Field > Statfjord Group (0.99)
- (6 more...)
Summary Multiobjective optimization (MOO), which accounts for several distinct, possibly conflicting, objectives, is expected to be capable of providing improved reservoir-management (RM) solutions for efficient oilfield development because of the overall optimization of subsurface flow. Considering the complexity and diversity of MOO problems in model-based RM, we develop three MOO methodsโMOAdjoint, MOGA, and MOPSOโin this work to address various oilfield-development problems. MOAdjoint combines a weighted-sum technique with a gradient-based method for solving large-scale continuous problems that have thousands of variables. An adjoint method is used to efficiently compute the derivatives of objective functions with respect to decision variables, and a sequential quadratic-programming method is used for optimization search. MOGA is a population-based method, which combines a Pareto-ranking technique with genetic algorithm (GA) to address small-scale (discrete) problems. MOPSO is another population-based method, which combines a Pareto technique with particle-swarm optimization (PSO) for a wide spectrum of optimization problems. Their advantages and disadvantages are highlighted. To take advantage of the strengths and overcome the drawbacks of these methods, a multiscale hybrid strategy is further formulated for solving complex, large-scale optimization problems by combining these methods at various scales. An example is used to compare these methods. Results show that all three methods can yield improved solutions. MOPSO seems particularly suitable for medium-scale RM problems, mainly because of its relatively fast convergence speed and efficient recovery of the Pareto front. With a proper initial guess and a set of effective weight coefficients, MOAdjoint can most efficiently solve large-scale continuous problems, particularly if model uncertainty is considered. The multiscale hybrid strategy is able to offer the best result.
- Europe (1.00)
- North America > United States > California (0.28)
A Tracing Algorithm for Flow Diagnostics on Fully Unstructured Grids With Multipoint Flux Approximation
Zhang, Zhao (Heriot-Watt University) | Geiger, Sebastian (Heriot-Watt University) | Rood, Margaret (Imperial College London) | Jacquemyn, Carl (Imperial College London) | Jackson, Matthew (Imperial College London) | Hampson, Gary (Imperial College London) | De Carvalho, Felipe Moura (University of Calgary) | Marques Machado Silva, Clarissa Coda (University of Calgary) | Machado Silva, Julio Daniel (University of Calgary) | Costa Sousa, Mario (University of Calgary)
Summary Flow diagnostics is a common way to rank and cluster ensembles of reservoir models depending on their approximate dynamic behavior before beginning full-physics reservoir simulation. Traditionally, they have been performed on corner-point grids inherent to geocellular models. The rapid-reservoir-modeling (RRM) concept aims at fast and intuitive prototyping of geologically realistic reservoir models. In RRM, complex reservoir heterogeneities are modeled as discrete volumes bounded by surfaces that are sketched in real time. The resulting reservoir models are discretized by use of fully unstructured tetrahedral meshes where the grid conforms to the reservoir geometry, hence preserving the original geological structures that have been modeled. This paper presents a computationally efficient work flow for flow diagnostics on fully unstructured grids. The control-volume finite-element method (CVFEM) is used to solve the elliptic pressure equation. The flux field is a multipoint flux approximation (MPFA). A new tracing algorithm is developed on a reduced monotone acyclic graph for the hyperbolic transport equations of time of flight (TOF) and tracer distributions. An optimal reordering technique is used to deal with each control volume locally such that the hyperbolic equations can be computed in an efficient node-by-node manner. This reordering algorithm scales linearly with the number of unknowns. The results of these computations allow us to estimate swept-reservoir volumes, injector/producer pairs, well-allocation factors, flow capacity, storage capacity, and dynamic Lorenz coefficients, which all help approximate the dynamic reservoir behavior. The total central-processing-unit (CPU) time, including grid generation and flow diagnostics, is typically a few seconds for meshes with (100,000) unknowns. Such fast calculations provide, for the first time, real-time feedback in the dynamic reservoir behavior while models are prototyped.
- South America > Brazil (0.68)
- North America > United States > Texas (0.28)
- North America > Canada > Alberta (0.28)
- Europe > United Kingdom > England (0.28)
- Geology > Sedimentary Geology (0.93)
- Geology > Geological Subdiscipline (0.67)
- Europe > Austria > Vienna > Vienna Basin (0.99)
- Europe > Austria > Lower Austria > Vienna Basin (0.99)
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Geologic modeling (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Tracer test analysis (0.87)
- Information Technology > Software (0.93)
- Information Technology > Modeling & Simulation (0.70)
- Information Technology > Architecture > Real Time Systems (0.54)
Summary Commercial compositional simulators commonly apply correlations or empirical relations that are based on fitting experimental data to calculate phase relative permeabilities. These relations cannot adequately capture the effects of hysteresis, fluid compositional variations, and rock-wettability alteration. Furthermore, these relations require phases to be labeled, which is not accurate for complex miscible or near-miscible displacements with multiple hydrocarbon phases. Therefore, these relations can be discontinuous for compositional processes, causing inaccuracies and numerical problems in simulation. This paper develops for the first time an equation-of-state (EOS) to model robustly and continuously the relative permeability as a function of phase saturations and distributions, fluid compositions, rock-surface properties, and rock structure. Phases are not labeled; instead, the phases in each gridblock are ordered on the basis of their compositional similarity. Phase compositions and rock-surface properties are used to calculate wettability and contact angles. The model is tuned to measured two-phase relative permeability curves with very few tuning parameters and then is used to predict relative permeability away from the measured experimental data. The model is applicable to all flow in porous-media processes, but is especially important for low-salinity polymer, surfactant, miscible gas, and water-alternating-gas (WAG) flooding. The results show excellent ability to match measured data, and to predict observed trends in hysteresis and oil-saturation trapping, including those from Land's model and for a wide range in wettability. The results also show that relative permeabilities are continuous at critical points and yield a physically correct numerical solution when incorporated within a compositional simulator (PennSim 2013). The model has very few tuning parameters, and the parameters are directly related to physical properties of rock and fluid, which can be measured. The new model also offers the potential for incorporating results from computed-tomography (CT) scans and pore-network models to determine some input parameters for the new EOS.
- North America > United States > Pennsylvania (0.47)
- North America > United States > Texas (0.46)
- Research Report > New Finding (0.66)
- Research Report > Experimental Study (0.48)
- North America > United States > Texas > East Texas Salt Basin > Hawkins Field > Woodbine Formation (0.99)
- North America > United States > Mississippi > Anna Field (0.89)
- Europe > United Kingdom > North Sea > Southern North Sea > Southern Gas Basin > Sole Pit Basin > Block 49/22 > Victor Field > Leman Sandstone Formation (0.89)
- Europe > United Kingdom > North Sea > Southern North Sea > Southern Gas Basin > Sole Pit Basin > Block 49/17 > Victor Field > Leman Sandstone Formation (0.89)
A Gauss-Newton Trust-Region Solver for Large-Scale History-Matching Problems
Gao, Guohua (Shell Global Solutions (US) Incorporated) | Jiang, Hao (Shell Global Solutions (US) Incorporated) | Hagen, Paul van (Shell Global Solutions International B.V.) | Vink, Jeroen C. (Shell Global Solutions International B.V.) | Wells, Terence (Shell Global Solutions International B.V.)
Summary Solving the Gauss-Newton trust-region subproblem (TRS) with traditional solvers involves solving a symmetric linear system with dimensions the same as the number of uncertain parameters, and it is extremely computational expensive for history-matching problems with a large number of uncertain parameters. A new trust-region (TR) solver is developed to save both memory usage and computational cost, and its performance is compared with the well-known direct TR solver using factorization and iterative TR solver using the conjugate-gradient approach. With application of the matrix inverse lemma, the original TRS is transformed to a new problem that involves solving a linear system with the number of observed data. For history-matching problems in which the number of uncertain parameters is much larger than the number of observed data, both memory usage and central-processing-unit (CPU) time can be significantly reduced compared with solving the original problem directly. An auto-adaptive power-law transformation technique is developed to transform the original strong nonlinear function to a new function that behaves more like a linear function. Finally, the Newton-Raphson method with some modifications is applied to solve the TRS. The proposed approach is applied to find best-match solutions in Bayesian-style assisted-history-matching (AHM) problems. It is first validated on a set of synthetic test problems with different numbers of uncertain parameters and different numbers of observed data. In terms of efficiency, the new approach is shown to significantly reduce both the computational cost and memory usage compared with the direct TR solver of the GALAHAD optimization library (see ). In terms of robustness, the new approach is able to reduce the risk of failure to find the correct solution significantly, compared with the iterative TR solver of the GALAHAD optimization library. Our numerical results indicate that the new solver can solve large-scale TRSs with reasonably small amounts of CPU time (in seconds) and memory (in MB). Compared with the CPU time and memory used for completing one reservoir simulation run for the same problem (in hours and in GB), the cost for finding the best-match parameter values using our new TR solver is negligible. The proposed approach has been implemented in our in-house reservoir simulation and history-matching system, and has been validated on a real-reservoir-simulation model. This illustrates the main result of this paper: the development of a robust Gauss-Newton TR approach, which is applicable for large-scale history-matching problems with negligible extra cost in CPU and memory.
- North America > United States (0.46)
- Europe (0.46)
- Asia > Middle East (0.46)
- Europe > United Kingdom (0.89)
- Europe > Netherlands (0.89)
- Asia > Middle East > Syria (0.89)
- Africa > Nigeria (0.89)
- Information Technology > Modeling & Simulation (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Optimization (1.00)
- Information Technology > Artificial Intelligence > Machine Learning (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (0.46)
Analysis of Effective Porosity and Effective Permeability in Shale-Gas Reservoirs With Consideration of Gas Adsorption and Stress Effects
Pang, Y.. (Texas Tech University) | Soliman, M. Y. (University of Houston) | Deng, H.. (Chengdu University of Technology) | Emadi, Hossein (Texas Tech University)
Summary Nanoscale porosity and permeability play important roles in the characterization of shale-gas reservoirs and predicting shale-gas-production behavior. The gas adsorption and stress effects are two crucial parameters that should be considered in shale rocks. Although stress-dependent porosity and permeability models have been introduced and applied to calculate effective porosity and permeability, the adsorption effect specified as pore volume (PV) occupied by adsorbate is not properly accounted. Generally, gas adsorption results in significant reduction of nanoscale porosity and permeability in shale-gas reservoirs because the PV is occupied by layers of adsorbed-gas molecules. In this paper, correlations of effective porosity and permeability with the consideration of combining effects of gas adsorption and stress are developed for shale. For the adsorption effect, methane-adsorption capacity of shale rocks is measured on five shale-core samples in the laboratory by use of the gravimetric method. Methane-adsorption capacity is evaluated through performing regression analysis on Gibbs adsorption data from experimental measurements by use of the modified Dubinin-Astakhov (D-A) equation (Sakurovs et al. 2007) under the supercritical condition, from which the density of adsorbate is found. In addition, the Gibbs adsorption data are converted to absolute adsorption data to determine the volume of adsorbate. Furthermore, the stress-dependent porosity and permeability are calculated by use of McKee correlations (McKee et al. 1988) with the experimentally measured constant pore compressibility by use of the nonadsorptive-gas-expansion method. The developed correlations illustrating the changes in porosity and permeability with pore pressure in shale are similar to those produced by the Shi and Durucan model (2005), which represents the decline of porosity and permeability with the increase of pore pressure in the coalbed. The tendency of porosity and permeability change is the inverse of the common stress-dependent regulation that porosity and permeability increase with the increase of pore pressure. Here, the gas-adsorption effect has a larger influence on PV than stress effect does, which is because more gas is attempting to adsorb on the surface of the matrix as pore pressure increases. Furthermore, the developed correlations are added into a numerical-simulation model at field scale, which successfully matches production data from a horizontal well with multistage hydraulic fractures in the Barnett Shale reservoir. The simulation results note that without considering the effect of PV occupied by adsorbed gas, characterization of reservoir properties and prediction of gas production by history matching cannot be performed reliably. The purpose of this study is to introduce a model to calculate the volume of the adsorbed phase through the adsorption isotherm and propose correlations of effective porosity and permeability in shale rocks, including the consideration of the effects of both gas adsorption and stress. In addition, practical application of the developed correlations to reservoir-simulation work might achieve an appropriate evaluation of effective porosity and permeability and provide an accurate estimation of gas production in shale-gas reservoirs.
- Asia (1.00)
- North America > United States > Texas (0.49)
- North America > United States > Texas > Fort Worth Basin > Barnett Shale Formation (0.99)
- Asia > China > Shanxi > Ordos Basin (0.99)
- Asia > China > Shaanxi > Ordos Basin (0.99)
- Asia > China > Gansu > Ordos Basin (0.99)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale gas (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)