From Storage Potential to Storage Capacity - A Re-evaluation Method of 'Old' Well-logs

2012 ◽  
Author(s):  
G. Falus ◽  
A. Szamosfalvi
Keyword(s):  
Evaluation Method ◽  
Storage Capacity ◽  
Well Logs ◽  
Storage Potential

scholarly journals Transient dynamics of terrestrial carbon storage: mathematical foundation and its applications

2017 ◽  
Vol 14 (1) ◽  
pp. 145-161 ◽  
Author(s):  
Yiqi Luo ◽  
Zheng Shi ◽  
Xingjie Lu ◽  
Jianyang Xia ◽  
Junyi Liang ◽  
...  
Keyword(s):  
Residence Time ◽  
Storage Capacity ◽  
Rate Of Change ◽  
Transient Dynamics ◽  
Mathematical Framework ◽  
Time Step ◽  
C Storage ◽  
C Cycle ◽  
Storage Potential ◽  
C Input

Abstract. Terrestrial ecosystems have absorbed roughly 30 % of anthropogenic CO2 emissions over the past decades, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling and experimental and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under global change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, which is the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3-D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. In addition, the physical emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. Overall, this new mathematical framework offers new approaches to understanding, evaluating, diagnosing, and improving land C cycle models.

scholarly journals Reservoir Flow Unit Analysis of Akos Field in Niger Delta

2020 ◽  
pp. 32-45
Author(s):  
G. O. Emujakporue ◽  
E. E. Enyenihi
Keyword(s):  
Niger Delta ◽  
Storage Capacity ◽  
Well Logs ◽  
Sampling Depth ◽  
Flow Units ◽  
Flow Capacity ◽  
Reservoir Flow ◽  
Porosity And Permeability ◽  
And Storage ◽  
Cumulative Flow

In this study, the flow units of reservoirs of Akos field have been computed with the Stratigraphic Modified Lorenz plot. Cumulative flow capacity and cumulative storage capacity were used for constructing the Stratigraphic Modified Lorenz Plot (SMLP). The flow capacity and storage capacity are functions of calculated permeability and porosity values considering their sampling depth. The porosity and permeability were obtained from composite well logs of eight oil wells in the study area. Two reservoirs A and B were delineated from the well logs. The stratigraphic Modified Lorenz Plots (SMLP) revealed a total of one hundred and twelve (112) Flow units (FU) in the two observed reservoirs A and B. Reservoir A has a total of 53 FU (25 speed zones, 18 baffle zones and 10 barrier zones) and reservoir B has a total of 59 FU (29 speed zones, 16 baffle zones and 14 barrier zones) which cut across all the wells. The flow units in both reservoirs fall within the speed zones, baffles and barrier unit categories. The speed zone units with equal flow and storage capacities are the dominant flow units in both reservoirs. This is an indication that the sediments have good reservoir qualities. The baffle zones have more storage capacity than the speed zones. The barrier zones within the reservoirs are acting as a seal to the flow of fluid.

scholarly journals CO2 storage capacity estimation under geological uncertainty using 3-D geological modeling of unconventional reservoir rocks in Shahejie Formation, block Nv32, China

2021 ◽  
Vol 11 (6) ◽  
pp. 2327-2345
Author(s):  
Ayman Mutahar AlRassas ◽  
Shaoran Ren ◽  
Renyuan Sun ◽  
Hung Vo Thanh ◽  
Zhenliang Guan
Keyword(s):  
Pore Volume ◽  
Storage Capacity ◽  
Co2 Storage ◽  
Optimal Solution ◽  
Well Logs ◽  
Reservoir Properties ◽  
Geological Uncertainty ◽  
Reservoir Rocks ◽  
Shahejie Formation ◽  
Net To Gross

AbstractUnderground CO2 storage is a promising technology for mitigating climate change. In this vein, the subsurface condition was inherited a lot of uncertainties that prevent the success of the CO2 storage project. Therefore, this study aims to build the 3D model under geological uncertainties for enhancing CO2 storage capacity in the Shahejie Formation (Es1), Nv32 block, China. The well logs, seismic data, and geological data were used for the construction of 3-D petrophysical models. The target study area model focused on four units (Es1 × 1, Es1 × 2, Es1 × 3, and Es1 × 4) in the Shahejie Formation. Well logs were utilized to predict petrophysical properties; the lithofacies indicated that the Shahejie Formation units are sandstone, shale, and limestone. Also, the petrophysical interpretation demonstrated that the $$Es1$$ E s 1 reservoir exhibited high percentage porosity, permeability, and medium to high net-to-gross ratios. The static model showed that there are lateral heterogeneities in the reservoir properties and lithofacies; optimal reservoir rocks exist in Es1 × 4, Es1 × 3, and Es1 × 2 units. Moreover, the pore volume of the Es1 unit was estimated from petrophysical property models, ranging between 0.554369 and 10.03771 × 106 sm3, with a total volumetric value of 20.0819 × 106 sm3 for the four reservoir units. Then, the 100–400 realizations were generated for the pore volume uncertainties assessment. In consequence, 200 realizations were determined as an optimal solution for capturing geological uncertainties. The estimation of CO2 storage capacity in the Es1 formation ranged from 15.6 to 207.9 × 109 t. This result suggests the potential of CO2 geological storage in the Shahejie Formation, China.

Inversion-based method for estimating total organic carbon and porosity and for diagnosing mineral constituents from multiple well logs in shale-gas formations

2013 ◽  
Vol 1 (1) ◽  
pp. T113-T123 ◽  
Author(s):  
Zoya Heidari ◽  
Carlos Torres-Verdín
Keyword(s):  
Shale Gas ◽  
Evaluation Method ◽  
Water Saturation ◽  
Total Porosity ◽  
Well Logs ◽  
Well Log ◽  
X Ray Diffraction ◽  
X Ray ◽  
Compositional Properties ◽  
Organic Shale

Reliable estimates of petrophysical and compositional properties of organic shale are critical for detecting perforation zones or candidates for hydro-fracturing jobs. Current methods for in situ formation evaluation of organic shale largely rely on qualitative responses and empirical formulas. Even core measurements can be inconsistent and inaccurate when evaluating clay minerals and other grain constituents. We implement a recently introduced inversion-based method for organic-shale evaluation from conventional well logs. The objective is to estimate total porosity, total organic carbon (TOC), and volumetric/weight concentrations of mineral/fluid constituents. After detecting bed boundaries, the first step of the method is to perform separate inversion of individual well logs to estimate bed physical properties such as density, neutron migration length, electrical conductivity, photoelectric factor (PEF), and thorium, uranium , and potassium volumetric/weight concentrations. Next, a multilayer petrophysical model specific to organic shale is constructed with an initial guess obtained from conventional well-log interpretation or X-ray diffraction data; bed physical properties are calculated with the initial layer-by-layer values. Final estimates of organic shale petrophysical and compositional properties are obtained by progressively minimizing the difference between calculated and measured bed properties. A unique advantage of this method is the correction of shoulder-bed effects on well logs, which are prevalent in shale-gas plays. Another advantage is the explicit calculation of accurate well-log responses for specific petrophysical, mineral, fluid, and kerogen properties based on chemical formulas and volumetric concentrations of minerals/kerogen and fluid constituents. Examples are described of the successful application of the new organic-shale evaluation method in the Haynesville shale-gas formation. This formation includes complex solid compositions and thin beds where rapid depth variations of mineral/fluid constituents are commonplace. Comparison of estimates for total porosity, total water saturation, and TOC obtained with (a) commercial software for multimineral analysis, (b) our organic-shale evaluation method, and (c) core/X-ray diffraction measurements indicates a significant improvement in estimates of total porosity and water saturation yielded by our interpretation method. The estimated TOC is also in agreement with core laboratory measurements.

scholarly journals Storage capacity and containment issues for carbon dioxide capture and geological storage on the UK continental shelf

2008 ◽  
Vol 223 (3) ◽  
pp. 239-248 ◽  
Author(s):  
S Holloway
Keyword(s):  
Carbon Dioxide ◽  
Continental Shelf ◽  
Large Scale ◽  
Storage Capacity ◽  
Saline Water ◽  
Pressure Rise ◽  
Greenhouse Gas Mitigation ◽  
Reservoir Rock ◽  
Storage Potential ◽  
The Uk

Carbon dioxide (CO2) can be stored in geological formations beneath the UK continental shelf (UKCS) as a greenhouse gas mitigation option. It can be trapped in subsurface reservoirs in structural or stratigraphic traps beneath cap rocks, as a residual CO2 saturation in pore spaces along the CO2 migration path within the reservoir rock, by dissolution into the native pore fluid (most commonly brine), by reaction of acidified groundwater with mineral components of the reservoir rock, or by adsorption onto surfaces within the reservoir rock, e.g. onto the carbonaceous macerals that are the principal components of coal. Estimates of the CO2 storage capacity of oil and gas fields on the UKCS suggest that they could store between 1200 and 3500×106 t of CO2 and up to 6100×106 t CO2, respectively. Estimating the regional CO2 storage potential of saline water-bearing sedimentary rocks is resource-intensive and no UK estimates have yet taken into account all the factors that should be considered. Existing studies estimate the pore volume and the likely CO2 saturation in the closed structures in a potential reservoir formation but do not take account of the potentially limiting regional pressure rise likely to occur as a result of the very large-scale CO2 injection that would be necessary to make an impact on national emissions. There is undoubtedly great storage potential in the saline water-bearing reservoir rocks of the basins around the UK, but the real challenge for studies of aquifer CO2 storage capacity in the UK is perhaps not to estimate the total theoretical CO2 storage capacity, as this is not a particularly meaningful number. Rather it is to thoroughly investigate selected reservoirs perceived to have good storage potential to a standard where there is scientific consensus that the resulting storage capacity estimates are realistic. This will allow it to be considered as closer to the status of a reserve rather than a resource and will help define the scope for CO2 capture and storage in the UK.

scholarly journals Technical Potential of Salt Caverns for Hydrogen Storage in Europe

2019 ◽  
Author(s):  
Dilara Caglayan ◽  
Nikolaus Weber ◽  
Heidi Ursula Heinrichs ◽  
Jochen Linßen ◽  
Martin Robinius ◽  
...  
Keyword(s):  
Storage Capacity ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Salt Domes ◽  
Suitability Assessment ◽  
The North ◽  
Technical Potential ◽  
Storage Potential ◽  
Salt Caverns ◽  
And Storage

The role of hydrogen in a future energy system with a high share of variable renewable energy sources (VRES) is regarded as crucial in order to balance fluctuations in electricity generation. These fluctuations can be compensated for by flexibility measures such as the expansion of transmission, flexible generation, larger back-up capacity and storage. Salt cavern storage is the most promising technology due to its large storage capacity, followed by pumped hydro storage. For the underground storage of chemical energy carriers such as hydrogen, salt caverns offer the most promising option owing to their low investment cost, high sealing potential and low cushion gas requirement. This paper provides a suitability assessment of European subsurface salt structures in terms of size, land eligibility and storage capacity. Two distinct cavern volumes of 500,000 m3 and 750,000 m3 are considered, with preference being given for salt caverns over bedded salt deposits and salt domes. The storage capacities of individual caverns are estimated on the basis of thermodynamic considerations based on site-specific data. The results are analyzed using three different scenarios: onshore and offshore salt caverns, only onshore salt caverns and only onshore caverns within 50 km of the shore. The overall technical storage potential across Europe is estimated at 84.8 PWhH2, 27% of which constitutes only onshore locations. Furthermore, this capacity decreases to 7.3 PWhH2 with a limitation of 50 km distance from shore. In all cases, Germany has the highest technical storage potential, with a value of 9.4 PWhH2, located onshore only in salt domes in the north of the country. Moreover, Norway has 7.5 PWhH2 of storage potential for offshore caverns, which are all located in the subsurface of the North Sea Basin.

scholarly journals Transient Dynamics of Terrestrial Carbon Storage: Mathematical foundation and Numeric Examples

2016 ◽  
Author(s):  
Yiqi Luo ◽  
Zheng Shi ◽  
Xingjie Lu ◽  
Jianyang Xia ◽  
Junyi Liang ◽  
...  
Keyword(s):  
Residence Time ◽  
Storage Capacity ◽  
Net Primary Production ◽  
Rate Of Change ◽  
Transient Dynamics ◽  
Time Step ◽  
C Storage ◽  
C Cycle ◽  
Storage Potential ◽  
C Input

Abstract. Terrestrial ecosystems absorb roughly 30 % of anthropogenic CO2 emissions since preindustrial era, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling, experimental, and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under climate change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can exactly replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. Moreover, the emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. We also propose that the C storage potential be the targeted variable for research, market trading, and government negotiation for C credits.

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