Mesh, properties, initial conditions, injection/withdrawal rates for modeling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, on large scale grid, with some results. First simulation of J.T. Smith, E. Sonnenthal, P. Dobson, P. Nico, and M. Worthington, 2021. Thermal-hydrological-mechanical modeling of Stockton University reservoir cooling system, Proceedings of the 46th Workshop on Geothermal Reservoir Engineering, Stanford University, SGP-TR-218, from which Figures 1-5 pertain.

Mesh, properties, initial conditions, injection/withdrawal rates for modelling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, for unscheduled two hour injection at 133 % designed capacity, on fine scale grid, with some results. Second simulation of J.T. Smith, E. Sonnenthal, P. Dobson, P. Nico, and M. Worthington, 2021. Thermal-hydrological-mechanical modeling of Stockton University reservoir cooling system, Proceedings of the 46th Workshop on Geothermal Reservoir Engineering, Stanford University, SGP-TR-218, from which Figures 6-9, pertain.

Mesh, properties, initial conditions, injection/withdrawal rates for modelling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, for unscheduled two hour injection at 133 % designed capacity, on fine scale grid, with some results. Second simulation of J.T. Smith, E. Sonnenthal, P. Dobson, P. Nico, and M. Worthington, 2021. Thermal-hydrological-mechanical modeling of Stockton University reservoir cooling system, Proceedings of the 46th Workshop on Geothermal Reservoir Engineering, Stanford University, SGP-TR-218, from which Figures 6-9, pertain.

This is the modeling data (input/output files of TOUGHREACT 4.10) used to simulate the reactive transport processes of the Aquifer Thermal Energy Storage (ATES) operations at Stockton University, NJ. Readme.txt lists all the files. TOUGHREACT 4.10 requires to reproduce the modeling output. The modeling data in this submission is related to the Aquifer Injection for Energy Storage purposes outlined in "Reactive Transport Modeling of Aquifer Thermal Energy Storage System at Stockton, NJ During Seasonal Operations".

This is the modeling data (input/output files of TOUGHREACT 4.10) used to simulate the reactive transport processes of the Aquifer Thermal Energy Storage (ATES) operations at Stockton University, NJ. Readme.txt lists all the files. TOUGHREACT 4.10 requires to reproduce the modeling output. The modeling data in this submission is related to the Aquifer Injection for Energy Storage purposes outlined in "Reactive Transport Modeling of Aquifer Thermal Energy Storage System at Stockton, NJ During Seasonal Operations".

This dataset contains input data, code, ReadMe files, output data, and figures that summarize the results of a stochastic analysis of geothermal reservoir production from two potential geothermal reservoirs that were evaluated for the Cornell University Deep Direct-Use project. These potential reservoirs are the Trenton-Black River (TBR) from 2.27-2.3 km depth, and basement rocks from 3.0-3.5 km depth and 3.5-4.0 km depth. Several utilization scenarios consisting of different injection fluid temperatures and flow rates were evaluated for each reservoir. Uncertainty in geologic properties, thermal properties, economic costs, and utilization efficiencies were evaluated using a Monte Carlo analysis of the reservoir simulations. Some reservoir simulations of the TBR were completed using the TOUGH2 software, as implemented in PetraSIM. The PetraSIM run files and associated data are provided with this submission. All other reservoir simulations were completed using the GEOPHIRES software, with some modifications to complete the uncertainty analyses. ReadMe files that describe additions to GEOPHIRES, the GEOPHIRES input data, and the output data are all provided, and references are provided to the code repository. Figures that summarize the reservoir heat production, temperature drawdown, and the probability of meeting targeted building heating demands with the produced heat and fluid temperatures are provided.

This dataset contains input data, code, ReadMe files, output data, and figures that summarize the results of a stochastic analysis of geothermal reservoir production from two potential geothermal reservoirs that were evaluated for the Cornell University Deep Direct-Use project. These potential reservoirs are the Trenton-Black River (TBR) from 2.27-2.3 km depth, and basement rocks from 3.0-3.5 km depth and 3.5-4.0 km depth. Several utilization scenarios consisting of different injection fluid temperatures and flow rates were evaluated for each reservoir. Uncertainty in geologic properties, thermal properties, economic costs, and utilization efficiencies were evaluated using a Monte Carlo analysis of the reservoir simulations. Some reservoir simulations of the TBR were completed using the TOUGH2 software, as implemented in PetraSIM. The PetraSIM run files and associated data are provided with this submission. All other reservoir simulations were completed using the GEOPHIRES software, with some modifications to complete the uncertainty analyses. ReadMe files that describe additions to GEOPHIRES, the GEOPHIRES input data, and the output data are all provided, and references are provided to the code repository. Figures that summarize the reservoir heat production, temperature drawdown, and the probability of meeting targeted building heating demands with the produced heat and fluid temperatures are provided.

Preliminary geothermal reservoir simulations were performed using a homogeneous static model to evaluate and understand the effects of fluid and rock properties that could influence the delivery of thermal energy in a doublet system. A 5000 feet by 5100 feet by 500 feet homogeneous model having a constant porosity and permeability of 20% and 100 mD was used to perform preliminary geothermal reservoir simulations. The model was discretized in the x-, y-, and z-directions into 100, 101, and 100, gridblocks. Two wells were placed on the opposite ends of the central column of the discretized model. One of the wells was designated as a producer and the other an injector. Equal volumes of water was extracted and then injected into the reservoir via the production and injection wells. Water was extracted at a temperature of 109 deg F and re-injected at 50 deg F at the 1000 bbl/day. The files attached contains the input and output files of this simulation case. The input and some of the output files can be viewed in any text editor.

Preliminary geothermal reservoir simulations were performed using a homogeneous static model to evaluate and understand the effects of fluid and rock properties that could influence the delivery of thermal energy in a doublet system. A 5000 feet by 5100 feet by 500 feet homogeneous model having a constant porosity and permeability of 20% and 100 mD was used to perform preliminary geothermal reservoir simulations. The model was discretized in the x-, y-, and z-directions into 100, 101, and 100, gridblocks. Two wells were placed on the opposite ends of the central column of the discretized model. One of the wells was designated as a producer and the other an injector. Equal volumes of water was extracted and then injected into the reservoir via the production and injection wells. Water was extracted at a temperature of 109 deg F and re-injected at 50 deg F at the 1000 bbl/day. The files attached contains the input and output files of this simulation case. The input and some of the output files can be viewed in any text editor.

This is a link to the open access, published dataset and modeling that supports a feasibility study of Reservoir Thermal Energy Storage (RTES) in the Portland Basin, Oregon, USA. Citation: Burns, E.R., 2020, SUTRA model used to evaluate Saline or Brackish Aquifers as Reservoirs for Thermal Energy Storage in the Portland Basin, Oregon, USA: U.S. Geological Survey data release, https://doi.org/10.5066/P9A6D6XM.