Prediction of gas production potential and hydrological properties of a methane hydrate reservoir using ANN-GA based framework

Chanda, Samarjeet; Singh, Randhir

doi:10.1016/j.tsep.2019.04.011

Cited by 10 publications

(2 citation statements)

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“…These reservoir models need to account for multiphase fluid flow, heat transfer, and thermodynamics of hydrate formation and dissociation, in addition to the changing porosity and permeability of the reservoirs. − Therefore, coupled mass and energy balance equations are solved in the simulations, which consider the equilibrium kinetics of hydrate formation and dissociation. ,, Generally, homogeneous reservoirs have been used in simulation studies and only a few studies describe the dynamics of heterogeneous reservoir behavior. , However, the flow properties and initial conditions that are used in the reservoir simulations are not deterministic. − This is because we use small samples of the reservoir rocks from the well to determine these properties from laboratory tests . During the drilling process of a well, a compact core sample is extracted, and subsequently, the laboratory conducts direct measurements of both porosity and permeability. , The flow properties of a reservoir can be estimated by field tests at wells, using indirect methods such as logging, however, this gives information for the areas around the well only. − This technique samples a greater, although still extremely limited volume. It is also possible to use multiple wells to reduce the uncertainty in the log data collected, but that will increase the cost of the testing.…”

Section: Introductionmentioning

confidence: 99%

“…13 During the drilling process of a well, a compact core sample is extracted, and subsequently, the laboratory conducts direct measurements of both porosity and permeability. 14,15 The flow properties of a reservoir can be estimated by field tests at wells, using indirect methods such as logging, however, this gives information for the areas around the well only. 16−18 This technique samples a greater, although still extremely limited volume.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty Propagation in Predicting Recovery from Gas Hydrate Reservoirs: From Reservoir Characteristics to Performance Analysis

Choudhary,

Phirani

2024

Energy Fuels

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The necessity of forecasting recovery from the gas hydrate reservoirs is restricted due to the limiting data availability for reservoir properties, such as porosity and hydrate saturation, used in reservoir models. Predicting recovery becomes essential to determine the feasibility and viability of a reservoir. Therefore, it is paramount to understand uncertainty propagation from reservoir characteristics to reservoir performance by using reservoir simulations. In this work, we explore the uncertainty in reservoir performance due to the uncertainty in reservoir characterization of porosity and saturation. We employ the Monte Carlo method to analyze the impact of uncertainty on gas and water production from a class 2, confined, oceanic methane hydrate reservoirs. We observe that uncertainty in porosity leads to a substantial uncertainty in our prediction of gas recovery until a critical porosity value. If the porosity is higher than the critical porosity value, then the gas production using depressurization does not change significantly. This is attributable to the thermal nature of gas hydrate dissociation in which high porosity means less heat content from the sediments for hydrate dissociation. For the same reason, at the same porosity, variation in hydrate saturation does not lead to a high variation in gas recovery. The uncertainty in porosity leads to a 24% coefficient of variation in cumulative gas production, uncertainty in initial hydrate saturation leads to 3% and their combined uncertainty leads to 20% coefficient of variation in cumulative gas production. Using the cumulative density function of the gas production, we show that our P 90 , P 50 , and P 10 estimates will vary depending on the production time considered for estimation.

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