Optimized Well Modeling of Liquid-Rich Shale Reservoirs

Juell, Aleksander; Whitson, Curtis Hays

doi:10.2118/166380-ms

Cited by 13 publications

(2 citation statements)

References 3 publications

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“…The wellbore flowing pressure will be lower than the dew point pressure. Juell and Whitson (2013) did simulation work to find optimal operation conditions for gas condensate shale reservoirs in the depletion mode. They found that the optimal production strategy for wells producing from highly undersaturated gas condensate reservoirs is likely to have an initial period where the flowing pressure equals the saturation pressure, followed by a gradual increase in drawdown, towards the minimum bottom-hole pressure that is operationally possible.…”

Section: Gas Injection In Gas Condensate Reservoirsmentioning

confidence: 99%

Enhanced oil recovery in shale reservoirs by gas injection

Sheng

2015

Journal of Natural Gas Science and Engineering

271

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The current available technique to produce shale oil and gas condensate is through primary depletion using horizontal wells with multiple transverse fractures. The oil recovery factor is only a few percent. There is a big prize to be claimed in terms of enhanced oil recovery (EOR). Because gas price is low and oil price is high, maximizing liquid oil production from gas condensate reservoirs becomes shale producers' top interest. This paper provides the status of enhanced oil recovery (EOR) in shale oil and gas condensate reservoirs by gas injection. It starts with the discussion of possible EOR options in shale reservoirs. For the gas injection option, the huff and puff mode is compared with the gas flooding mode. Different modes of water injection in shale oil reservoirs are also compared. The discussion and comparison show that gas injection is more feasible in shale reservoirs than waterflooding and any other EOR methods. The rest of the paper focuses on review of gas injection in shale reservoirs, which covers the following. • Mechanisms of gas injection • Experimental results on huff and puff gas injection • Simulation results on huff and puff gas injection • Gas injection in gas condensate reservoirs This paper summarizes the EOR efforts which has been made in the industry and provides the direction for the industry future efforts to maximize liquid oil production.

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Section: Gas Injection In Gas Condensate Reservoirsmentioning

confidence: 99%

Enhanced oil recovery in shale reservoirs by gas injection

Sheng

2015

Journal of Natural Gas Science and Engineering

271

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“…SP models typically assume each hydraulic fracture unit is identical, so only a single unit must be modeled, and simple scale-up can be applied (e.g. Juell and Whitson, 2013).…”

Section: Reservoir Simulation -Well History Matching (Hm)mentioning

confidence: 99%

Shale Reserve Forecasting - Model Consistency and Uncertainty

Whitson¹,

Coll

Dahouk³

et al. 2016

All Days

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Three general categories of modeling are traditionally used to provide shale reserve forecasting -(1) decline curve analysis (DCA), (2) rate-time analysis (RTA), and (3) numerical model history matching (HM). The focus of this paper is aligning each of the three modeling approaches to ensure maximum consistency in terms of fundamental reservoir description, including (but not limited to) initial fluid in place, reservoir rock properties, PVT, well completion factors, fracture area and conductivity, well controls, and definition of infinite-acting and boundary-dominated flow regimes. The HM model approach, though more rigorous, is time consuming and cannot be used for the hundreds of wells in a typical shale field. We recommend, as have others, that history-matched numerical models be used to help calibrate RTA and DCA models in a consistent manner for all wells. Once a consistent model framework is achieved, reserve forecasting can be better understood by regulators, engineering and reserve teams within the operating company and their partners. Furthermore, a consistent modeling framework can provide more reliable uncertainty analysis to establish probabilistic reserves estimates in terms of P90-P50-P10 values (1P-2P-3P).Modeling methods used in forecasting shale reserves are based on production data that includes rates and pressures. DCA applies the boundary-dominated methods such as Arps, where multiple time regions are used to capture infinite-acting and boundary-dominated flow. RTA uses dimensionless pressure and rate solutions applicable to horizontal wells with multiple fractures, including superposition, pseudopressure and pseudotime. Numerical models solve the complex set of differential equations describing multiphase fluid flow using a properly-selected grid refinement (e.g. near fractures) and, in some cases, a dual porosity/dual permeability treatment of fracture-matrix interaction.

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Gaussian Processes for history-matching: application to an unconventional gas reservoir

et al. 2017

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The process of reservoir history-matching is a costly task. Many available history-matching algorithms either fail to perform such a task or they require a large number of simulation runs. To overcome such struggles, we apply the Gaussian Process (GP) modeling technique to approximate the costly objective functions and to expedite finding the global optima. A GP model is a proxy, which is employed to model the input-output relationships by assuming a multi-Gaussian distribution on the output values. An infill criterion is used in conjunction with a GP model to help sequentially add the samples with potentially lower outputs. The IC fault model is used to compare the efficiency of GP-based optimization method with other typical optimization methods for minimizing the objective function. In this paper, we present the applicability of using a GP modeling approach for reservoir history-matching problems, which is exemplified by numerical analysis of production data from a horizontal multi-stage fractured tight gas condensate well. The results for the case that is studied here show a quick convergence to the lowest objective values in less than 100 simulations for this 20-dimensional problem. This amounts to an almost 10 times faster performance compared to the Differential Evolution (DE) algorithm that is also known to be a powerful optimization technique. The sensitivities are conducted to explain the performance of the GP-based optimization technique with various correlation functions

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Optimized Well Modeling of Liquid-Rich Shale Reservoirs

Cited by 13 publications

References 3 publications

Enhanced oil recovery in shale reservoirs by gas injection

Enhanced oil recovery in shale reservoirs by gas injection

Shale Reserve Forecasting - Model Consistency and Uncertainty

Gaussian Processes for history-matching: application to an unconventional gas reservoir

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