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Temperature Prediction Model for Horizontal Well with Multiple Fractures in Shale Reservoir

Fracture diagnostics is a key technology for well performance prediction of a horizontal well in a shale reservoir. The combination of multiple fracture diagnostic techniques gives reliable results, and temperature data has potential to provide more reliability on the results. In this work, we show an application of a temperature prediction model for a horizontal well with multiple hydraulic fractures in order to investigate the possibility of evaluating reservoir and hydraulic fracture parameters using temperature data. The model consists of wellbore model and reservoir model.

The wellbore model was formulated based on mass, momentum and energy balance. The reservoir flow model was solved by a numerical reservoir simulation, and the reservoir thermal model was formulated by transient energy balance equation considering viscous dissipation heating and temperature variation caused by fluid expansion besides heat conduction and convection. The reservoir flow and reservoir thermal model were coupled with the wellbore model to predict temperature distribution in a horizontal well considering boundary conditions at the contact of reservoir and wellbore. In the reservoir system, primary hydraulic fractures which are transverse to the horizontal well were modeled with thin grid cells explicitly, and the hydraulically-induced fracture network around the horizontal well was modeled as higher permeable zone to unstimulated matrix zone. The reservoir grids between two primary fractures were logarithmically spaced in order to capture transient flow behavior. We applied the model to synthetic examples: horizontal well with identical five fractures and with different five fractures. The results show two fundamental mechanisms: heat conduction between formation and wellbore fluid at non-perforated zone, and wellbore fluid mixing effect at each fracture. The synthetic example with identical fractures shows that fracture locations affect wellbore temperature distribution because of fluid mixing effect between reservoir inflow and wellbore fluid. And also, the synthetic example with different fractures shows that the fracture heterogeneity causes different magnitude of temperature change due to inflow variation per fracture. In addition, the model was applied to synthetic examples without network fracture region in order to find the effects by the network. It reveals that under constant rate condition, network fracture masks large temperature change due to small pressure change at the contact between fracture and formation, and that under constant BHP condition, network fracture augments temperature change with the increase of flow rate in wellbore and inflow rate from reservoir.

Sensitivity studies were performed on temperature distribution to identify influential parameters out of the reservoir and hydraulic fracture parameters including reservoir porosity, reservoir permeability, fracture half-length, fracture height, fracture permeability, fracture porosity, fracture network parameters, and fracture interference between multiple clusters. In this work, in order to find contributions by a target fracture, temperature change sensitivity is evaluated. Single fracture case reveals that fracture permeability, network fracture parameters and fracture geometries are primary influential parameters on temperature change at the fracture location. And also, multiple fractures case shows that temperature change is augmented with the increase of fracture geometry and is decreased with the increase of fracture permeability. These results show the possibility of using temperature to determine these sensitive parameters, and also the quantified parameter sensitivities provide better understandings of the temperature behavior of horizontal well with multiple fractures.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/149366
Date03 October 2013
CreatorsYoshida, Nozomu
ContributorsHill, Alfred Daniel, Zhu, Ding, Sun, Yuefeng
Source SetsTexas A and M University
LanguageEnglish
Detected LanguageEnglish
TypeThesis, text
Formatapplication/pdf

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