[my shale ①]RESERVOIR MODELING OF NEW ALBANY SHALE

非常规能源

硕士论文作者：
Kalantari-Dahaghi, Amirmasoud

指导老师：
Shahab D. Mohaghegh, PhD., Chair
Samuel Ameri, PhD.
Razi Gaskari, PhD.

完成时间
May 2010

摘要
The intent of this study is to reassess the potential of New Albany Shale formation using a novel and integrated workflow, which incorporates field production data and well logs using a series of traditional reservoir engineering analyses complemented by artificial intelligence & data mining techniques. The model developed using this technology is a full filed model and its objective is to predict future reservoir/well performance in order to recommend field development strategies. The impact of different reservoir characteristics such as matrix porosity, matrix permeability, initial reservoir pressure and pay thickness as well as the length and the orientation of horizontal wells on gas production in New Albany Shale have been presented. The study was conducted using publicly available numerical model, specifically developed to simulate gas production from naturally fractured reservoirs.  The study focuses on several New Albany Shale (NAS) wells in Western Kentucky. Production from these wells is analyzed and history matched. During the history matching process, natural fracture length, density and orientations as well as fracture bedding of the New Albany Shale are modeled using information found in the literature and outcrops and by performing sensitivity analysis on key reservoir and fracture parameters. Sensitivity analysis is performed to identify the impact of reservoir characteristics and natural fracture aperture, density and length on gas production. Then, the history-matched results of 87 NAS wells have been used to develop a full field reservoir model using an  integrated workflow, named Top-Down, Intelligent Reservoir Modeling. In this integrated workflow unlike traditional reservoir simulation and modeling, we do not start from building a geo-cellular model. Top-Down intelligent reservoir modeling starts by analyzing the production data using traditional reservoir engineering techniques such as Decline Curve Analysis, Type Curve Matching, Single-well History Matching, Volumetric Reserve Estimation and Recovery Factor. These analyses are performed on individual wells in a multi-well New Albany Shale gas reservoir in Western Kentucky that has a reasonable production history. Data driven techniques are used to develop single-well predictive models from the production history and the well logs (and any other available geologic and petrophysical data).

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