In the oil and gas industry today, continuous wellbore data can be obtained with high
precision. This accurate and reliable downhole data acquisition is made possible by
advancements in permanent monitoring systems such as downhole pressure and
temperature gauges and fiber optic sensors. The monitoring instruments are increasingly
incorporated as part of the intelligent completion in oil wells where they provide
bottomhole temperature, pressure and sometimes volumetric flow rate along the
wellbore - offering the promise of revolutionary changes in the way these wells are
operated. However, to fully realize the value of these intelligent completions, there is a
need for a systematic data analysis process to interpret accurately and efficiently the raw
data being acquired. This process will improve our understanding of the reservoir and
production conditions and enable us make decisions for well control and well
performance optimization.
In this study, we evaluated the practical application of an interpretation model,
developed in a previous research work, to field data. To achieve the objectives, we developed a simple and detailed analysis procedure and built Excel user interface for
data entry, data update and data output, including diagnostic charts and graphs. By
applying our interpretation procedure to the acquired field data we predicted temperature
and pressure along the wellbore. Based on the predicted data, we used an inversion
method to infer the flow profile - demonstrating how the monitored raw downhole
temperature and pressure can be converted into useful knowledge of the phase flow
profiles and fluid entry along the wellbore. Finally, we illustrated the sensitivity of
reservoir parameters on accuracy of interpretation, and generated practical guidelines on
how to initialize the inverse process. Field production logging data were used for
validation and application purposes.
From the analysis, we obtained the production profile along the wellbore; the fluid
entry location i.e. the productive and non-productive locations along the wellbore; and
identified the fluid type i.e. gas or water being produced along the wellbore. These
results show that temperature and pressure profiles could provide sufficient information
for fluid identity and inflow distribution in gas wells.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2355 |
| Date | 15 May 2009 |
| Creators | Achinivu, Ochi I. |
| Contributors | ZHU, DING |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | electronic, application/pdf, born digital |
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