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Monitoring of a well and the surrounding reservoir performances is a crucial component in evaluating on-going and planning future well and field operations. This is carried out at all stages of a well life-span: from exploration to production and, sometimes, after abandonment. Despite tremendous progress in reservoir simulations, simple and fast techniques for well-reservoir performance evaluation are still demanded in the industry, especially in the context of the vast amount of permanent well monitoring data continuously accumulated. Such techniques are of special interest for on-the-fly well monitoring to detect and alarm about deteriorating performance issues. Installation of permanent pressure gauges in many wells motivated development of time-lapse Pressure Transient Analysis (PTA), capable of revealing and monitoring of different factors governing well performance and reservoir production. The paper describes PTA-based metrics introduced in the context of automated interpretation of time-lapse pressure responses and their derivatives. The paper begins with a review of time-lapse PTA applications in the oil and gas industry and examples of patterns formed by the time-lapse pressure transients and their derivatives in the log–log scale. Then, integral-based PTA-metrics for well-reservoir performance analysis are introduced. The metrics enable to distinguish between reservoir and well-reservoir connection contributions to a well’s performance using the Bourdet derivative, while avoiding the need for selecting and matching of a well-reservoir model. The metrics were further tested with synthetic well models and field cases. The testing demonstrated high accuracy of the metrics for the cases of vertical wells with stable transient patterns. Testing for the horizontal well cases has confirmed reliability of the metrics for the stable patterns, while change of the patterns may reduce the metrics reliability. Model independence and using only pressure and rate measurements as input data are the main advantages of the metrics for integration into automated interpretation workflows and on-the-fly analysis intensively developed in the industry.
Monitoring of a well and the surrounding reservoir performances is a crucial component in evaluating on-going and planning future well and field operations. This is carried out at all stages of a well life-span: from exploration to production and, sometimes, after abandonment. Despite tremendous progress in reservoir simulations, simple and fast techniques for well-reservoir performance evaluation are still demanded in the industry, especially in the context of the vast amount of permanent well monitoring data continuously accumulated. Such techniques are of special interest for on-the-fly well monitoring to detect and alarm about deteriorating performance issues. Installation of permanent pressure gauges in many wells motivated development of time-lapse Pressure Transient Analysis (PTA), capable of revealing and monitoring of different factors governing well performance and reservoir production. The paper describes PTA-based metrics introduced in the context of automated interpretation of time-lapse pressure responses and their derivatives. The paper begins with a review of time-lapse PTA applications in the oil and gas industry and examples of patterns formed by the time-lapse pressure transients and their derivatives in the log–log scale. Then, integral-based PTA-metrics for well-reservoir performance analysis are introduced. The metrics enable to distinguish between reservoir and well-reservoir connection contributions to a well’s performance using the Bourdet derivative, while avoiding the need for selecting and matching of a well-reservoir model. The metrics were further tested with synthetic well models and field cases. The testing demonstrated high accuracy of the metrics for the cases of vertical wells with stable transient patterns. Testing for the horizontal well cases has confirmed reliability of the metrics for the stable patterns, while change of the patterns may reduce the metrics reliability. Model independence and using only pressure and rate measurements as input data are the main advantages of the metrics for integration into automated interpretation workflows and on-the-fly analysis intensively developed in the industry.
Reservoir connectivity over production timescales is a key uncertainty impacting estimated ultimate recover (EUR) per well, and ultimately the economics of a development, but is difficult to address without production data (particularly where the reservoir is poorly defined by seismic). While appraisal well tests can be designed to help predict the performance of future development wells, high rig costs in deepwater means the test duration is often insufficient to investigate the volume that would be accessed under production conditions. Recoverable resources from a recent deepwater gas discovery were dependent on demonstrating significant reservoir connectivity and net reservoir volume; however, this was complicated by a lower delta plain interval that was dominated by sub-seismic reservoir elements. This paper describes the acquisition and interpretation of long-term pressure build-up data in a plugged and abandoned deepwater appraisal well. To accomplish the test objectives at an acceptable cost, we turned to a novel combination of well testing, wireless gauge technology and material balance techniques to allow the collection and interpretation of reservoir pressure data over a planned period of 6 to 15 months following the well test. The final build-up duration was 428 days (14 months). Three interpretation methods of increasing complexity were used to provide insights into the reservoir. Firstly, material balance was used to produce an estimate of the minimum connected reservoir volume. The advantage of material balance is that it requires very few input assumptions and produces a high confidence result. Secondly, we used analytical models in commercial pressure transient analysis software to investigate near wellbore properties and distances to boundaries. Finally, we used finite difference simulation models to investigate reservoir properties and heterogeneity throughout the entire tested volume. With increasing model complexity came additional insights into the reservoir properties and architecture but reduced solution uniqueness. A key complication for the interpretation of the recorded pressure data was the potential for gauge drift to occur – this was incorporated into the uncertainty range used in all three interpretation methods. The observed relative performance for the various gauges used during the well test is also reported in this paper.
Interference testing is a common tool for addressing reservoir connectivity and compartmentalization risks. Due to the high costs of deep-water and ultra-deep-water extended well testing, this type of test is rarely performed during the appraisal phase and is usually postponed until the start of the field development. With the infrastructure in place, testing can be carried out with minimum planning and at a minimum cost. This is generally acceptable for fields with a lower subsurface complexity. However, for complex turbidite fields, this information becomes critical at the appraisal and early development planning stages to reduce the risks in depletion optimization and production infrastructure planning. To make testing practical, it has to be performed in a way that minimizes rig time and de-risks collection of required data. To optimize the interference test design for the West Africa deep-water field appraisal phase, a simulation study was carried out to assess the impact of major uncertainties. A fine-scale 3D simulation model was used due to high heterogeneity and complex connectivity between individual channels and channel complexes. Impact of the drawdown rate, flow duration, tidal effect amplitude, OWC, faults transmissibility, absolute permeability, reservoir pore volume, and zones connectivity on interference time for different selections of test and observation wells were assessed through the sensitivity runs. Results were analyzed to get a better understanding of reservoir dynamic response such as pressure travel time and potential interference between zones. Based on this study a flexible interference test plan was defined that ensures optimal rig use and minimal risk of sub-optimal dataset collection. This plan embeds both pre-test decisions and real-time decisions that depend on early time observations. An optimal test and observation wells setup that provides a balance between the rig time and value of information will depend on the planned appraisal well results and is one of the decisions to be finalized before the test. However, decisions on flow duration adjustment and consequent data monitoring in the observation wells will be made based on a set of early time events identified from the sensitivity of pressure interference response between different zones and wells. The proposed uncertainty driven approach provides an obvious advantage over the common test design based on the "best technical estimate" model. It also provides a better basis for test feasibility decision and cost-effective implementation.
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