Production Forecasting of an Unstable Compacting Chalk Field Using Uncertainty Analysis
- T. Hegdal (Enterprise Oil Norge Ltd.) | R.T. Dixon (Enterprise Oil Norge Ltd.) | R. Martinsen (Amoco Norway Oil Co.)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- June 2000
- Document Type
- Journal Paper
- 189 - 196
- 2000. Society of Petroleum Engineers
- 5.6.3 Deterministic Methods, 5.3.4 Integration of geomechanics in models, 4.6 Natural Gas, 5.7.2 Recovery Factors, 4.1.5 Processing Equipment, 1.6 Drilling Operations, 2 Well Completion, 5.1.2 Faults and Fracture Characterisation, 5.6.9 Production Forecasting, 5.7.4 Probabilistic Methods, 2.2.2 Perforating, 4.5 Offshore Facilities and Subsea Systems, 1.10 Drilling Equipment, 5.8.7 Carbonate Reservoir, 3 Production and Well Operations
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Past years' forecasting performance has demonstrated that single "most likely" (deterministic) prediction of future production, without quantifying the associated uncertainties, is inadequate for management and planning purposes. Based on this an effort was initiated to improve the forecasting methodology and procedures with special emphasis on quantifying the uncertainty in short-term production forecasting (STPF).
The Valhall field, offshore Norway, presented special problems for production forecasting because many unusual events affect production, even for STPF. The soft compacting reservoir chalk causes well collapses and chalk influxes and makes drilling difficult. Modeling of reservoir fracturing and therefore well performance is also uncertain.
A probabilistic forecasting approach was adopted using a customized spreadsheet and commercially available statistical analysis add ins which allowed deterministic forecasting, partially probabilistic analysis, or fully integrated uncertainty analysis. Uncertainties were characterized by distributions based on historical data where possible.
Communication and integration of knowledge were also key success factors since the process required input from several departments and many individuals to ensure that the "company knowledge" was fully reflected. A "common language" to communicate uncertainty and an auditable process to ensure buy in and consistency were also critical.
The Valhall field is a high porosity naturally fractured chalk reservoir located 290 km offshore, in the southwest corner of the Norwegian North Sea. The field was discovered in 1975, with first oil in October 1982. Production drilling is currently ongoing from two drilling rigs, and is expected to result in peak production from Valhall in 2000 from a total of 49 wells.
The oil originally in place is approximately 2,350 mmSTB, located in two main reservoir layers, the Tor formation and the Hod formation. Due to the weakness of the high porosity chalk and the very low original net stress, the Tor formation exhibits exceptional drive energy through pore collapse and compaction.1-3 The expected field recovery factor under primary depletion is close to 28%.
The downside of the compaction drive is movement of the reservoir and overburden by approximately 25 cm/yr at the center of the subsidence bowl, causing wells to deform and ultimately collapse. Furthermore, the soft high porosity chalk is prone to mechanical failure under drawdown, leading to solid influx into the wells. The well failures at Valhall play a dominant role in the overall uncertainty related to STPF, but drilling time and initial rates are also significant contributors to the total uncertainty. The historical production and Enterprise's STPFs, presented in Fig. 1, reflect the difficulty in predicting these uncertainties deterministically. A cyclical trend of over-, then underpredicting, is seen with increased error with increased activity. With the installation of a new wellhead platform in 1996, the Valhall well operation went from one to two drilling rigs, and this increased the uncertainty in the production forecasting. Past years' forecasting performance has demonstrated that single most likely (deterministic) prediction of future production, without quantifying the associated uncertainties, is inadequate for management and planning purposes. Based on this an effort was initiated to improve the forecasting methodology and procedures with special emphasis on quantifying the uncertainty in STPF.
Although the model and principles applied to probabilistic forecasting are not sophisticated as such, the integration and management of all elements in the process make the approach relatively complex. A comprehensive understanding of the input data, that is, the elements generating uncertainty, is essential to improve the quality of the production forecast.
The particular production problems experienced at Valhall have made production forecasting very challenging. The random nature of the well failures makes the range of possible outcomes for a given production scenario wider and less predictable than is normally the case. To improve management of the uncertainty, an improvement project was defined with the following objectives:
a complete review of the STPF process to identify areas for improvement (tools, communication, roles, and responsibilities, etc.);
development of procedures and methodology for STPF;
inclusion of statistical methods (i.e., probabilistic model) in order to quantify the uncertainties;
a strong focus on the description of the input parameters and distributions;
development of a fit for purpose STPF tool with a balance between flexibility and ease of use, and level of detail and complexity.
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