Benchmarking of Steamflood Field Projects in Light/Medium Crude Oils
- Alfredo Perez-Perez (PDVSA Intevep) | Marjorie Gamboa (Universidad Central de Venezuela) | Cesar Ovalles (PDVSA Intevep) | Eduardo Manrique (PDVSA Intevep)
- Document ID
- Society of Petroleum Engineers
- SPE Asia Pacific Improved Oil Recovery Conference, 6-9 October, Kuala Lumpur, Malaysia
- Publication Date
- Document Type
- Conference Paper
- 2001. Society of Petroleum Engineers
- 4.1.5 Processing Equipment, 5.4.10 Microbial Methods, 5.4.6 Thermal Methods, 5.3.4 Reduction of Residual Oil Saturation, 5.8.5 Oil Sand, Oil Shale, Bitumen, 2.4.3 Sand/Solids Control, 5.6.4 Drillstem/Well Testing, 5.1 Reservoir Characterisation, 5.2.1 Phase Behavior and PVT Measurements, 4.3.4 Scale, 4.1.2 Separation and Treating, 1.8 Formation Damage
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A benchmarking study on 43 steamflood of light/medium crude oils was performed, to find attractive reservoir characteristics and successful operational practices that are used worldwide. More than 30 successful projects were analyzed and summarized in a database, which included reservoir properties, best operational practices and results obtained. On average, an incremental oil recovery of 19% OOIP was obtained by steamflooding, during a project lifetime of up to seven years.
Based on the successful project characteristics, we developed a model to rank potential reservoirs. Reservoir data were analyzed using standard statistical methods for properties, such as: API gravity, initial oil saturation, reservoir temperature, porosity, initial pressure, depth, net pay, viscosity at reservoir condition, initial (at the beginning of steamdrive)-bubble pressure ratio and average permeability. The statistical model ranked the properties on a standardized score scale. A predicted score close to one hundred indicates a high probability of success. Supported by this numerical model, we selected the La Salina reservoir (La Rosa Formation, Lake Maracaibo, Western Venezuela) as a potentially successful reservoir to apply steamflood technology.
In addition, unsuccessful projects from two different reservoirs (the Naval Petroleum Reserve No. 1, and Buena Vista Hills, both in the USA) were analyzed, to understand the reasons for failure. Several reasons were identified, such as: poor reservoir characterization, thief zones and carbon dioxide formation by decomposition of reservoir minerals.
In 1952, steamflood was initiated as an enhanced oil recovery technique in the Yorba Linda Field in California. This early work determined that steam injection is generally most efficient in highly permeable reservoirs (k > 1 Darcy) and thick sands (greater than 30 feet)1. By the 1970's many fields were benefiting from steamdrive technology; and oil production peaked in the mid 1980's has been fairly constant since1. This production had been almost exclusively from the heavy oil reservoirs (10-22 °API).
Light/medium oil steamflood (LMOSF) also had its roots in California2. In the 1960's, one of the first LMOSF field trials was initiated at the Brea Field near Los Angeles2. Application of steamdrive in medium/light oil reservoir (> 22 °API) now has a prominent position in producing thermal EOR projects3.
Because of the small viscosity (at reservoir conditions) and the large volatility of the light oils, the principal recovery mechanisms are different from those responsible for steamflood recovery of heavy oil4. Figure-1 qualitatively displays the roles that individual mechanisms play on light and heavy oils5-6. Thermal expansion and distillation are the most important for light oil and viscosity reduction plays the primary role for heavy oil1. The beneficial effect of steam for light oils is distillation of light hydrocarbons, which results in small residual oil saturation7.
Additionally, a successful EOR project requires selection of a reservoir, whose characteristics should be appropriate for steamflooding. Steamflood screening guides are useful for this purpose. These have been proposed by various authors8. A review of steamflooding was carried out by Ovalles et al6. Table 1 shows a summary of screening criteria applicable to light/medium crude oil reservoirs. A list of the various screening guides depicted in Table 1 shows that only 6 criteria have been defined as critical properties.
The final goal of this work is to develop a statistical model that can be used to select prospective reservoirs in a more reasonable way than the isolated criteria in Table 1. In this model, each property will be ranked against others based on their relative significance. If successful, the method will lead to better decision about where and how to apply LMSOF projects.
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