The Impact of Geologic Reservoir Characterization on the Flow Unit Modeling at the Kern River Field, California, Usa

Ginger, Elliott P.; Almon, William R.; Longacre, Susan A.; Huggins, C.A.

doi:10.2110/scn.95.34.0317

Cited by 7 publications

(19 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The reservoir is homoclinal, dipping southwest into the basin. The simple homoclinal geometry shown in Figure 1 is locally disrupted by normal faults (Kuespert and Sanford, 1990;Ginger et al, 1995). Some of those faults, such as the Kern Front, Poso Creek, and China Grade faults, help define the field boundaries (Kodl and Eacmen, 1990;.…”

Section: Location and Geologymentioning

confidence: 99%

“…Some of those faults, such as the Kern Front, Poso Creek, and China Grade faults, help define the field boundaries (Kodl and Eacmen, 1990;. Internally, a number of faults have been identified based on well-log correlation and 3D seismic studies, and are recognized to affect productivity by acting as local baffles and barriers to fluid flow (Ginger et al, 1995). Magnitude of fault offset on field-bounding faults is typically >100 ft (>30 m), whereas internal fault offsets are from 25 to 50 ft (7.6 to 15.2 m).…”

Section: Location and Geologymentioning

confidence: 99%

“…The eastern boundary is more puzzling: strata in the Kern River Formation are exposed in outcrop and subcrop to the east. Previous workers have argued for hydrodynamic trapping of Kern River Formation oils as there is no obvious seal (Kodl and Eacmen, 1990;Kuespert and Sanford, 1990;Ginger et al, 1995).…”

Section: Location and Geologymentioning

confidence: 99%

“…There are nine producing zones within the Kern River Formation ( Figure 2B), and all zones represent fluvial depositional environments (Miller, 1986;Brelih and Kodl, 1990;Ginger et al, 1995). These nine zones are defined based on sandstone and mudstone packages that can be traced, with difficulty, across the field.…”

Section: Location and Geologymentioning

confidence: 99%

“…The OOIP is quoted as 3-4 BBO in the literature, such that perception of current recovery is impacted by that lack of clarity. Hurst (1980) cites 4 BBO, and Ginger et al (1995) cite 3.8 BBO OIP. Swartz et al (2008) cite an OOIP of >3.5 BBO in their summary of the field.…”

Section: Field Historymentioning

confidence: 99%

See 4 more Smart Citations

Creation and utility of a large fit-for-purpose earth model in a giant mature field: Kern River field, California

Beeson¹,

Hoffman²,

Larue³

et al. 2014

Bulletin

View full text Add to dashboard Cite

A B S T R A C TReservoir management studies of California's Kern River field rely on a full-field 155-million cell three-dimensional (3D) earth model. This full-field model provides input for reserves estimation as well as the identification, targeting, and ranking of remaining opportunities. The earth model is regarded as "fit for purpose" in that characteristics of the model are aligned with specific needs for reservoir management. Normalized resistivity logs from more than 12,000 wells are used to establish lithology and reservoir architecture. Temperature, steam, gas, and oil saturation logs from over 650 boreholes provide regular periodic surveillance for identifying changes in fluids and temperature. Changes in fluid contacts and saturations are integrated with reservoir architecture three times each year. These model updates are important to the development teams for staying current on changes in their project area. The integration of these data provides the basis for linked reserves and resource estimation and the identification and development of remaining opportunities. Kern River reserves and resources are estimated from the model for over 130 internal reporting entities. For asset reservoir management purposes, reserves are updated for over 160,000 entities (based on patterns, zones, and reserves) across the 12-sq-mi (31-sq-km) field. The updated reserves supply input to reserves distribution maps and spreadsheets used for evaluating workover and new development opportunities. Some of these opportunities represent heat mining of untapped hot oil zones whereas other opportunities are cold and require the introduction of steam to mobilize the oil. Using multiple reservoir property characteristics as filter criteria for identifying remaining opportunities is an important tool used at

show abstract

Section: Location and Geologymentioning

confidence: 99%

Section: Location and Geologymentioning

confidence: 99%

Section: Location and Geologymentioning

confidence: 99%

Section: Location and Geologymentioning

confidence: 99%

Section: Field Historymentioning

confidence: 99%

See 3 more Smart Citations

Creation and utility of a large fit-for-purpose earth model in a giant mature field: Kern River field, California

Beeson¹,

Hoffman²,

Larue³

et al. 2014

Bulletin

View full text Add to dashboard Cite

show abstract

Identification of Horizontal Well Placement Using Fuzzy Logic

Popa

2013

SPE Annual Technical Conference and Exhibition

View full text Add to dashboard Cite

Estimated to have over 3.5 billion barrels of original oil in place, the 114 year old Kern River Oil Field was a sleeping giant until the late 1960's when steamflooding began and oil production ramped up from 19,000 to over 142,000 BOPD by the mid 1980's. Kern River Field is now in decline, but still produces over 70,000 BOPD, making it one of the largest onshore oil producers in the continental United States. In 2007 the field's cumulative production reached two billion barrels of heavy oil. With the introduction of horizontal wells in 2007, the production decline curve that had been at approximately 6%, began to flatten and today the decline rate is at 2%. Since the discovery of the field, over 19,000 wells have been drilled with the largest producers, horizontal wells, drilled in the last 6 years.Though the oil production is in decline, new opportunities are continuing to be identified and exploited using a broad array of reservoir management tools. The primary tool utilized for both tactical and strategic planning is a full field 3D reservoir model. The static lithologic framework for this full field model uses over 12,500 normalized resistivity logs. Temperature, steam and oil saturation data from a network of over 650 surveillance wells are periodically incorporated into this model to provide current reservoir conditions. Project teams first identify their opportunities in the full field model using a filtering criteria. For example, horizontal infill wells seeking "hot bottom oil" within partially depleted reservoir intervals can be developed around geo-body criteria including property cut-off values for gas saturation, oil saturation, temperature, resistivity and thickness.The filtering criterion was useful in identifying well locations; however, the pool of candidates significantly declined due to the exclusive nature of the hard cut-off approach. The lack of candidates threatened the continued horizontal drilling program. A Fuzzy Logic approach was considered to deal with the imprecise information and aggregate multiple variables with suitable membership functions. The Fuzzy Inference System (FIS) using the Mamdani model incorporated knowledge rules developed by the asset team. Once developed, the system was run for each grid block of the nine productive formations of the field, generating areas of interest for identification and placement of horizontal wells.The output of the system allowed generation of "quality maps" which revealed target areas with substantial potential of horizontal drilling. Moreover, some of these target areas were not even considered in previous searches. In a first pass, approximately 600 new locations were identified.The paper presents a new approach for identification and placement of horizontal wells using fuzzy logic. In addition to the large number of wells identified, the methodology focused the asset team on high potential areas, as well as offered an objective approach to deal with imprecise and uncertain reservoir information. Due to its success in Kern River, the tech...

show abstract

Heavy Oil Field Development Revitalized through Horizontal and Lateral Re-Entry Wells

Popa

Cassidy

2014

SPE Annual Technical Conference and Exhibition

View full text Add to dashboard Cite

Heavy oil assets represent a significant component of Chevron's portfolio with a continuous potential growth given the well understood recovery mechanism and established processes for reservoir management. Technology advancements such as horizontal drilling and completions enable ingenious and lucrative re-development projects to achieve maximum recovery. This paper describes the success of the reservoir management practices used in one of the company's heavy oil reservoirs to revitalize production and arrest the decline through use of horizontal well drilling and high angle lateral re-entry wells. Deployed in 2013, the new workflow using artificial intelligence enabled a significant step change in the selection outcome of horizontal infill and well re-entry candidate selection. Using this methodology increased production output was realized and it is expected to achieve recovery factors as great as 75% in some of the nine producing sands of the reservoir.With over 20, 000 wells drilled and more than 100 years of production history, the Kern River Field presents an interesting and attractive challenge for reservoir management, identification of widespread development opportunities, and continued optimization. Located in Kern County, California, the heavy oil reservoir consists of nine productive sands, with additional stratigraphic complexity introduced by the braided stream depositional setting. The field is currently produced by steam injection, and the primary production mechanism is gravity drainage.Initial development of the field consisted of vertical well drilling with pattern development as dense as 5/8 acres. The field reached a peak production in 1997 followed by a steep 6% decline driven by a rapidly shrinking number of new recompletion and expansion opportunities. With the introduction of horizontal wells in 2006 and lateral re-entry completions in 2012, the production decline curve flattened and today the decline rate is around 2 %.Prior to 2013 the full field 3D reservoir model was the primary tool used for the identification and selection of horizontal well drilling. While initially successful, the hard cut-off filtering criteria lead to a quick exhaustion of the candidate pool and threatened the future of the program. In December 2012 an intelligent approach to well selection identification was introduced using fuzzy quality maps. This approach expanded the pool of candidates tenfold with more than 600 well locations identified.Building on the quality maps created for the horizontal well identification program, and integrating Voronoi mapping for reserves, engineers were able to identify high potential areas to place lateral re-entry

show abstract

The Impact of Geologic Reservoir Characterization on the Flow Unit Modeling at the Kern River Field, California, Usa

Cited by 7 publications

References 0 publications

Creation and utility of a large fit-for-purpose earth model in a giant mature field: Kern River field, California

Creation and utility of a large fit-for-purpose earth model in a giant mature field: Kern River field, California

Identification of Horizontal Well Placement Using Fuzzy Logic

Heavy Oil Field Development Revitalized through Horizontal and Lateral Re-Entry Wells

Contact Info

Product

Resources

About