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Correlation-based EUR prediction of shale oil wells: A case of the Qingcheng Oil Field in the Ordos Basin
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Suiyi Fua, Lingbin Laib, Zhengdong Leib, Qingfu Fengb, Huizhu Xiangb, *, Bo Wangc, Xiulin Houb, Ting Xuec
Petroleum Research | 2026, 11(1) : 63 - 71
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Petroleum Research | 2026, 11(1): 63-71
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Correlation-based EUR prediction of shale oil wells: A case of the Qingcheng Oil Field in the Ordos Basin
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Suiyi Fua, Lingbin Laib, Zhengdong Leib, Qingfu Fengb, Huizhu Xiangb, *, Bo Wangc, Xiulin Houb, Ting Xuec
Affiliations
  • aHalliburton (China) Energy Services Limited, Beijing, 100020, China
  • bResearch Institute of Petroleum Exploration and Development, PetroChina, Beijing, 100083, China
  • cPetroChina Changqing Oilfield Company, Xi'an, 710000, China
Published: 2026-03-10 doi: 10.1016/j.ptlrs.2025.06.001
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Shale reservoirs are characterized by low permeability and a weak capacity for natural seepage. These reservoirs are commonly developed using a combination of horizontal well drilling and fracturing. The production performance of shale oil wells is evaluated through single-well production decline analysis, with the estimated ultimate recovery (EUR) used as an important indicator of the development outcome. This study predicted the EUR of the X233 well zone in the Qingcheng Shale Oil Field in the Ordos Basin. It reviewed the applicability of production forecasting methods to unconventional reservoirs and put forward a correlation-based approach to EUR prediction. The latter was developed by integrating the characteristics of Qingcheng shale oil production with EURs predicted using empirical methods intended for typical wells. The correlation-based approach was also designed on the basis of the relationship between cumulative oil production and the empirically derived EURs. The results suggest that the proposed method rapidly predicts the EUR of a single well using cumulative oil production from the first one, two, and three years of production. The predictions closely align with the empirically derived values, demonstrating the strong practical effectiveness of the approach put forward in this work. To determine its applicability and limitations, this study examined the EUR distribution characteristics of different well classes (Classes I to III). This research provides a simple and effective approach to rapidly predicting the EURs of shale oil wells, significantly reducing computational time and labor costs.

Shale reservoirs  /  Estimated ultimate recovery  /  Production decline  /  Qingcheng Oil Field
Suiyi Fu, Lingbin Lai, Zhengdong Lei, Qingfu Feng, Huizhu Xiang, Bo Wang, Xiulin Hou, Ting Xue. Correlation-based EUR prediction of shale oil wells: A case of the Qingcheng Oil Field in the Ordos Basin[J]. Petroleum Research, 2026 , 11 (1) : 63 -71 . DOI: 10.1016/j.ptlrs.2025.06.001
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Article Info
doi: 10.1016/j.ptlrs.2025.06.001
  • Receive Date：2024-10-22
  • Online Date：2026-10-14
  • Published：2026-03-10
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History
  • Received：2024-10-22
  • Revised：2025-05-29
  • Accepted：2025-06-03
Affiliations
    aHalliburton (China) Energy Services Limited, Beijing, 100020, China
    bResearch Institute of Petroleum Exploration and Development, PetroChina, Beijing, 100083, China
    cPetroChina Changqing Oilfield Company, Xi'an, 710000, China

Corresponding:

* Research Institute of Petroleum Exploration and Development, PetroChina, Beijing, 100083, China. E-mail address: (H. Xiang).
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
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Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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