Identification of Favorable Zones of Gas Accumulation via Fault Distribution and Sedimentary Facies: Insights From Hangjinqi Area, Northern Ordos Basin

Abstract

The Hangjinqi area was explored for natural gas around 40 years ago, but the efficient consideration in this area was started around a decade ago for pure gas exploration. Many wells have been drilled, yet the Hangjinqi area remains an exploration area, and the potential zones are still unclear. The Lower Shihezi Formation is a proven reservoir in the northern Ordos Basin. This study focuses on the second and third members of the Lower Shihezi Formation to understand the controlling factors of faults and sedimentary facies distribution, aimed to identify the favorable zones of gas accumulation within the Hangjinqi area. The research is conducted on a regional level by incorporating the 3D seismic grid of about 2500 km2, 62 well logs, and several cores using seismic stratigraphy, geological modeling, seismic attribute analysis, and well logging for the delineation of gas accumulation zones. The integrated results of structural maps, thickness maps, sand-ratio maps, and root mean square map showed that the northwestern region was uplifted compared to the southern part. The natural gas accumulated in southern zones was migrated through Porjianghaizi fault toward the northern region. Well J45 from the north zone and J77 from the south zone were chosen to compare the favorable zones of pure gas accumulation, proving that J45 lies in the pure gas zone compared to J77. Based on the faults and sedimentary facies distribution research, we suggest that the favorable zones of gas accumulation lie toward the northern region within the Hangjinqi area.

The potential of offshore Nile Delta Basin natural gas reserves: a case study of Messinian reservoir in Baltim field

“…Moreover, the construction of lithofacies maps (e.g., sand-ratio maps) as well as isoparametric maps are extremely recommended to examine the distribution of the sedimentary facies plus the petrophysical properties within Baltim field. Accordingly, the favorable gas zones will be accurately delineated (Anees et al 2022;Ali et al 2022).…”

Application of Machine Learning for Lithofacies Prediction and Cluster Analysis Approach to Identify Rock Type

“…The Palaeocene Girdo (Ranikot) Formation marine shales serve as the top seal for the Khadro Formation reservoir sand, which is present throughout the field and offers a durable continuous pressure barrier, even when cut by thrusts. Because the basal Khadro Formation shales form a good seal from the underlying Pab Formation reservoir, Khadro Formation sandstones are anticipated to be closer to virgin field pressures, unless depleted by production from Khadro Formation producing wells [22][23][24][25].…”

“…This is a linear mathematical strategy for condensing a big set of variables (seismic characteristics) into a smaller set that retains the majority of the independent information variation found in the larger data set [18,19]. One can distinguish sedimentary units with similar log characteristics by gathering data from several good logs [20][21][22][23][24]. In the literature, sedimentary units established on this basis and characterized from wireline logs were referred to as electrofacies or logfacies [17,[25][26][27].…”

Sand-ratio distribution in an unconventional tight sandstone reservoir of Hangjinqi area, Ordos Basin: Acoustic impedance inversion-based reservoir quality prediction

“…The Hangjinqi area lies in the Ordos Basin. Pure gas exploration began here a decade ago (Anees et al, 2022b). Hangjinqi has several wells, however, the distribution of sand-ratio in many zones is unclear.…”