Investigating the effect of hole size, bottom hole temperature, and composition on cement bonding quality of exploratory wells in Iran.

The oil and gas industry's reliance on well cementing practices to ensure well integrity and productivity is a pressing concern, particularly in exploratory wells where unpredictable conditions can lead to subpar cement bonding efficiency. This study addresses the pressing issue of optimizing cementing practices in Iran's exploratory wells, ensuring better well integrity and productivity. The preliminary objective is to investigate the impact of hole size and bottom hole temperature variations on cement bonding efficiency in these wells.

Unraveling time-dependent roof stability dynamics in Iran's coal mines through laboratory-based rock displacement testing.

Roof stability is a critical concern in coal mines, as the potential for roof collapse poses a significant risk to miners' safety and productivity. Roof stability is heavily influenced by the time-dependent properties of the rock mass above the workings. This study uses rock displacement testing to examine the effect of time-dependent properties on roof stability and resistance reduction in coal mines in Iran.

Scaling-up dynamic elastic logs to pseudo-static elastic moduli of rocks using a wellbore stability analysis approach in the Marun oilfield, SW Iran.

Wellbore stability analysis is a critical component of petroleum engineering, evaluating the risks of sanding, reservoir compaction, and casing failures. Laboratory rock mechanical measurements must be scaled up to reservoir scales to achieve accurate results. One challenge lies in upscaling dynamic measurements from petrophysical logs to pseudo-static elastic properties, which has significant implications for oil and gas operations.

Electrical facies of the Asmari Formation in the Mansouri oilfield, an application of multi-resolution graph-based and artificial neural network clustering methods.

Electrofacies analysis conducted the distribution effects throughout the reservoir despite the difficulty of characterizing stratigraphic relationships. Clustering methods quantitatively define the reservoir zone from non-reservoir considering electrofacies. Asmari Formation is the most significant reservoir of the Mansouri oilfield in SW Iran, generally composed of carbonate and sandstone layers.

Hydraulic flow unit and rock types of the Asmari Formation, an application of flow zone index and fuzzy C-means clustering methods.

Rock types are the reservoir's most essential properties for special facies modeling in a defined range of porosity and permeability. This study used clustering techniques to identify rock types in 280 core samples from one of the wells drilled in the Asmari reservoir in the Mansouri field, SW Iran. Four hydraulic flow units (HFUs) were determined for studied data utilizing histogram analysis, normal probability analysis, and the sum of squared errors (SSE) statistical methods.

Geobody estimation by Bhattacharyya method utilizing nonlinear inverse modeling of magnetic data in Baba-Ali iron deposit, NW Iran.

One of the essential geophysical concerns is the estimation of the physical and geometrical parameters of the reserve (geobody), which is done by exploiting the nonlinear inverse modeling of magnetic data. The present study includes preparing and modeling magnetic data to suggest the Baba Ali Iron ore deposit's drilling locations in NW Iran. The area is covered with 1000 points of geomagnetic reading with an almost 5 × 10 m regularly spaces grid trending WE.