Determining the drilling mud window by integration of geostatistics, intelligent, and conditional programming models in an oilfield of SW Iran

Abstract

Accurate knowledge of pore and fracture pressures is essential for drilling wells safely with the desired mud weight (MW). Overpressure occurs when the pore pressure is higher than the normal hydrostatic pressure. There is a challenge regarding the pressure studies domain in an oilfield in SW Iran, where lack of geo-mechanical data limits exact mud window calculation. Also, the reservoir generally consists of carbonate rocks and contains no shale interbeds, so mechanical stratigraphy based on Gamma ray could not be applied. This study is to provide safe drilling considering MW to prevent the flow or loss in the vicinity of the new wells in the studied field. In this research, the formation pressures and mud window models are determined by combining geostatistical, intelligent, and conditional programming models and compared with real data. The conditional programming was also used to correct small out-of-range data. The highest correlation between the final effective pressure and velocity cube was observed in lower Fahliyan Formation with 0.86 and Ilam with 0.71.The modeled MW difference ranged between 2.5 and 30 PCF. Also, the maximum modeled MW is 150 PCF in the upper Fahliyan Formation. Heavy mud of more than 130 PCF is suggested for drilling the Khalij member and continues to the end of stratigraphy column. Best observed correlation comparing the drilled and modeled MW, especially achieved in the Fahliyan reservoir Formation with more than 100 PCF and the Ilam Formation with 80–100 PCF. Finally, 3D formation pressures are presented and recommended for further safe drillings.

Determining the petrophysical rock types utilizing the Fuzzy C-means Clustering technique and the concept of hydraulic flow units

“…It has a variable width of up to 6 kilometers in the middle of the field and an average of 4.5 kilometers, which decreases to the east and west slopes. The dimensions of the reservoir at the contact surface of water and oil (2272 m below sea level) are 30 km long and 3.5 km wide, stretching northwest-southeast (Aleali et al, 2013;Hosseini et al, 2023a;Kianoush et al, 2023b;Kianoush et al, 2023a;Michael and Gupta, 2022;NISCO, 2022;Sabouhi et al, 2023). In addition to the Asmari reservoir and sandstone section of Ahwaz, the Bangestan reservoir (Ilam and Sarvak Formations) are also present in this field (AbdollahieFard et al, 2019;Motiei, 1995;Talaie et al, 2023;Tavakkoli and Amini, 2006).…”

Determining the petrophysical rock types utilizing the Fuzzy C-means Clustering technique and the concept of hydraulic flow units

“…It has a variable width of up to 6 kilometers in the middle of the field and an average of 4.5 kilometers, which decreases to the east and west slopes. The dimensions of the reservoir at the contact surface of water and oil (2272 m below sea level) are 30 km long and 3.5 km wide, stretching northwest-southeast (Hosseini et al, 2023b;Hosseini et al, 2023a;Kianoush et al, 2023b;Kianoush et al, 2023a;NISCO, 2022). In addition to the Asmari reservoir and sandstone section of Ahwaz, the Bangestan reservoir (Ilam and Sarvak Formations) are also present in this field (AbdollahieFard et al, 2019;Motiei, 1995;Tavakkoli & Amini, 2006).…”

Determination of electrical facies using MRGC and ANN clustering methods

“…If the lithofacies match the lithofacies, lithofacies can be substituted for lithofacies and applied. Created facies can be later used to predict rock facies in core-free or core-free intervals (Abrar 2011;Frew 2004;Kianoush et al 2022;Kianoush et al 2023b). A practical method for facies analysis is to create a facies classi cation model that splits the log data into a set of log responses that describes sediment and provides sediment separation and identi cation from other sediments.…”