WELL LOGS DATA PREDICTION OF THE NAHR UMR AND MISHRIF FORMATIONS IN THE WELL NOOR-10, SOUTHERN IRAQ

Abbas Mohammed

doi:10.46717/igj.53.2a.4rw-2020-08-04

Abstract

Well logs data are the most widely used data to evaluate subsurface rocks, their petrophysical properties include porosity, permeability and fluid saturation. They are essential for the hydrocarbon reserves estimations and perforation zones determination for production purposes and fields development. Well logging operations of the targeted reservoirs could not be done in NO-10 Well, Noor Oilfield, Southern Iraq due to some problems related to the well condition. The gamma-ray and sonic logs were the only recorded logs, while neutron, density and deep resistivity logs are missed. The missing neutron, density and deep resistivity logs of the Early Cretaceous Nahr Umr Sandstone and the Late Cretaceous Mishrif formations of the well NO-10 were produced and compared together using the Artificial Neural Network ANN in Petrel software. The results show that the total correlation of the ANN Nahr Umr model for the neutron, density and deep resistivity logs are 0.81, 0.49 and 0.51 respectively. Interestingly, the ANN Mishrif Formation model recorded 0.88, 0.92 and 0.81 for neutron, density and resistivity logs respectively. The results show excellent relationships between the original and the predicted logs in the Mishrif model, unlike the Nahr Umr model expect in ANN of the neutron log. It was expected that the total relationships are low in Nahr Umr due to the lithology variation that includes interbedded consolidated and unconsolidated sandstone interbedded with the shale. It is also observed that the gamma log shows low values and the caliper logs is smoothed in the Mishrif. In contrast, the Nahr Umr sandstone logs show that many washouts have occurred. Therefore, logs’ responses highly possible to be affected in the Nahr Umr Formation which leads to a decreasing in the coefficient of determinations.

Highlights

The Noor-10 well was drilled in the Noor Oilfield to produce hydrocarbons from the Nahr Umr sandstone
The predicted neutron log was added to the input data for the step which is density log prediction step and the same steps of prediction of NPHI were applied to the Artificial Neural Network (ANN) model of prediction of the RHOB as well as the LLD logs (Fig. 3)
To assess the results and to check their validation, the predicted NPHI log plotted against the original NPHI log of the wells that selected in this ANN model (Noor-1, Noo1-7 and Noor-13) (Fig. 4a, b and c)

Summary

Introduction

The Noor-10 well was drilled in the Noor Oilfield to produce hydrocarbons from the Nahr Umr sandstone. During drilling the third hole-section (83/8 " section) that contains the reservoirs layers that include the Mishrif and Nahr Umr formations, a problem has occurred, the casing pipes collapsed from the depth of 2318-2333. For the oil company’s, it is essential to determine the best hydrocarbon zone and to estimate the hydrocarbon accumulations for exploration and development stages This cannot be done without the calculations of petrophysical properties (including porosity and fluid saturation) and the numerical models. This can be much challenging in siliciclastic sediments such as in Nahr Umr Formation that contains friable and non-friable sandstone interbedded with shale which makes it difficult to determine the reservoir layers. The predicted logs data can, be used for formations evaluation and to determine the best possible oil zones

Objectives

Methods

Results

Discussion

Conclusion