Abstract

An onshore gas field (hereafter called the R field—real name not revealed) is in the southeast coast of Tanzania which includes a Tertiary aged shaly sand formation (sand–shale sequences). The formation was penetrated by an exploration well R–X wherein no core was acquired, and there is no layer-wise published data of the petrophysical properties of the R field in the existing literature, which are essential to reserves estimation and production forecast. In this paper, the layer-wise interpretation of petrophysical properties was undertaken by using wireline logs to obtain parameters to build a reservoir simulation model. The properties extracted include shale volume, total and effective porosities, sand fractions and sand porosity, and water saturation. Shale volume was computed using Clavier equation from gamma ray. Density method was used to calculate total and effective porosities. Thomas–Stieber method was used to determine sand porosity and sand fraction, and water saturation was computed using Poupon–Leveaux model. The statistics of the parameters extracted are presented, where shale volume obtained that varies with zones is between 6 and 54% volume fraction, with both shale laminations and dispersed shale were identified. Total porosity obtained is in a range from 12 to 22%. Sand porosity varies between 15 and 25%, and sand fraction varies between 33 and 93% height fraction. Average water saturation obtained is between 32 and 49% volume fraction.

Highlights

  • An onshore gas field is in the southeast coast of Tanzania

  • Clean sand porosity of 26% and pure shale porosity of 16.4% were taken from depth intervals mentioned in shale volume computation Section to develop endpoints of Thomas–Stieber plot

  • The results of shale volume, sand fraction, porosities, and water saturation computed are displayed in Fig. 9 for sample zones

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Summary

Introduction

An onshore gas field (hereafter called the R field—real name not revealed) is in the southeast coast of Tanzania. Properties accounting for and included in models to compute water saturation are electrical conductivity (inverse of resistivity), porosity, formation water salinity, lithology-dependant fitting parameters (cementation or porosity exponent m and saturation exponent n), and temperature (Thomas 2018; Santamarina et al 2019; Hill 2017; Archie 1942) These properties can vary vertically (with depth) and laterally depending on the lithology-type and texture with the degree of sorting, compaction, cementation (e.g., type, quantity, and distribution of shale or clay minerals), and dissolution (Thomas 2018; Lin et al 2017; Gong et al 2016; Zheng et al 2015; Magara 1980; Smith 1971; Athy 1930). The details of established methods are presented in “Appendix A”

Methodology and workflow
Results and discussion
Conclusions and future perspectives
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