Comparison and sensitivity analysis of water saturation models in shaly sandstone reservoirs using well logging data

This study involved an interpretation of wire-line logs in assessing the hydrocarbon capacity of the sandstone reservoir within the gas fields of Kadanwari, Sindh, Pakistan. Wire-line logs from four wells (KD-01, KD-03, KD-10 and KD-11) were used in our research and provided interpretation for thirteen reservoir zones. Reservoir analyses were done for effective porosity (ϕeff), shale content (Vsh), net pay thickness variations, water saturation, and hydrocarbon (Sw and Shc). Hydrocarbon-bearing zones consist of high values of resistivity, permeability, porosity, low water saturation content, and less shale content, indicating the presence of clean sand. The Thomas Stieber model findings show that in lower Goru sand, the laminated form of shale distribution persists. Sub-reservoirs’ petrophysical parameters were analyzed and ranked into a good sand reservoir quality (having ϕeff ∼0.11-0.44%), permeability (∼10.539-477.76 mD), hydrocarbon saturation (having Shc ∼0.59-0.86%), and water saturation (having Sw ∼0.18-0.45%). In the current research Indonesian model has been used to test for water saturation over a shaly-sand reservoir situated in a heterogeneous zone. It was observed that each well exhibited Sw at values lesser than 60%. This is indicative the selected zone has a hydrocarbon potential, and the hydrocarbons are of good quality. Isoparametric maps and crossplots of litho-saturation results reveal variations in the horizontal and vertical petrophysical parameters of the reservoir. The subsurface reservoir geographical distribution is visualized employing isoparametric maps. The fuel treasure in the southwestern section of the study area is enormous, as revealed by the petrophysical investigations, suggesting more well-drilling prospects in the gas fields of the lower Goru Formation situated in Kadanwari. Our research identified a quality hydrocarbon hotspot zone of immense economic value in Southern Kadanwari. In contrast, more research is needed regarding the northeastern section though our present findings suggest the northeastern section should be avoided because of excess shale and high-water concentrations. 

Prediction of Cretaceous reservoir zone through petrophysical modeling: Insights from Kadanwari gas field, Middle Indus Basin

Depositional environment and reservoir characterization of the deep offshore Upper Miocene to Early Pliocene Agbada Formation, Niger delta, Nigeria


 Oil production from shale and tight formations will increase to more than 6 million barrels per day (b/d) in the coming decade, making up most of total U.S. oil production (> 50%). However, achieving an accurate formation evaluation of shale faces many complex challenges. One of the complexities is the accurate estimation of shale properties from well logs, which is initially designed for conventional reservoirs. When we use the well logs to obtain shale properties, they often cause some deviations. Therefore, in this work, we combine cores and well logs together to provide a more accurate guideline for estimation of total organic carbon, which is primarily of interest to petroleum geochemists and geologists.
 Our work is based on Archie's equation. Resistivity log will lead to some incorrect results, such as total resistivity, when we follow the conventional interpretation procedure in well logs. Porosity is another complex parameter, which cannot be determined only by well log, i.e. density, NMR, and Neutron log. Therefore, the flowchart of TOC calculation includes five main parts: (I) the shale content calculation using Gamma log; (II) the determination of shale distributions using Density and Neutron logs and cross-plot; (III) the calculation of total resistivity at different distribution types; (IV) obtaining porosity using core analysis, NMR and density logs; and (V) the calculation of TOC from modified Archie's equation.
 The results indicate that the shale content has a strong effect on estimation of water saturation and hydrocarbon saturation. Especially, the effect of shale content is exacerbated at a low water saturation. A more accurate flowchart for TOC calculation is established. Based on Archie's equation, we modify total resistivity and porosity by combining Gamma Log, Density Log, Neutron Log, NMR Log, and Cross-plot. An easier way to estimate porosity is provided. We combine the matrix density and kerogen density together and obtain them from core analysis. Poupon's et al. (1954) laminar model has some limitations when applying in shale reservoirs, especially at a low porosity.
 Literature surveys show few studies on the flowchart of TOC calculation in shale reservoirs. This paper provides some insights into challenges of well logs, core analysis in shale reservoirs and a more accurate guideline of TOC calculation in shale reservoirs.

Determination of Total Organic Carbon for Organic Rich Shale Reservoirs by Means of Cores and Logs

Resistivity well-logging devices respond to all of the electrically conductive matter found within their respective ranges of investigation To be consistent with this concept in shaly sand interpretation, the user must have some means to estimate the total rock porosity containing electrically conductive interstitial solutions and a means to estimate the contribution of each solution to the total conductivity It will be one f the purposes of this paper to show the user a method for ascertaining usable values of these important parameters for use in Archie's basic water saturation relationship A method for the evaluation of effective porosity from neutron and density well-logging responses has been developed by others, and is well documented in literature A method for the evaluation of total porosity, as defined herein, has not been described in literature In this paper, the neutron and density well-logging responses will be used to estimate the volumes of both effective and total porosities Before these volumes can be determined to any degree of reliability in heterogeneous shaly sands, the influences of constituents other than quartz and water must be recognized and nullified These constituents may be clay, cement or fragments of material other than quartz or clay, or more » hydrocarbon fluids which have densities different from that of interstitial water In the process of evaluating effective and total porosities, other distinguishing features about the reservoir rock may be recognized This additional information will help the user to understand the producibility of the reservoir rock of interest « less

Methods based on density and neutron well-logging responses to distinguish characteristics of shaly sandstone reservoir rock. [Effective and total porosity]

Determination of shale volume distribution is one of the most important factors that has to be considered in formation evaluation, since existence of shale reduces effective porosity and permeability of the reservoir. In this paper, shale volume and distribution (dispersed, laminar and structural) and formation effective porosity are estimated from well log data and cross-plots. Results show that distribution of shale is mainly dispersed with few of laminar ones, and the quality of reservoir (effective porosity) decreases with depth resulting in low productivity of gas wells drilled in lower zones. Good agreement of estimated shale volumes and effective porosities from neutron-density cross-plot with the values determined from gamma ray log (CGR) and core analysis demonstrates the accuracy and applicability of these plots in determination of petrophysical parameters from conventional log data.

https://iopscience.iop.org/article/10.1088/1755-1315/44/4/042002/pdf

Determination of Shale Volume and Distribution Patterns and Effective Porosity from Well Log Data Based On Cross-Plot Approach for A Shaly Carbonate Gas Reservoir

Mohammad Moeini

Papers

Determination of Shale Volume and Distribution Patterns and Effective Porosity from Well Log Data Based On Cross-Plot Approach for A Shaly Carbonate Gas Reservoir