Ultradeep Resistivity Inversion for Increased Confidence in Areas of Seismic Uncertainty

Nigel, Clegg (Halliburton) | Michael, Welch (Halliburton) | Bronwyn, Djefel (Halliburton) | Maarten, Wachter (Wintershall) | Jarle, Pedersen (Wintershall)

OnePetro 

Abstract

A high risk of suboptimal well placement exists in new field development where seismic uncertainty can be great. Recent ultradeep resistivity measurement developments provide great benefits for identifying and optimizing the well path position within a given stratigraphic sequence. This paper presents a case study in which an operator planned to place wells 10 m TVD below the reservoir top because of seismic uncertainty of the top reservoir pick. To help mitigate this subsurface risk, the field development plan required real-time well placement optimization, using both standard formation evaluation data and an ultradeep azimuthal resistivity service. In this case-history, the ultradeep inversion canvases could be used to identify the well path position within the reservoir, as well as provide sufficient confidence to steer the well closer to the reservoir top than originally planned.

Multiple geological models, created from nearby offset wells and seismic grids, represented the expected seismic uncertainty of 5 to 15 m TVD. To identify the optimal measurement setup for real-time operations, resistivity modelling illustrated the effect of frequency and spacing on the data, producing multiple inversions for each geological scenario. After drilling began, real-time inversions for the ultradeep resistivity data were initially qualified using standard formation evaluation data, including both deep azimuthal resistivity and azimuthal density images. Multiple inversion canvases from various spacings and frequencies identified several formation features, including distances to the top and base of the reservoir. The quantified uncertainty of these results assisted in the evaluation of the inversion quality.

When close to the reservoir top, the wellbore position indicated in the ultradeep inversion canvases matched the interpretation from the conventional logs, which provided increased confidence in the inversion canvas results at distances farther away. This enhanced reservoir knowledge enabled the operator to progressively raise the well path to 5 and to 2 m TVD from the reservoir top. Except for strategic geosteering decisions based on expected faults positions from the seismic data, the operator made most well-placement decisions, across multiple wells, using ultradeep resistivity data. The high data quality and close collaboration within the subsurface team quickly led to high confidence in the inversion results. Integrating the full suite of available data, from shallow to ultradeep measurements in a comprehensive interpretation, provided better reservoir understanding, resulting in optimal well placement.

This paper presents formation evaluation results used within an integrated well-placement optimization service from a new field development. The integrated data qualified the results for an ultradeep resistivity tool. Confidence in the tool results enabled the operator to place wells much closer to the reservoir top than initially planned, in an area of seismic uncertainty.