Optimization Work Flow Maximizes Value of Unconventional Fields
Authors: Feder Judy 
Published: September 2019

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE-191779-18ERM-MS, “A Fast-Paced Work Flow for Well Spacing and Completions Design Optimization in Unconventional Reservoirs,” by Hoss Belyadi, SPE, and Malcolm Smith, EQT Corporation, prepared for the 2018 SPE Eastern Regional Meeting, Pittsburgh, Pennsylvania, USA, 7–11 October. The paper has not been peer reviewed.

Well spacing optimization is one of the more important considerations in unconventional field development. The essence of field development and optimization is to use completions design and well spacing to optimize the net present value (NPV) of the field on the basis of current commodity pricing, capital expenditure (CAPEX), operating cost, cycle time, and net revenue interest. A substantial variation in any of these essential factors must be studied to make sure the appropriate changes are accounted for in field development and optimization. A fast-paced and dynamic work flow has been developed that can be applied in different shale reservoirs to maximize the NPV of these assets. This paper describes the work flow, starting with a fracture model, then coupled with a production model using numerical simulation to obtain a calibrated model, and, finally, a detailed economic and sensitivity analysis to obtain the well spacing and completions design that will yield the highest NPV of the field.

Introduction

When well spacing systems (interlateral spacing) for various unconventional basins were developed, commodity pricing was much higher and completions job sizes were smaller than they are today. The majority of wells were completed with less than 1,300 lbm/ft of proppant. As operators increased job sizes and seized the benefit of higher production performance, discussions regarding increasing well spacing also took place.

After 2014, operators sought ways to stay economical at lower commodity pricing and began to consider feasible ways to reduce operational costs, improve well productivity, raise NPV/acre, automate processes and work flows, use machine learning (ML) to improve predictability, and optimize workforce efficiency. Optimal well spacing for any unconventional well depends on many factors, including gas price, capital and operating expense, acreage position and inventory, completions design, production performance, and lateral length. There is no one-size-fits-all well spacing for various completions designs. Performing a full analysis, therefore, is crucial to finding the optimal well spacing for each area, either analytically or numerically.

Factors such as geology, engineering, and economic analysis must be considered. For instance, optimal well spacing and completions design for a geologically noisy and complex reservoir will be invalid in a discreet and quiet area. Similarly, if well spacing and completions design were developed for a high-commodity-pricing environment, performing the same work flow and evaluation at lower commodity pricing would yield an increase in well spacing. The work flow described in the complete paper addresses all these factors and uses modeling, numerical simulation, ML, and linear programming to optimize NPV.