In making the petrophysical calculations of lithology, net pay, porosity, water saturation, and permeability at the reservoir level, the development of a complete petrophysical database is the critical first step. This section describes the requirements for creating such a database before making any of these calculations. The topic is divided into four parts: inventory of existing petrophysical data; evaluation of the quality of existing data; conditioning the data for reservoir parameter calculations; and acquisition of additional petrophysical data, where needed. The overall goal of developing the petrophysical database is to use as much valid data as possible to develop the best standard from which to make the calculations of the petrophysical parameters. The second step in working with the petrophysical data is to evaluate the quality of each of these types of data. This step requires that the data inventory and database preparation steps are completed first so that this second step can occur as a systematic and complete process. The evaluation process is a "compare and contrast" exercise. The evaluation of log-data quality has many aspects. This should be noted in the petrophysical database. "Flags" of various types should be stored, for example, to denote intervals where the hole size exceeds some limit, or where there is cycle-skipping on the sonic logs. Logging tools sometimes become temporarily stuck as a log is being run. When the tool is stationary, each detector on it becomes stuck at a different depth, so the interval of "stuck" log will vary for each log curve. For example, the neutron log typically sticks over an interval approximately 10 ft above the stuck interval on a density log. It may be possible to "splice" in a replacement section of log from a repeated log section, or the invalid readings may simply be deleted. Second, each log is formally calibrated before the start of each logging run by various calibration standards. The logs are also checked again after the run. Calibration records may assist in determining the quality of the logs. Perhaps of equal importance are the written comments on the log heading made immediately after the job by the logging engineer. Third, systematic influences on the quality of log readings should be corrected. For example, if some of the wells are drilled with water-based mud (WBM), the effect of WBM-filtrate invasion on various resistivity logs can be quantified. This is done by computations made using the various resistivity logs in the same wellbore; however, where deep invasion of WBM filtrate occurs, offsetting wells drilled with oil-based mud (OBM) give a good comparison. The induction logs in OBM wells can provide accurate true reservoir resistivity values in thick hydrocarbon zones. See the chapter on resistivity and SP logging in this volume of the Handbook for more information on how invasion effects can be handled. Boreholes are not always right cylinders.
This article presents brief summaries of detailed petrophysical evaluations of several fields that have been described in the SPE and Soc. of Professional Well Log Analysts (SPWLA) technical literature. These case studies cover some of the complications that occur when making net-pay, porosity, and water saturation (Sw) calculations. Prudhoe Bay is the largest oil and gas field in North America with more than 20 billion bbl of original oil in place (OOIP) and an overlying 30 Tscf gas cap. In the course of this determination, an extensive field coring program was conducted, which resulted in more than 25 oil-based mud (OBM) cores being cut in all areas of the field and some conventional water-based mud (WBM) and bland-mud cores in other wells. The background geologic understanding of the major reservoir, the Ivishak or Sadlerochit, and various technical studies have been presented in a number of technical papers.
A Sand Wash Basin well was drilled for an unconventional target for which the measured core properties did not match production for the well. The crushed-rock porosity for the core suggested a bulk-volume hydrocarbon (BVH) of 1.5 to 2.0 p.u., indicating that the stimulation would have to be draining at approximately 400 ft vertically. To resolve this incongruity for further field development, we investigated the validity of crushed-rock porosity and nuclear magnetic resonance (NMR) to accurately assess the resource. Initial results using conventional 2-MHz core NMR yielded results similar to those for crushed-rock porosity. Because unconventional rocks have very fast relaxations in NMR, it was then theorized that with the use of a high-resolution 20-MHz machine, the signal/noise ratio would improve and create a more-accurate quantification of porosity components. The results of using a high-resolution 20-MHz NMR showed a porosity increase from 6.5 p.u. using the Gas Research Institute (GRI) methodology (Luffel et al. 1992) to 14 p.u. on an as-received sample, creating a large increase for in-place calculations. As a result, a process termed sequential fluid characterization (SFC) was developed using high-resolution 20-MHz NMR to quantify all components of porosity (i.e., movable fluid, capillary-bound water, clay-bound water, heavy hydrocarbon, residual hydrocarbon, and free water). This method represents an alternative to crushed-rock methodologies (such as GRI and tight rock analysis) that will accurately quantify movable porosity as well as the other components without the errors introduced by cleaning and crushing. After investigating the application of SFC with the high-resolution 20-MHz NMR, it was identified that other unconventional plays (such as Marcellus and Fayetteville) have an average of 45% uplift on in-place calculations using SFC-based movable porosity. Identifying in-place volumes correctly can vastly improve the characterization of fields and prospects for unconventional-resource development, and, as is shown in this paper, SFC can be used to do so with a great effect on volume assessment in unconventional reservoirs.
With the help of artificial intelligence, BP says it needs 40% fewer workers to keep its natural gas flowing in Wyoming. A visitor to one of BP’s natural gas fields in Wyoming a few years ago might have noticed an odd sight: smartphones in plastic bags tied to pumps with zip ties. This was an early test of a multistate initiative by the oil giant to link a network of Wi-Fi sensors to an artificial intelligence (AI) system—one that now operates the Wamsutter field in Wyoming with far less human oversight than before. AI has come to the oil patch, accelerating a technical change that is transforming the conditions for the oil and gas industry’s 150,000 US workers. Giant energy companies like Shell and BP are investing billions of dollars to bring artificial intelligence to new refineries, oilfields, and deepwater drilling platforms.
Rathnaweera, Tharaka D. (Monash University /Nanyang Technological University) | Gamage, Ranjith P. (Monash University) | Wei, Wu (Nanyang Technological University) | Perera, Samintha A. (The University of Melbourne) | Haque, Asadul (Monash University) | Wanniarachchi, Ayal M. (Monash University) | Bandara, Adheesha K. (Monash University)
Over the last several decades, many studies have generated a large amount of proppant performance data, but these studies have only focused on proppant conductivity, with no attention to how proppant mechanical properties vary under loading conditions. The impact of mechanical behaviour on proppant performance can only be fully understood by the combined investigation of micro-structural and mechanical changes with increasing loading. Therefore, this study aims to identify such micro-structural behaviour, and in particular the impact on proppant mechanical properties. Proppant samples were tested under one-dimensional compression loading using high-resolution X-ray CT scanning technology. The reconstructed images taken at different load stages were analysed to capture the micro-structural behaviour and finally correlated with the mechanical behaviour of the proppant.
According to the results, there are significant micro-pore voids inside the proppant mass. When the proppant has a higher degree of porosity, there is a considerable reduction of the compressive strength which is not favourable for hydro-fracturing treatment designs. Moreover, it is clear that the brittleness of the proppant decreases with increasing porosity, as its Young’s modulus reduces with increasing pore voids. Therefore, it is important to have high manufacturing standards to achieve effective proppant performance at great depths. The micro-structural behaviour under increasing loading was investigated by performing comprehensive CT image analysis using Drishti software. According to the results, under compressive loading, proppants cleave and generate large fragments like a flower, and this happens suddenly and quite violently through the material. Interestingly, post-failure analysis revealed that the failure mechanism of a single proppant consists of three major stress levels, where initially proppant fails at a high stress level and gains some crushing-associated strength at later stages.
Unconventional oil/gas production has recently attracted the research community due to the uncontrollable increasing demand for primary energy sources (Perera et al., 2016; Wu et al., 2017). Since this method provides a good solution to energy scarcity, over the last several decades, the industry has tried to enhance the production rate, mainly focusing on production enhancement techniques which can be effectively used in the energy extraction from sub-surface geological formations. Of the various options, hydraulic fracturing is one of the best ways to enhance oil/gas extraction, as it increases the formation’s permeability, allowing easy movement of the extracted oil/gas towards the production well (Rutledge and Scott, 2003; Orangi et al., 2011; Vengosh et al., 2014; Wanniarachchi et al., 2015). However, this process may be jeopardised due to the high stress levels acting on the formation at great depths (both vertical overburden and confining pressures). One possible consequence is re-closure of the fracture network under downhole stress conditions, which severely affects the post-fracturing production. Such issues can negate the use of proppant as a hydraulic fracture treatment method where proppants injected with the fracturing fluid prop the fractures, withstanding the fracture-closure stress (Wanniarachchi et al., 2015). Although the proppant gives a reliable solution to overcome this issue (propping the fracture network), sufficient closure stress can cause mechanical failure of the proppant, changing the fracture conductivity, causing re-closure of the fracture network, and altering the bulk properties of the proppant pack, which can negatively influence oil/gas extraction. Therefore, it is important to understand the mechanical behaviour of proppants under downhole stress conditions before injecting proppant with the hydro-fracturing fluid.
This paper was prepared for presentation at the Unconventional Resources Technology Conference held in Houston, Texas, USA, 23-25 July 2018. The URTeC Technical Program Committee accepted this presentation on the basis of information contained in an abstract submitted by the author(s).
This paper develops innovative methods for analysis of some important exploration and production problems in shale petroleum reservoirs such as the determination of burial maturity and maturation trajectories, and determination of sweet spots with the use of Modified Pickett plots. The methods are explained with data from 226 Niobrara wells.
Pickett plots have been used historically as a powerful tool for petrophysical analysis of well logs. The plots represent a snapshot on time that corresponds to the time when the well logs are run. Pickett plots rely on pattern recognition observable on log-log crossplots of porosity vs. true resistivity. The analysis has been used in the past primarily for determination of water saturation. However, the plot has been extended throughout the years for evaluation of other parameters of practical importance including, for example, permeability, process or delivery speed (permeability over porosity,
In this paper, Pickett plots are extended from representing a snapshot on time to representing millions of years of burial and maturation trajectories. The proposed method is explained with data from 226 Niobrara wells. The modified Pickett plots leads to curved lines of water saturation (Sw) and BVW. The maturation trajectories on the plot help to explain compaction and why as maturation increases to generate oil and gas condensate, resistivity goes up. However, as maturation increases to generate dry gas in the Niobrara, resistivity decreases. The Lopatin time-temperature index (TTI) is also included in the modified Pickett plot.
The proposed methodology also allows estimating changes in pore throat sizes updip and downdip of a structure, as well as in a basin flank. The ability to combine maturity, pore throat sizes, as well as porosity and process speed in a single graph makes the modified picket plot a valuable tool with potential to locate sweet spots in shale petroleum reservoirs to locate areas for possible improved oil recovery (IOR) and enhanced oil recovery (EOR).
The key contributions of this paper are generating an original method for determining burial maturity and maturation trajectories of shale petroleum reservoirs with the use of modified Pickett plots, as well as determining changes in pore throat sizes in different places of a structure, which lead to the location of sweet spots. Although the methodology is explained with data of the Niobrara shales, it should have application in other shale petroleum reservoirs of the world.
There has been recognition in the oil and gas and mineral extractive industries for some time that a set of unified common standard definitions is required that can be applied consistently by international financial, regulatory, and reporting entities. An agreed set of definitions would benefit all stakeholders and provide increased - Consistency - Transparency - Reliability A milestone in standardization was achieved in 1997 when SPE and the World Petroleum Council (WPC) jointly approved the "Petroleum Reserves Definitions." Since then, SPE has been continuously engaged in keeping the definitions updated. The definitions were updated in 2000 and approved by SPE, WPC, and the American Association of Petroleum Geologists (AAPG) as the "Petroleum Resources Classification System and Definitions." These were updated further in 2007 and approved by SPE, WPC, AAPG, and the Society of Petroleum Evaluation Engineers (SPEE). This culminated in the publication of the current "Petroleum Resources Management System," globally known as PRMS. PRMS has been acknowledged as the oil and gas industry standard for reference and has been used by the US Securities and Exchange Commission (SEC) as a guide for their updated rules, "Modernization of Oil and Gas Reporting," published 31 December 2008. SPE recognized that new applications guidelines were required for the PRMS that would supersede the 2001 Guidelines for the Evaluation of Petroleum Reserves and Resources. The original guidelines document was the starting point for this work, and has been updated significantly with addition of the following new chapters: - Estimation of Petroleum Resources Using Deterministic Procedures (Chap.
The Piceance Basin is located in western Colorado and covers an area of about 7,100 square miles1. A spoon-shaped basin, sediments reach a maximum depth of about 20,000 feet near the central portion, and encompass rocks ranging in age from Tertiary to Precambian. The basin is bounded by outcrops on the east, west and south, and by uplifts that separate it on the north from the Sand Wash Basin and on the northwest from the Uinta Basin. There are massive tertiary intrusives – laccoliths and volcanics – on the southeastern portion of the basin that have elevated the heat flow there and a massive basaltic flow extended west across a portion of the central basin to form the caprock of the Grand Mesa area. Figure 1 is a geologic map of the Piceance Basin in western Colorado1.
Oil and gas exploration in the Piceance Basin dates to the early 1900’s, with the discovery of the Rangely field in the northwest portion of the basin. With the exception of Rangely and a few other small fields, the basin is dominated by wells that produce natural gas. Oil and gas production from the Piceance Basin Mancos was first established in the Rangely field area, as well2. To date, about 30,000 wells have been drilled and completed in the basin, and the vast majority of those that are active, about 15,000 wells3, are producing from the Upper Cretaceous Williams Fork formation sands of the Mesaverde Group, in the central portion of the basin
Mancos Exploration to Date
Gas production was established from the Mancos B sand along the western flank of the basin, an area known as the Douglas Creek Arch, that separates the Piceance and Uintah basins, near the Colorado-Utah state line. The Mancos B sand is a sandy interval in the upper portion of the massively thick Mancos Group shale. In May 2001, WPX Energy began gas production from the lower portion of the Mancos shale in the central portion of the basin, in its vertical Vassar Heath RMV 229-27 well, at Section 27-T6S-R94W, in the Rulison Field.
To date, about 120 Mancos shale oil and gas wells have been drilled, completed and placed into production, not including the aforementioned Mancos B sand wells located along the Douglas Creek Arch and the wells in the Rangely field area. About 56 of these wells are vertical completions, and about 64 are horizontal completions. Figure 2 shows the total production from these wells, along with the Nymex price of natural gas. Note that exploration for Mancos shale gas wells began around the time that Nymex natural gas prices began to decline, and that since gas prices reached a low in early 2016, Mancos development has been limited to a few wells per year.
Huang, Qingfeng (Abu Dhabi Marine Operating Company) | Arii, Hiroaki (Abu Dhabi Marine Operating Company) | Sadok, Abdel Aziz Ben (Abu Dhabi Marine Operating Company) | Baslaib, Mohamed A. (Abu Dhabi Marine Operating Company) | Sasaki, Akihito (Abu Dhabi Marine Operating Company)
Infill drilling has been recognized as a common practice to accelerate oil production and increase ultimate recovery. Infill drilling can be performed under different drive mechanisms (primary, secondary and tertiary). With a certain history of development, many oil fields have become mature to some extend with waterflood. In order to have a sustainable corporate development plan, pattern flood towards further EOR is considered. Nonetheless a tertiary process as a whole project involves massive investment with high risks and uncertainties. If incremental oil can be recovered via infill drilling as a transition, the investment can be partially offset and justified. Infill oil producers as components of pattern flooding can be accelerated while pattern water injectors can be scheduled in a latter phase.
Two main approaches are used in the determination of infill potential. The first one uses empirical techniques to determine infill wells number and spacing based on volumetric calculation of oil in place. It ignores impact of reservoir heterogeneity and continuity. The second approach relies on numerical simulation coupled with optimization algorithms. Based on the second approach, this paper presents a new one that looks at the remaining mobile oil distribution at the time of infill drilling, and locates the optimum pattern configurations whose centers have the maximum sum of stacked mobile oil thickness of each pattern. Each square pattern has only one oil producer centered without corner water injectors.
An automated algorithm has been generated to identify infill potential and locations. First, the remaining stacked mobile oil distribution is calculated; second, multiple average-spacing pattern realizations are placed on the field, and only one realization is chosen since it has the highest value of summing mobile stacked oil thickness; third, remove infill wells which have nearby existing oil producers in the pattern area; then, select perforation intervals with a certain criteria to avoid early water/gas breakthrough; after that, an automatic schedule of infill wells is output for simulation run to screen potential infill wells having minimum impact on the existing wells.
This infill drilling approach identifies potential pattern oil producers to recover mobile oil, sustain the production plateau and increase oil recovery, prior to planning pattern water injectors. In offshore field, tower slots are limited, so some infill wells can be utilized to workover/sidetrack future inactive wells to save slots. Infill wells can be coupled utilizing conventional completion strategy to minimize wells count. These wells act as a smooth transition to future pattern configurations towards further EOR to recover remaining oil.
For the first time, this paper demonstrates a novel approach of determining infill locations by chasing in-situ stacked mobile oil thickness at the specified time step. An automated program is generated to efficiently identify infill wells at any time step. A complete workflow of infill drilling and transition to pattern flood is prepared for a full image. This process also suits both new and mature field. Pattern flood is accelerated by drilling infill oil producers and followed by water injectors.