Nuclear Magnetic Resonance (NMR), a valuable tool for Tar detection in a Carbonate Formation of Abu Dhabi.
Bibliographic record
Abstract
Nuclear Magnetic Resonance (NMR), A Valuable Tool for Tar detection in a Carbonate Formation of Abu Dhabi Walid Najia; Walid Najia Zakum Development Company ZADCO Search for other works by this author on: This Site Google Scholar Mohammad Shaban; Mohammad Shaban Zakum Development Company ZADCO Search for other works by this author on: This Site Google Scholar Hedhili Gossa; Hedhili Gossa Zakum Development Company ZADCO Search for other works by this author on: This Site Google Scholar Paolo Ferraris; Paolo Ferraris Schlumberger, Abu Dhabi, UAE Search for other works by this author on: This Site Google Scholar Vissapragada Badarinadh; Vissapragada Badarinadh Schlumberger, Abu Dhabi, UAE Search for other works by this author on: This Site Google Scholar Mario Petricola; Mario Petricola Schlumberger, Abu Dhabi, UAE Search for other works by this author on: This Site Google Scholar K.M.N. Namboodri K.M.N. Namboodri Schlumberger, Abu Dhabi, UAE Search for other works by this author on: This Site Google Scholar Paper presented at the Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, United Arab Emirates, October 2002. Paper Number: SPE-78485-MS https://doi.org/10.2118/78485-MS Published: October 13 2002 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Najia, Walid, Shaban, Mohammad, Gossa, Hedhili, Ferraris, Paolo, Badarinadh, Vissapragada, Petricola, Mario, and K.M.N. Namboodri. "Nuclear Magnetic Resonance (NMR), A Valuable Tool for Tar detection in a Carbonate Formation of Abu Dhabi." Paper presented at the Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, United Arab Emirates, October 2002. doi: https://doi.org/10.2118/78485-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)Abu Dhabi International Petroleum Exhibition and Conference Search Advanced Search AbstractDuring the geological history, water borne bacteria may react with oil and result in the formation of tar (synonymous of bitumen in this paper). The dynamics of the reservoir over its history may also leave some tar within the hydrocarbon zones. Tar occupies a portion of the pores and may plug partially or fully the pore throats, significantly affecting the fluid flow in the reservoir. Detection of tar is of high significance in the field development for understanding the recovery and effectiveness of water/gas injection.Tar can be easily identified in the water zones using the resistivity response. In the oil zone, it is difficult to separate tar and hydrocarbons by using exclusively a resistivity log. NMR transverse T2 relaxation contains useful petrophysical and geological information. The T2 histogram is a function of both fluid properties and pore size distribution. Tar is almost solid and the hydrogen it contains relaxes very fast because of its strong binding forces. The shortened T2 in the presence of tar results in lower NMR porosity, compared to the conventional Density-Neutron porosity. The missing porosity from NMR along with other conventional logs and wireline formation tester can be reliably used in the evaluation of tar in the formation. The results can be quantified with confidence after calibrating with core results.Two examples are presented from the carbonate formations of Abu Dhabi, in the Middle East, where tar evaluation was successfully performed using NMR, Density- Neutron and MDT data.IntroductionPresence of tar in an oil reservoir due to its negative effect on flow performance in porous media may represent a significant problem for field management if not recognized and characterized properly. It is essential to know as early as possible volume and spatial distribution of tar to minimize field development risks, and optimize drain areas while guaranteeing effective pressure maintenance.The giant Middle East field studied in this paper is an anticline structure consisting of three major reservoirs. The reservoirs under investigation, respectively 40 &140 feet thick Lower Cretaceous carbonates, are the top and middle ones. Both reservoirs have been developed using five spot patterns with 1.4 km spacing between the injectors and producers. One of the key uncertainties in the Northern and Eastern part of the field is the area and vertical distribution of bitumen in the reservoirs. Development optimization studies for the Northern and Eastern flank areas recommended several producers and injectors in phases so as to enhance the production from the field. From reservoir development perspective, identification and distribution of bitumen therefore, becomes crucial in order to optimize the horizontal well locations and placement of laterals. In addition, it is very critical to understand the impact of bitumen on the effectiveness of peripheral injectors for reservoir management.The bitumen is associated with the historical oil water contact (OWC) prior to tilting of the reservoir to the present day contacts. It is postulated that on tilting, a section of the reservoir was left with a residual hydrocarbon that degraded to bitumen.The approximate tar area distribution derived from an earlier study is displayed in Fig-1. This will actually be the starting point for a new detailed analysis.The paper discusses the historical approach for tar identification in this field and a quantitative methodology using the new technology NMR logs. Keywords: viscosity, reservoir, pore throat, tar, permeability, porosity, bitumen, porosity deficit, relaxation, well logging Subjects: Formation Evaluation & Management, Open hole/cased hole log analysis This content is only available via PDF. 2002. Society of Petroleum Engineers You can access this article if you purchase or spend a download.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".