Meana Petro
PR-09IntermediaOla 2IADominio

Optimización del Diseño de Acidificación

En una frase

Chooses which wells will actually respond to an acid job, and what volume and placement to use.

El problema

Acid jobs are often scheduled by rotation rather than by candidate quality. A significant share produce no measurable gain, and because post-job evaluation is inconsistent nobody learns which wells were the wrong candidates.

Cómo funciona

Candidate selection combines skin estimated from well test or nodal analysis with damage-mechanism inference from production and completion history. Treatment design — acid system, volume, diversion — is then matched against the inferred mechanism and the field’s own job outcome database.

Datos necesarios

  • Pre-job well test or productivity index history
  • Completion and perforation detail, formation mineralogy
  • Historical acid job records with pre- and post-job rates
  • Water chemistry and scale analysis

Qué obtiene

  • Ranked candidate list with expected gain and the damage mechanism identified
  • Treatment design recommendation with diversion strategy
  • Standardised post-job evaluation comparing actual to predicted gain

Qué no puede hacer

Skin is an aggregate number that does not distinguish between damage types, so the mechanism inference relies on indirect evidence and is wrong often enough to matter. The candidate ranking is reliable at the top and bottom of the list and weak in the middle; we present it that way rather than as a precise ordering.

Cada página de capacidad declara una limitación real. Si un proveedor no puede decirle dónde termina su producto, no le están diciendo la verdad sobre dónde empieza.

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